Digital Crimes Investigates: Counterfeit Tales
Digital crime-fighterDonal Keatingrevisits the podcast, but this time… it’s personal. *cue dramatic crime-fighting music* The Director of Innovation and Research of the Digital Crimes Unit (DCU) at Microsoft joins hostsNic FillinghamandNatalia Godylato regale us with the origin story of the DCU and his captivating career exploits.Whether it’s tales of his early days preventing Windows 98 counterfeits in Ireland or the many international law enforcement raids he’s participated in…there’s no shortage to Donal’s crime-fighting adventures.In This Episode, You Will Learn:• The mission of Microsoft’s DCU and the techniques used to combat fraud• The events and needs that led to the creation of a forensic analytic lab at Microsoft• How counterfeiting and intellectual property crime have evolved over the years with advanced technology• What it’s like partnering with law enforcement to take down criminals around the worldSome Questions We Ask:• What does a day in the life of Donal look like in the DCU?• Was there ever a counterfeit example that shocked Donal at just how good it was?• With so many shifts in Donal’s work, what in his background has prepared him to stay on top of the changes?• What does a digital crime fighter do in their time off?Resources:Donal’sLinkedInhttps://www.linkedin.com/in/donal-keating/Nic’s LinkedInhttps://www.linkedin.com/in/nicfill/Natalia’s LinkedInhttps://www.linkedin.com/in/nataliagodyla/Microsoft Security Bloghttps://www.microsoft.com/security/blog/Transcript(Full transcript can be found at https://aka.ms/SecurityUnlockedEp17)Nic Fillingham:Hello, and welcome to Security Unlocked, a new podcast from Microsoft where we unlock insights from the latest in news and research from across Microsoft Security engineering and operations teams. I'm Nic Fillingham.Natalia Godyla:And I'm Natalia Godyla. In each episode, we'll discuss the latest stories for Microsoft Security, deep dive into the latest threat intel, research and data science-Nic Fillingham:And profile some of the fascinating people working on artificial intelligence in Microsoft Security.Natalia Godyla:And now, let's unlock the pod. Hi, Nic. How's it going?Nic Fillingham:Hello, Natalia. It's going well. How are you?Natalia Godyla:It's going well. I am super-excited for this episode, because it will be a trip down memory lane. We're gonna be talking about counterfeiting CDs and Beanie Babies. Well, Beanie Babies aren't covered in this episode, but they're counterfeited.Nic Fillingham:So we were, we were having a conversation before we started recording about, you know, things that have been counterfeited, and one of the examples that we stumbled upon was Beanie Babies, and I said, "What's a Beanie Baby?" And Natalia said "How do you not know what Beanie Babies are?" So 15 minutes ago, you, you educated me on a Beanie Baby, and I've learned something about you, is that you collected Beanie Babies. Is that right? You were in the Beanie Baby fad. You were in the, the trend.Natalia Godyla:Oh, yes. Yes. Beanie Babies and Pokemon cards. I definitely collected them.Nic Fillingham:Do you still have your Pokemon cards?Natalia Godyla:Yes. Yes, I do.Nic Fillingham:And do you still have your Beanie Babies?Natalia Godyla:I've got one Beanie Baby left.Nic Fillingham:Do you know, with certainty, that it is not a counterfeit Beanie Baby?Natalia Godyla:I don't, but I don't think I wanna find out.Nic Fillingham:If only there were some kind of technology. Maybe a, a hologram or something, embedded into the Beanie Baby for you to have a high degree of certainty-Natalia Godyla:(laughs)Nic Fillingham:That it was real.Natalia Godyla:(laughs)Nic Fillingham:And I'm talking about holograms because our guest on the podcast today, Donal Keating from the DCU, walks us through his journey into security, and his path to Microsoft, and how he spent a lot of his career in the anti-counterfeiting space. And we talked about CDs, we talked about counterfeiting CDs and optical discs. This was very exciting for me. We talk about the period in time when I was actually joining Microsoft, which was when Windows XP was coming out, and so the whole, you know, hologram on the CD, and you hold it up to the light, and there'd be different colors and pictures, like...Nic Fillingham:That was all very exciting. I guess that must have been early 2000s. That was a-, that was super-exciting when that was happening, so this was a, this was a great conversation, and I think we also talk about chickens at some point, too. I don't, I d-, I'm not sure how we got there, but we cover a lot of ground in this conversation.Natalia Godyla:And with that, I feel like we shouldn't keep people hanging. On to the pod.Nic Fillingham:On to the pod.Natalia Godyla:Hi, Donal. Welcome back to Security Unlocked. Thanks for joining us for a second time.Donal Keating:Thank you. I'm delighted to be here.Natalia Godyla:So Donal, you are the director of research and innovation of the Digital Crime Unit. I know that you've talked a little bit about what you did in our last episode, but would you mind giving the audience a refresher? What does a, a day in the life of Donal in the Digital Crimes Unit?Donal Keating:Well, e-each day is different, obviously, because when you're sort of working on the, on the side of security and crime-fighting, people evolve very rapidly, so there is no set pattern of what I do every day. But I am lucky to have a relatively unique position in the DCU, we call it the Digital Crimes Unit, in that I work across all of the different pillars th-, that we fight, and I also the opportunity to work, uh, work across the company, so... And we're always looking for new techniques, new data sources, and new crime mechanics, and I tend to get involved in, in the things that are new. So it's a very interesting job. As someone said, there's not many jobs where you wake up in the morning and look at the news and say, "What's going to be on my plate today?" But-Natalia Godyla:(laughs)Donal Keating:Working in this space tends to be that sort of a job.Natalia Godyla:And how did you end up in this role? What has been your path not just to Microsoft, but security? I know, a big question.Donal Keating:Oh, my. (laughs)Natalia Godyla:(laughs)Donal Keating:Once upon a time, Mammy Keating and Daddy Keating met. E-e-e-, um...Natalia Godyla:(laughs)Donal Keating:So, if I start-Nic Fillingham:And where was that, Donal?Natalia Godyla:(laughs)Donal Keating:Sorry? Wh- where was that?Nic Fillingham:Yeah, where was that?Donal Keating:That was in, that was in Ireland. So I, I grew up in-Nic Fillingham:Paint, paint us the picture. Like, it's, tell... I want beautiful, rolling green countrysides. I want-Donal Keating:(laughs)Nic Fillingham:Paint me that beautiful picture of Ireland.Donal Keating:Uh, well, uh... (laughs)Natalia Godyla:(laughs)Donal Keating:I don't know if I'm gonna go back that far. It's, that's before Moses was a boy.Nic Fillingham:(laughs)Natalia Godyla:(laughs)Donal Keating:So my parents are Irish. Uh, father an engineer, my grandfather an artist. My other grandfather was a blacksmith. So sort of technology had always been in the family. When I was growing up, uh, I guess my parents had been a product of the, of the war, and Ireland, at the best of times, didn't have very much, so the, the ability to make things and figure things out from first principles was always p-pretty important, uh, in my family.Donal Keating:So I grew up. My brother's, uh, an engineer. A c-, a civil engineer, built a very successful company in civil engineering. So I guess I was the black sheep of the family. I became a physicist, and when I graduated from physics, it was in the 1980s. I won't say exactly when, but the unemployment rate in Ireland at the time was in the high 20s, I believe, and for new graduates, there was pretty much two, three jobs a year going, and I certainly wasn't in the top two or three percent of the graduates coming out of the country, so I emigrated, like a lot of Irish people do, and my first stop was the UK.Donal Keating:So I got a job as a young, very green physicist. The only advantage I have is I had done applied physics, so I was to run a lathe as well as do some calculations, and I started to work for a, a UK company that was a venture capital-funded start up, looking at some very interesting optical technology. So my major was in opto-electronics, and this company was involved in the research into storage media. And at the time, CD audio had been quite the technology. C-, recordable CD had not been yet invented, but there was a space in the market for what was considered archival media, and this company had some very innovative and patented technology which we called Mothi. It was a, a recordable media that effectively made a mechanical mark. So it wasn't just a change of reflection. There was actually a mechanical mark on the media. And b- (laughs), I won't even go into the capacities of these things in, in today's world.Nic Fillingham:Almost like a vinyl record?Donal Keating:Uh, a-, well, uh, almost like a vinyl record, but at a nano scale. So a laser would... What normally it would do with m-, recordable media is, a dye would absorb, or not absorb and a-allow light through to the reflective layer beneath. The trick of this technology, called WORM, uh, write once read many, was a layer that looked a little bit like an egg box, and when the laser hit the texture, it would blow a bubble in the egg box, therefore making it reflective, and the company name was Plasmon, which actually refers to a physical phenomenon that means a surface that the, uh, incident light gets redirected along the surface of the incident plane.Donal Keating:So i-, it was just an interesting piece of technology. I worked for that company for six years, starting out knowing nothing, and worked for an incredible mentor engineer, a guy by the name of Bob Longman, who taught many engineers like me. He was quite a legend.Donal Keating:And through that company, it was like pure R&D work. We knew what the end goal was, but how to get there was entirely uncharted.So we got to work on all sorts of interesting, uh, technologies. But that really was the beginning of a skillset that I think everyone in security needs, and, uh, particular in research innovation. It's, when there aren't train tracks, how can you look at a problem, split it into smaller problems, and do things that you can measure, observe... Uh, basically articulate, "Well, okay, these three things happen. Therefore, what does it mean for the bigger picture?" So that reframing the question was training that I got right when I, when I graduated. So that was the start.Nic Fillingham:I think I i-interrupted you, Donal, but what was the... Did you tell us? What was the capacity? What was the storage capacity of this early CD-Donal Keating:(laughs) -Nic Fillingham:Technology. Nic Fillingham:I'm assuming it was small.Donal Keating:it was-Nic Fillingham:I'm assuming that's, that's Nic Fillingham:... the giggle your-Donal Keating:It was small, yeah.Natalia Godyla:(laughs)Donal Keating:540 megabytes was considered this huge enormous storage capacity.Nic Fillingham:But that's much smaller than the, the theoretical max of uh, cd's. No, it didn't say you only get to about 714 meg or something?Donal Keating:Yeah. Yeah but that, that was yeah but that was a CDR, and now we got DVDR, and yeah but these are capacities like if you pick a USB now, the tiny, tiny, tiny surface area will contain ten times that capacity. You know you look at floppy discs and you know, you look at the evolution of it. Really truly the laws of physics are being uh, like hard disc drives which I, at one stage I worked for Seagate, I'm like come to the, my narrative, but even when I was at Seagate in the 90's, the idea that you were coming close to the capacity of what a platter could hold.Donal Keating:They continue, hard drives, continue to push the limits. They're still uh, following Moore's at a phenomenal rate. Like if you look at a technology like hard drive, and you had to start that from scratch, people would say that's impossible. That is absolutely impossible to get that performance you know, even if using a huge design team.Donal Keating:But that's the great thing about evolution, you start off with something small you tweak it, you tweak it, you tweak it you put economic pressure on it to make it faster and bigger and you end up with here we have hard drives today same with Solid State. Solid State technology in another 20 years time. There will still be Solid State and it'll be faster and bigger and better than all the rest of it.Nic Fillingham:I thought you were sort of going to be comparing that early technology. That mech, that mechanical I forget the, the words you use but that mechanical mark on the disc. I thought you might have been comparing that to sort of later uh, technologies for writing to a CD. But you were, you were talking about CD's in general. Yes the capacity of a CD is, is obviously very very small.Donal Keating:Yeah. So the, the sort of people that were interested in it were people who needed archival technology. So uh, they worked with the British Library for instance was one of their um, audiences. But also company records and you know things that needed very good archival life. So, what you might not know is that your CDR um, if you've kept them in a drawer for 20 years will not be producing all the pictures that you thought you'd put onto your CDR.Donal Keating:And those technologies break down relatively quickly. So this was a, a technology that they said would um, stay on the shelf for a long time.Nic Fillingham:Why was that? The material is sort of susceptible to pressure change, temperature change, what, what is it?Donal Keating:Well with a recordable CD for instance is a dyeing. And dyes tend not to be, not to be stabled. You know you look at an old book even when it's closed up. The pictures in the, in your old books would be faded from what they were. Well if you need that high contrast and, and you have fading with your dye, you're gonna loose fidelity.Donal Keating:That's really just comparing this technology and CDR which is you know, but, the bit that I'm getting to is, you might have recording mechanisms that store data for a long time but the drives that read those do not store for a long time. Donal Keating:So, back then it was all scuzzy interfaces. To find a PC with a scuzzy interface now would be a, would be a whole, a whole piece of work. So, the reason the Cloud is gonna be so much better for storing data is regardless of what the readout technology is going to evolve with the Cloud.Donal Keating:I was kinda lucky in my career in that I was at the right place at the right time. So I worked for a number of companies that basically built CD manufacturing in Ireland. I hopped around those companies being part of the supply chain to Microsoft. So the very first indication of security, Microsoft introduced what we called an Innerband Hologram on I want to say was Windows 98.Donal Keating:It was a security feature to try and make counterfeiting of the Windows 98 dix, more difficult. Long story short, Microsoft decided themselves that they wanted a CD manufacturing plant. And they recruited me. At the time I really want to work for Microsoft. I had been a supplier to them and they had been pretty aggressive as customers. So I, I wasn't a terribly keen employee but they made it worth my while to join Microsoft to build them a CD-ROM plant in Dublin which I did.Donal Keating:We got that up and running. And just at that time, a team in the US wanted even more secure CD manufacturing. So at the time, one of the great ways of making money very easily was to produce either Office 97 or Windows 98 CD's and sell them. Now, you could make money in different ways. You could just bootleg them and make recordable CD's, but people then knew that they were buying something cheap and cheerful. There was, you get a few bucks for it but you weren't gonna make big dollars. Donal Keating:But the more sophisticated criminals did is they made visual pass offs, like very very good pass offs of the product. Packaged them up and even it into the supply chain. So today everyone is conscious of supply chain attacks. Solar winds being an example and in the recent past supply chain attacks have been all over the business. But if you go back to those times, people didn't really consider the supply chain attack. And one of the significant vulnerabilities in the software industry back then was, there was this whole world of people prepared to make very, very sophisticated counterfeits. Donal Keating:So, I was working for Microsoft at the time and there had been some legal cases chasing down counterfeiters and the, they had a newly appointed attorney in Europe looking after the counterfeiting team and we got talking and it was just one of those things that you know, you suddenly meet someone who knows what they really want to do and I knew how the product was made. And I said, "Look. All, all of the, the way you're going about this identification of counterfeit is all wrong." You know. The, the example I think was that if something was misprinted, it was, if it was badly printed disc it must be counterfeit. Donal Keating:I've run en, enough CD plants to know you can have a bad day in printing discs. So that was the start of the concept of a proper forensic analytic lab that would look at product and say, "This is genuine or counterfeit." And that really was the start of getting into the security space. And then I guess was in the year 2000-2001 maybe.Natalia Godyla:What was your next step within Microsoft. What, what brought you to the role you have today?Donal Keating:Yeah, so actually at the time when, when I met the legal team for the first time I, I was transitioning out from running the CD plant to working on the anti-counterfeiting technologies. In fact I used to, I kinda had a role that was mostly based in the US uh, looking at hologram technology, fingerprinting technology, just a variety of technologies that are going to be used to protect our products. Donal Keating:But it became more and more interesting to me to chase the criminals rather than to try and protect the product. There was lots of people focused on protecting the product. There was very few people uh, focused on, on locking up the crooks. And I think that was from one side, from the traditional counterfeiting side. One of the things that you got to learn is the economics of being a, a criminal.Donal Keating:And they would save themselves as, as people but what's their motivation? How do they do it? You know, how do they communicate? So, that was way back then that seemed to be very interesting and exciting. So I did more and more of that. Like I said I went around the world. I was in raids all over the world of, of plants producing counterfeit discs.Nic Fillingham:Can you share any examples?Natalia Godyla:(laughs)Donal Keating:Yeah. yeah, yeah, yeah I can so, the, the more recent one actually that's back in 2013 because we pretty much stopped em' physically counterfeiting but back in 2013-2014, there was a plant in the Ukraine that had been, it, it had belonged to the old regime. There's a new regime comes in so they re-raid the plant and I, I got called in just because I knew about how to obtain evidence from a CD plant. So they just wanted a kind of an expert from Microsoft to help them obtain Donal Keating:... obtain the evidence from the plant. But I arrived at this factory, brought there by law enforcement, and they had these huge doors, big, enormous, big steel doors. But the bit that appealed to me was (laughing) two feet to the right of the door, there was actually a hole blown in the wall. The cops said that to do the raid, he said, "That door is too secure but the wall's not so secure." So they went through the wall.Donal Keating:I- I've done cases in- in Russia also. So everyone knows that counterfeiting is a problem, but one of the ways you- you protect yourself is if you have someone who is on the law enforcement side of the house who will not raid plants, that they are kind of under their protection. But what happens when you stop paying the protection money? So it turns out that Microsoft got pulled in because someone wasn't paying their protection money, uh, anymore, and law enforcement raided the f- facility. Donal Keating:I went there to analyze the evidence and testify that yes, this in fact was a Microsoft product that was being counterfeited. When the plant that had been raided realized that the law enforcement were taking it seriously, they obviously paid their dues again. So I'm in this police station in the morning, uh, we're taking the evidence, y- you know, gathering up the notes. And when you're handling evidence, you have these tags, so you take something out, do your analysis, and then you seal the bag and- and sign it. Donal Keating:Suddenly, there's an urgent request to go to lunch at, you know, 11:30 or something. Never a man to dodge lunch, we went off to lunch.Natalia Godyla:(laughs).Donal Keating:But the lunch went on about three hours, and when we came back I'm looking at my pile and I see all this stuff that I had already examined, but they're not my seals, it's not my signature. And I said, "Th- this is not what I looked at this morning." (laughs). "Oh yeah, that's- that's what you looked at this morning." (laughs).Donal Keating:It was the sort of environment where you don't- don't go and argue with anyone, so we just stepped away from that. There was some- some follow-up, but there was no confirmation that what that plant had been producing was Microsoft counterfeits and it all got swept under the carpet.Nic Fillingham:Donal, when I hear the word raid though, I think of paramilitary, I think of guns and- and- and all that. Is my mental image accurate? What, how- how sort of scary, how dangerous were these- these raids that you were a part of? Or are they a bit more sort of... Well, yeah, that- that- that's my question.Donal Keating:So generally with counterfeiting, they tend to be, they're not dangerous. So sometimes, mostly I would get called in after the raid had happened, so therefore there's no danger, the environment is secure. Remember, these manufacturers are doing it on behalf of someone else. It- it's like malware today, there's a whole bunch of different individuals in the supply chain. My specialization at the time was the- the actual plants themselves, so we were going to sites that it was a regular manufacturer who was just breaking the law. There wasn't that risk.Donal Keating:But since I came to the US, I moved for Microsoft to the US in 2013, I got hauled into a raid where someone was selling product keys, and for some reason the case was a Homeland Security case. And that's the first time that I've ever seen, I actually wrote up a report afterwards, um, I was there with a- a Microsoft colleague and he was ex-FBI, and to him, it was perfectly normal. But to an Irishman who has grown up on American TV, it looked like the real thing. Donal Keating:They had an address and we were going in to the address, but there's a briefing beforehand that has a SWAT and a whole bunch of agents that are going there now. We're invited along as the- the analysts, like to- to analyze what they find. But there's this briefing that starts off with, you know, if there's- if there's shootings, here's where the hospitals are. If it's, you know, serious, here's where the helicopters land. You kinda get this mental image built up that you're going to raid a super-secure and heavily-armed target.Donal Keating:In this case, the entire team arrive up (laughing), and the guy arrives out in his dressing gown. And- and his first words to law enforcement was, "I haven't counterfeited for a year." (laughs). Natalia Godyla:(laughs).Nic Fillingham:(laughs). Donal Keating:Working that closely with law enforcement was quite a buzz, but all of that was sort of intellectual property crime that I was focused on, and since then, since 2013, 2014, I have changed my focus pretty much entirely to protecting Microsoft customers. So taking all of those techniques and, you know, understanding about the way people behave, and looking at behavior of criminals. Donal Keating:And using data, in essence, to- to look for, I used to look forensically for evidence of did it come from an authorized supply chain or an unauthorized supply chain? We built some special technology to do that with microscopes and image matching and stuff. So taking a lot of those concepts and then applying it to data streams. Is this a normal behavior for this type of data? Where's the anomaly? What's the cause of it? All of those sorts of things.Natalia Godyla:Was there ever a counterfeit example that shocked you, that was just so close to truth that you were surprised? Like just awed at the counterfeit artistry?Donal Keating:Well, I will say absolutely, I'm- I'm in awe of the ability for people to make things that look so visually identical. And a- a counterfeit never, they never manufacture things in exactly the same way that we did it, so we would emboss a hologram, uh, the counterfeiters by and large produce labels. But boy, were those labels good visual pass-offs. You know, it became, I wouldn't say impossible but it actually became, you know, you need to put your glasses on to look at the th- thing and say, "Oh yeah, that's counterfeit."Donal Keating:But again, that's to someone who has knowledge of the product. Uh, I think a- a thing that a lot of people forget, specialists, people who look at this stuff all the time will look at it and say, "Oh, well, that's, you know, it's missing the T and I've got a small I here. And look, this- this color is a bit off." To someone who buys this product once every three years or once every two years there's no build-up of a reference library of, "You know what? If it looks good, it must be genuine. And in fact, there's a little sticker on it that says this is genuine." (laughs). Therefore, you're socially engineered into thinking yes, it's genuine.Donal Keating:Uh, I love- I love when you g- get products from Amazon and you, a little card comes out that says, "This is an authentic product because, you know, we've got the card that says it's an authentic product."Nic Fillingham:The certificate of authenticity, which is a little matchbox-Donal Keating:Uh, yeah.Nic Fillingham:... square of cardboard that, uh, (laughing)-Donal Keating:Yeah, yeah. Nic Fillingham:... has been printed on an inkjet printer. (laughing). And cut out with scissors.Donal Keating:Yeah. One of the things that criminals are very good at is social engineering people into thinking they're doing the right thing, in- in whatever area it is. Like they would give people additional stuff in counterfeit packages, and made them feel even better about themselves getting this really good deal online. Uh, you know, it- it's just the- the psychology of- of people, we're just not designed to be suspicious of everything. Which is great, but unfortunately for people who work in this space, you get suspicious of everything.Nic Fillingham:So we're rapidly moving away from physical media. My Xbox doesn't even have a- doesn't even have a disc drive anymore, so it's, you know, it's entirely- it's entirely online digital distribution. But I see there is still, there are still counterfeiters out there. There are still, you know, it's still probably big business in some parts of the world. Is that, are- are, do you still have your finger on the pulse or have you fully, uh, left that- that space?Donal Keating:I have fully left that space, but absolutely, you know, there- as long as there is a dollar to be made there will be people in that space. But it's just not- it's just not what Microsoft focuses our effort on. You know, there- there will always be people who wanna go and pick up- up Windows on a CD-R. What I would say is then they know the risks that they're taking. You know, they're- they're a self-selecting group. Donal Keating:You know, we always talk about make sure that you're patched and have everything updated and use good password security. Well, you can- you can lose all that if you choose to obtain your software on a recordable CD where it says, you know, "This- this is real stuff." You know, e- especially on a, at the OS level. When you're installing an OS from a disc before anything has been turned on and all your signatures have been updated, it- it- Donal Keating:It's really easy to- to build a device with a lot of malware on it. Therefore, that is an area that I have concerns about, is that your supply chain for your hardware is, y- you're not buying the thing that you can get for the cheapest price. You're- you're buying from your authorized channel, you're buying from people that are reputable. Donal Keating:I think one of the really important things in security is the reputation and, you know, trustworthiness of your supply chain. So that's not an area that we spend a huge amount of time in, but it certainly is a thing that, um, is- is of concern to me.Nic Fillingham:And Donal, I think you've already said this, but to reiterate, the- the- the principles and the learning from your time in- in forensics and in physical, uh, disk manufacturing and- and- and anti-counterfeit work is that the sort of human psychology and the social engineering that was a big part of that business continues to this day. And you were sort of bringing a lot of those learnings and principles forward, and you're just now applying them to, uh, new supply chains and- and new technologies. Is that- is that accurate?Donal Keating:That's accurate. The- the one other thing, we did start to get into what I would consider big data in 2013, 2014, when we started to take activation behavior. So as devices touch Microsoft's servers for activation or validation, starting to do analysis on- on, at a large scale. So there were a lot of indications back when that you could identify countries that had relatively high rates of what I would considered piracy, and they correlated well with what, with encounter rates of malware coming from Defender and th- the various AV companies.Donal Keating:So it- it started out as a narrative, uh, in 2013, 2014, that we had high piracy rates. You als- also had high levels of- of security issues on the devices. I think that has- that has continued to some extent, but now as we move to a more digital, and- and hopefully more secure, supply chain, that opportunity for people to, you know, put large volumes of physical product that have malicious doors on them is hopefully being removed. But the skillset that I learned in, you know, analyzing very large volumes of data, that sort of was the start of it.Donal Keating:In fact, the Digital Crimes Unit built some analytic environments, uh, originally on, you know, on-prem servers, and now we've moved over to Azure. That allows us to do very large-scale analytics of huge datasets. That was sort of borne of our analysis of activation and validation, um, six, seven years ago.Natalia Godyla:You've had a couple notable shifts. What else other than your background in analytics has prepared you, or have you done to prepare for these changes? Do you have any recommendations to somebody who might be experiencing a similar shift and wants to get up to speed for this type of role?Donal Keating:W- well, if it's in Microsoft, we are incredibly lucky in that we have some very, very smart people. I'd say that the number one skillset that you need in navigating this is your ability to pick up the phone and talk to someone and admit that you know nothing about it. You really do have to talk to people who have expert knowledge in the area. Because you can be great at cultivating data, but unless you understand really what it means down to a very, very granular level, not the- not the 101 version of it but the 201 and 301 version of what do these things mean? And in Microsoft, we also have the people from Microsoft Research. I've been helped enormously on the AI and ML side from people who have done this clustering on short strings. Donal Keating:There is no magic to any of this. You've gotta have the data, you've gotta have the right data, you've gotta have the cleaned data, but there are tooling that, once you have everything that you want, allow you to represent it in a way that is easy to manipulate and- and highlight the things that are important. So I would say what have I done? I've talked to a lot of people in Microsoft about how they do what they're specialized at.Nic Fillingham:And what about when you're not working on this stuff? What's, what do you- what do you like to do, Donal, in your- in your spare time? And does any of that, uh, bleed over into your professional life? Do you, uh, do you like to do your thinking when you're climbing walls or- or something? That was a terrible example, but- but what (laughing)- what-Natalia Godyla:(laughs).Nic Fillingham:What do you- what do you do for fun?Donal Keating:Well, when I'm working, my 150-pound dog, who really is a- a- a slobbering sweetheart-Natalia Godyla:(laughs). Nic Fillingham:Type of dog, breed?Donal Keating:He's an Anatolian Shepherd, specifically a Kangal. So-Nic Fillingham:I have a Great Pyrenees, which I believe is a- a distant cousin. Donal Keating:Oh, yes. Yes. Uh, his name is Pamuk, it's a Turkish breed and pamuk means cotton in Turkish. But when I'm working, um, he does kinda, because he's a big dog, I kinda like to think that, you know, hey, if we had a security team that just looked, you know, dangerous would people mess with our product? Natalia Godyla:(laughs).Donal Keating:So that's one thing that, you know, I- I- I do like to think about my job when I walk the dog. But I'm also something of an urban farmer. I have three chickens and I like to grow potatoes, because I'm an Irishman, and turnips and leeks and stuff in my tiny little garden. So.Nic Fillingham:Are your chickens laying at the moment? Because we have ducks, and my ducks have gone on strike and I'm not getting any eggs out of them at the moment.Natalia Godyla:(laughs).Nic Fillingham:I'm wondering if- if you're... I know- I know chickens and ducks are a- a different bird, so I am aware of that, but just wondering if it's, what are you seeing in your- in your chickens?Donal Keating:You know, I'm a data guy, so, um, we went from one egg per chicken per day in the summer to kind of nothing in the late fall, and then starting luckily on the 21st of December, we got a- a burst of eggs. And then we now, out of three chickens I get one a day. I'm not exactly sure which one is doing, is... Natalia Godyla:(laughs).Donal Keating:If one is producing all of 'em or they're firing every third day. But, um, yeah, we're- we're- we're production again. Nic Fillingham:I think we need some machine learning algorithms to, uh, monitor the egg producing habits of chickens and/or ducks to see if we can, uh, increase output. Donal Keating:Uh, for- for sure.Natalia Godyla:(laughs). Donal Keating:It- it's- it's the only way to go about it, eh? The problem though with AI is we'd need to get about half a million chickens, and then we'd have a pretty good answer.Natalia Godyla:(laughs).Nic Fillingham:(laughs). Natalia Godyla:Well, we definitely thank you for that, Donal. And thanks for joining us again on Security Unlocked. Donal Keating:You're very welcome. Thank you for having me back. Natalia Godyla:Well, we had a great time unlocking insights into security. From research to artificial intelligence, keep an eye out for our next episode.Nic Fillingham:And don't forget to tweet us @msftsecurity, or email us at firstname.lastname@example.org, with topics you'd like to hear on a future episode. Until then, stay safe.Natalia Godyla:Stay secure.
Judging a Bug by Its Title
Most people know the age-old adage, “Don’t judge a book by its cover.” I can still see my grandmother wagging her finger at me when I was younger as she said it. But what if it's not the book cover we’re judging, but the title? And what if it’s not a book we’re analyzing, but instead a security bug? The times have changed, and age-old adages don’t always translate well in the digital landscape.In this case, we’re using machine learning (ML) to identify and “judge” security bugs based solely on their titles. And, believe it or not, it works! (Sorry, Grandma!)Mayana Pereira, Data Scientist at Microsoft, joins hosts Nic Fillingham and Natalia Godyla to dig into the endeavors that aresaving security experts’ time. Mayana explains how data science and security teams have come together to explore ways that ML can help software developers identify and classify security bugs more efficiently. A task that, without machine learning, has traditionally provided false positives or led developers to overlook misclassified critical security vulnerabilities.In This Episode, You Will Learn:• How data science and ML can improve security protocols and identify and classify bugs for software developers• How to determine the appropriate amount of data needed to create an accurate ML training model• The techniques used to classify bugs based simply on their titleSome Questions We Ask:• What questions need to be asked in order to obtain the right data to train a security model?• How does Microsoft utilize the outputs of these data-driven security models?• What is AI for Good and how is it using AI to foster positive change in protecting children, data and privacy online?Resources:Microsoft Digital Defense Reporthttps://www.microsoft.com/en-us/security/business/security-intelligence-reportArticle: “Identifying Security Bug Reports Based Solely on Report Titles and Noisy Data”https://docs.microsoft.com/en-us/security/engineering/identifying-security-bug-reportsMayana’s LinkedInhttps://www.linkedin.com/in/mayana-pereira-2aa284b0Nic’s LinkedInhttps://www.linkedin.com/in/nicfill/Natalia’s LinkedInhttps://www.linkedin.com/in/nataliagodyla/Microsoft Security Blog:https://www.microsoft.com/security/blog/Transcript(Full transcript can be found at https://aka.ms/SecurityUnlockedEp16)Nic Fillingham:Hello, and welcome to Security Unlocked, a new podcast from Microsoft where we unlock insights from the latest in news and research from across Microsoft Security engineering and operations teams. I'm Nic Fillingham-Natalia Godyla:And I'm Natalia Godyla. In each episode we'll discuss the latest stories from Microsoft Security, deep dive into the newest threat, intel, research and data science-Nic Fillingham:And profile some of the fascinating people working on artificial intelligence in Microsoft Security.Natalia Godyla:And now let's unlock the pod.Natalia Godyla:Hello, Nic. How's it going?Nic Fillingham:Hello, Natalia. Welcome back. Well, I guess welcome back to Boston to you. But welcome to Episode 16. I'm confused because I saw you in person last week for the first time. Well, technically it was the first time for you, 'cause you didn't remember our first time. It was the second time for me. But it was-Natalia Godyla:I feel like I just need to justify myself a little bit there. It was a 10 second exchange, so I feel like it's fair that I, I was new to Microsoft. There was a lot coming at me, so, uh-Nic Fillingham:Uh, I'm not very memorable, too, so that's the other, that's the other part, which is fine. But yeah. You were, you were here in Seattle. We both did COVID tests because we filmed... Can I say? You, you tell us. What did we do? It's a secret. It is announced? What's the deal?Natalia Godyla:All right. Well, it, it's sort of a secret, but everyone who's listening to our podcast gets to be in the know. So in, in March you and I will be launching a new series, and it's a, a video series in which we talk to industry experts. But really we're, we're hanging with the industry experts. So they get to tell us a ton of really cool things about [Sec Ups 00:01:42] and AppSec while we all play games together. So lots of puzzling. Really, we're just, we're just getting paid to do puzzles with people cooler than us.Nic Fillingham:Speaking of hanging out with cool people, on the podcast today we have Mayana Pereira whose name you may have heard from a few episodes ago Scott Christiansen was on talking about the work that he does. And he had partnered Mayana to build and launch a, uh, machine learning model that looked at the titles of bugs across Microsoft's various code repositories, and using machine learning determined whether those bugs were actually security related or not, and if they were, what the correct severity rating should be. Nic Fillingham:So this episode we thought we'd experiment with the format. And instead of having two guests, instead of having a, a deep dive upfront and then a, a profile on someone in the back off, we thought we would just have one guest. We'd give them a little bit extra time, uh, about 30 minutes and allow them to sort of really unpack the particular problem or, or challenge that they're working on. So, yeah. We, we hope you like this experiment.Natalia Godyla:And as always, we are open to feedback on the new format, so tweet us, uh, @msftsecurity or send us an email email@example.com. Let us know what you wanna hear more of, whether you like hearing just one guest. We are super open. And with that, on with the pod?Nic Fillingham:On with the pod.Nic Fillingham:Welcome to the Security Unlocked podcast. Mayana Pereira, thanks for joining us.Mayana Pereira:Thank you for having me. I'm so happy to be here today, and I'm very excited to share some of the things that I have done in the intersection of [ML 00:03:27] and security.Nic Fillingham:Wonderful. Well, listeners of the podcast will have heard your name back in Episode 13 when we talked to Scott Christiansen, and he talked about, um, a fascinating project about looking for or, uh, utilizing machine learning to classify bugs based simply on, on their title, and we'll get to that in a minute. But could you please introduce you- yourself to our audience. Tell us about your title, but sort of what does that look like in terms of day-to-day and, and, and the work that you do for Microsoft?Mayana Pereira:I'm a data scientist at Microsoft. I've been, I have been working at Microsoft for two years and a half now. And I've always worked inside Microsoft with machine learning applied to security, trust, safety, and I also do some work in the data privacy world. And this area of ML applications to the security world has always been my passion, so before Microsoft I was also working with ML applied to cyber security more in the malware world, but still security. And since I joined Microsoft, I've been working on data science projects that kinda look like this project that we're gonna, um, talk today about. So those are machine learning applications to interesting problems where we can either increase the trust and the security Microsoft products, or the safety for the customer. You know, you would develop m- machine learning models with that in mind. Mayana Pereira:And my day-to-day work includes trying to understand which are those interesting programs across the company, talk to my amazing colleagues such as Scott. And I have a, I have been so blessed with an amazing great team around me. And thinking about these problems, gathering data, and then getting, you know, heads down and training models, and testing new machine learning techniques that have never been used for a specific applications, and trying to understand how well or if they will work for those applications, or if they're gonna get us to better performance, or better accuracy precision and those, those metrics that we tend to use in data science works. And when we feel like, oh, this is an interesting project and I think it is interesting enough to share with the community, we write a paper, we write a blog, we go to a conference such as RSA and we present it to the community, and we get to share the work and the findings with colleagues internal to Microsoft, but also external. So this is kinda what I do on a day-to-day basis.Mayana Pereira:Right now my team is the data science team inside Microsoft that is called AI For Good, so the AI for Good has this for good in a sense of we want to, to guarantee safety, not only for Microsoft customers, but for the community in general. So one of my line of work is thinking about how can I collaborate with NGOs that are also thinking about the security or, and the safety of kids, for example. And this is another thing that I have been doing as part of this AI for Good effort inside Microsoft.Natalia Godyla:Before we dive into the bug report classification project, can you just share a couple of the projects that your team works for AI for Good? I think it would be really interesting for the audience to hear that.Mayana Pereira:Oh, absolutely. So we have various pillars inside the AI for Good team. There is AI for Health, AI for Humanitarian Action, AI for Earth. We have also been collaborating in an effort for having a platform with a library for data privacy. It is a library where we have, uh, various tools to apply the data and get us an output, data with strong privacy guarantees. So guaranteeing privacy for whoever was, had their information in a specific dataset or contributed with their own information to a specific research and et cetera. So this is another thing that our team is currently doing.Mayana Pereira:And we have various partners inside and outside of Microsoft. Like I mentioned, we do a lot of work in NGOs. So you can think like project like AI for Earth several NGOs that are taking care of endangered species and other satellite images for understanding problems with the first station and et cetera. And then Humanitarian Action, I have worked with NGOs that are developing tools to combat child sexual abuse and exploration. AI for Health has so many interesting projects, and it is a big variety of projects. Mayana Pereira:So this is what the AI for Good team does. We are, I think right now we're over 15 data scientists. All of us are doing this work that it is a- applied research. Somehow it is work that we need to sit down with, with our customers or partners, and really understand where the problem is. It's usually some, some problems that required us to dig a little deeper and come up with some novel or creative solution for that. So this is basically the overall, the AI for Good team.Nic Fillingham:Let's get back in the way back machine to I think it was April of 2020, which feels like 700 years ago.Mayana Pereira:(laughs) Nic Fillingham:But you and Scott (laughs) published a blog. Scott talked about on Episode 13 called securing Nic Fillingham:The s- the software development lifecycle with machine learning, and the thing that I think both Natalia and I picked up on when Scott was talking about this, is it sounded first-, firstly it sounded like a exceptionally complex premise, and I don't mean to diminish, but I think Natalia and I were both "oh wow you built a model that sort of went through repro steps and passed all the logs inside of security bugs in order to better classify them but that's not what this does", this is about literally looking at the words that are the title of the security bug, and then building a model to try and determine whether it was truly security or something else, is that right?Mayana Pereira:That's exactly it. This was such an interesting project. When I started collaborating with Scott, and some other engineers in the team. I was a little skeptical about using only titles, to make prediction about whether a bug has, is security related or not. And, it seems. Now that I have trained several models and passed it and later retrained to- to get more of a variety of data in our model. I have learned that people are really good at describing what is going on in a bug, in the title, it feels like they really summarize it somehow so it's- it's doing a good job because, yes, that's exactly what we're doing, we are using bug titles only from several sources across Microsoft, and then we use that to understand which bugs are security related or not, and how we can have an overall view of everything that is happening, you know in various teams across different products. And, that has given a lot of visibilities to some unknown problems and some visibility to some things that we were not seeing before, because now you can scan, millions of bugs in a few seconds. Just reading titles, you have a model that does it really fast. And, I think it is a game changer in that sense, in the visibility and how do you see everything that is happening in that bug world.Natalia Godyla:So what drove that decision? Why are we relying only on the titles, why can't we use the- the full bug reports? Mayana Pereira:There are so many reasons for that. I think, the first reason was the fact that the full bug report, sometimes, has sensitive information. And we were a little bit scared about pulling all that sensitive information which could include passwords, could include, you know, maybe things that should not be available to anyone, and include that in a- in a VM to train a model, or, in a data science pipeline. And, having to be extremely careful also about not having our model learning passwords, not having that. So that was one of the big, I think incentives off, let's try titles only, and see if it works. If it doesn't work then we can move on and see how we can overcome the problem of the sensitive information. And it did work, when we saw that we had a lot of signal in bug titles only, we decided to really invest in that and get really good models by u- utilizing bug titles only. Nic Fillingham:I'm going to read from the blog just for a second here, because some of the numbers here, uh, are pretty staggering, so, again this was written 2020, uh, in April, so there's obviously, probably updated numbers since then but it said that Microsoft 47,000 developers generate nearly 30,000 bugs a month, which is amazing that's coming across over 100 Azure DevOps and GitHub repositories. And then you had it you, you actually have a count here saying since 2001 Microsoft has collected 13 million work items and bugs which I just thinks amazing. So, do you want to speak to, sort of, the volume of inputs and, sort of, signals here in to building that model and maybe some of the challenges, and then a follow on question is, is this model, still active today, is this- is this work still ongoing, has it been incorporated into a product or another, another process?Nic Fillingham:Do you want to start with, with numbers or. Mayana Pereira:Yes, I think that from my data scientist point of view, having such large numbers is absolutely fantastic because it gives us a historical data set, very rich so we can understand how data has evolved over time. And also, if this- the security terminology has changed the law, or how long will this model last, in a sense. And it was interesting to see that you can have different tools, different products, different things coming up, but the security problems, at least for, I would say for the past six, seven years, when it comes to terminology, because what I was analyzing was the terminology of the security problems. My model was a natural language processing model. It was pretty consistent, so that was really interesting to see from that perspective we have. And by having so much data, you know, this amazing volume. It helped us to build better classifiers for sure. So this is my- my data scientist side saying, amazing. I love it so much data.Nic Fillingham:What's the status of this project on this model now.? Is it- is it still going? Has it been embedded into another- another product, uh, or process?Mayana Pereira:Yes, it's still active. It's still being used. So, right now, this product. This, not the product- the product, but the model is mainly used by the customer security interest team in [Sila 00:16:16], so they use the model in order to understand the security state of Microsoft products in general, and, uh, different products and looking at specific products as well, are using the model to get the- the bugs statistics and security bugs statistics for all these different products across Microsoft. And there are plans on integrating the- this specific model or a variation of the model into other security lifecycle pipelines, but this is a decision that is more on CST customer Security Trust side and I have, um, only followed it, but I don't have specific details for that right now. But, I have seen a lot of good interesting results coming out of that model, good insights and security engineers using the results of the model to identify potential problems, and fix those problems much faster.Natalia Godyla:So, taking a step back and just thinking about the journey that your team has gone on to get the model to the state that it's in today. Uh, in the blog you listed a number of questions to figure out what would be the right data to train the model. So the questions were, is there enough data? How good is the data? Are there data usage restrictions? And, can data be generated in a lab? Natalia Godyla:So can you talk us through how you answered these questions like, as a- as a data scientist you were thrilled that there was a ton of data out there, but what was enough data? How did you define how good the data was? Or, whether it was good enough.Mayana Pereira:Great. So, those were questions that I asked myself before even knowing what the project was about, and the answer to is there enough data? It seemed very clear from the beginning that, yes, we had enough data, but those were questions that I brought up on the blog, not only for myself but for anyone else that was interested in replicating those experiments in their company or maybe university or s- anywhere any- any data scientist that is interested to train your own model for classification, which questions should be asked? Once you start a project like this. So the, is there enough data for me? Was clear from the beginning, we had several products so we had a variety of data sources. I think that when you reach, the number of millions of samples of data. I think that speaks for itself. It is a high volume. So I felt, we did have enough data.Mayana Pereira:And, when it came to data quality. That was a more complex question. We had data in our hands, bugs. We wanted to be able to train a model that could different- differentiate from security bugs and non security bugs, you know. And, for that, Usually what we do with machine learning, is we have data, that data has labels, so you have data that represents security bugs, data that represents non security bugs. And then we use that to train the model. And those labels were not so great. So we needed to understand how the not so great labels was going to impact our model, you know, we're going to train a model with labels that were not so great. So Mayana Pereira:That was gonna happen. So that was one of the questions that we asked ourselves. And I did a study on that, on understanding what is the impact of these noisy labels and the training data set. And how is it gonna impact the classification results that we get once using this, this training data? So this was one of the questions that I asked and we, I did several experiments, adding noise. I did that myself, I, I added noise on purpose to the data set to see what was the limits of this noise resilience. You know, when you have noisy labels in training, we published it in a, in an academic conference in 2019, and we understood that it was okay to have noisy labels. So security bugs that were actually labeled as not security and not security bugs labeled as security. There was a limit to that.Mayana Pereira:We kinda understood the limitations of the model. And then we started investigating our own data to see, is our own data within those limits. If yes, then we can use this data confidentially to train our models. If no, then we'll have to have some processes for correcting labels and understanding these data set a little bit better. What can we use and what can we not use to train the models. So what we found out is that, we didn't have noisy labels in the data set. And we had to make a few corrections in our labels, but it was much less work because we understood exactly what needed to be done, and not correct every single data sample or every single label in a, an enormous data set of millions of entries. So that was something that really helped. Mayana Pereira:And then the other question, um, that we asked is, can we generate data in the lab? So we could sometimes force a specific security issue and generate some, some box that had that security description into titles. And why did we include that in the list of questions? Because a lot of bugs that we have in our database are generated by automated tools. So when you have a new tool being included in your ecosystem, how is your model going to recognize the bugs that are coming from this new tool? So does our, ma- automatically generated box. And we could wait for the tool to be used, and then after a while we gathered the data that the tool provided us and including a retraining set. But we can also do that in the lab ecosystem, generate data and then incorporate in a training set. So this is where this comes from.Nic Fillingham:I wanted to ask possibly a, a very rudimentary question, uh, especially to those that are, you know, very familiar with machine learning. When you have a data set, there's words, there is text in which you're trying to generate labels for that text. Does the text itself help the process of creating labels? So for example, if I've got a bug and the name of that bug is the word security is in the, the actual bug name. Am I jump-starting, am I, am I skipping some steps to be able to generate good labels for that data? Because I already have the word I'm looking for. Like I, I think my question here is, was it helpful to generate your labels because you were looking at text in the actual title of the bug and trying to ascertain whether something was security or not?Mayana Pereira:So the labels were never generated by us or by me, the data scientists. The labels were coming from the engineering systems where we collected the data from. So we were relying on what- whatever happened in the, in the engineering team, engineering group and relying that they did, uh, a good job of manually labeling the bugs as security or not security. But that's not always the case, and that doesn't mean that the, the engineers are not good or are bad, but sometimes they have their own ways of identifying it in their systems. And not necessarily, it is the same database that we had access to. So sometimes the data is completely unlabeled, the data that comes to us, and sometimes there are mistakes. Sometimes you have, um, specific engineer that doesn't have a lot of security background. The person sees a, a problem, describes the problem, but doesn't necessarily attribute the problem as a security problem. Well, that can happen as well.Mayana Pereira:So that is where the labels came from. The interesting thing about the terminology is that, out of the millions and millions of security bugs that I did review, like manually reviewed, because I kinda wanted to understand what was going on in the data. I would say that for sure, less than 1%, even less than that, had the word security in it. So it is a very specific terminology when you see that. So people tend to be very literal in what the problem is, but not what the problem will generate. In a sense of they will, they will use things like Cross-site Scripting or passwords in clear, but not necessarily, there's a security pr- there's a security problem. But just what the issue is, so it is more of getting them all to understand that security lingual and what is that vocabulary that constitutes security problems. So that's wh- that's why it is a little bit hard to generate a list of words and see if it matches. If a specific title matches to this list of words, then it's security.Mayana Pereira:It was a little bit hard to do that way. And sometimes you have in the title, a few different words that in a specific order, it is a security problem. In another order, it is not. And then, I don't have that example here with me, but I, I could see some of those examples in the data. For example, I think the Cross-site Scripting is a good example. Sometimes you have site and cross in another place in the title. It has nothing to do with Cross-site Scripting. Both those two words are there. The model can actually understand the order and how close they are in the bug title, and make the decision if it is security or not security. So that's why the model is quite easier to distinguish than if we had to use rules to do that.Natalia Godyla:I have literally so many questions. Nic Fillingham:[laughs].Natalia Godyla:I'm gonna start with, uh, how did you teach at the lingo? So what did you feed the model so that it started to pick up on different types of attacks like Cross-site Scripting?Mayana Pereira:Perfect. The training algorithm will do that for me. So basically what I need to guarantee is that we're using the correct technique to do that. So the technique will, the machine learning technique will basically identify from this data set. So I have a big data set of titles. And each title will have a label which is security or non-security related to it. Once we feed the training algorithm with all this text and their associated labels, the training algorithm will, will start understanding that, some words are associated with security, some words are associated with non-security. And then the algorithm will, itself will learn those patterns. And then we're gonna train this algorithm. So in the future, we'll just give the algorithm a new title and say, "Hey, you've learned all these different words, because I gave you this data set from the past. Now tell me if this new ti- if this new title that someone just came up with is a security problem or a, a non-security problem." And the algorithm will, based on all of these examples that it has seen before, will make a decision if it is security or non-security.Natalia Godyla:Awesome. That makes sense. So nothing was provided beforehand, it was all a process of leveraging the labels. Mayana Pereira:Yes.Natalia Godyla:Also then thinking about just the dataset that you received, you were working with how many different business groups to get this data? I mean, it, it must've been from several different product teams, right?Mayana Pereira:Right. So I had the huge advantage of having an amazing team that is a data center team that is just focused on doing that. So their business is go around the company, gather data and have everything harmonized in a database. So basically, what I had to do is work with this specific team that had already done this amazing job, going across the company, collecting data and doing this hard work of harvesting data and harmonizing data. And they had it with them. So it is a team that does that inside Microsoft. Collects the data, gets everything together. They have their databases updated several times a day, um, collecting Mayana Pereira:... Data from across the company, so it is a lot of work, yeah.Natalia Godyla:So do different teams treat bug reports differently, meaning is there any standardization that you had to do or anything that you wanted to implement within the bug reports in order to get better data?Mayana Pereira:Yes. Teams across the company will report bugs differently using different systems. Sometimes it's Azure DevOps, sometimes it can be GitHub. And as I mentioned, there is a, there was a lot of work done in the data harmonization side before I touched the data. So there was a lot of things done to get the data in, in shape. This was something that, fortunately, several amazing engineers did before I touched the data. Basically, what I had to do once I touched it, was I just applied the data as is to the model and the data was very well treated before I touched it. Nic Fillingham:Wow. So many questions. I did wanna ask about measuring the success of this technique. Were you able to apply a metric, a score to the ... And I'm, I, I don't even know what it would be. Perhaps it would be the time to address a security bug pre and post this work. So, did this measurably decrease the amount of time for prioritized security bugs to be, to be addressed?Mayana Pereira:Oh, definitely. Yes, it did. So not only it helped in that sense, but it helped in understanding how some teams were not identifying specific classes of bugs as security. Because we would see this inconsistency with the labels that they were including in their own databases. These labels would come to this big database that is harmonized and then we would apply the model on top of these data and see that specific teams were treating their, some data points as non-security and should have been security. Or sometimes they were treating as security, but not with the correct severity. So it would, should have been a critical bug and they were actually treating it as a moderate bug. So, that, I think, not only the, the timing issue was really important, but now you have a visibility of behavior and patterns across the company that the model gives us.Nic Fillingham:That's amazing. And so, so if I'm an engineer at Microsoft right now and I'm in my, my DevOps environment and I'm logging a bug and I use the words cross- cross scripting somewhere in the bug, what's the timing with which I get the feedback from your model that says, "Hey, your prioritization's wrong," or, "Hey, this has been classified incorrectly"? Are we at the point now where this model is actually sort of integrated into the DevOps cycle or is that still coming further down the, the, the path?Mayana Pereira:So you have, the main customer is Customer Security and Trust team inside Microsoft. They are the ones using it. But as soon as they start seeing problems in the data or specific patterns and problems in specific teams' datasets, they will go to that team and then have this, they have a campaign where they go to different teams and, and talk to them. And some teams, they do have access to the datasets after they are classified by our model. Right now, there's, they don't have the instant response, but that's, that's definitely coming.Nic Fillingham:So, Mayana, how is Customer Security and Trust, your organization, utilizing the outputs of this model when a, when a, when a bug gets flagged as being incorrectly classified, you know, is there a threshold, and then sort of what happens when you, when you get those flags?Mayana Pereira:So the engineering team, the security engineering team in Customer Security and Trust, they will use the model to understand the overall state of security of Microsoft products, you know, like the products across the company, our products, basically. And they will have an understanding of how fast those bugs are being mitigated. They'll have an understanding of the volume of bugs, and security bugs in this case, and they can follow this bugs in, in a, in a timely manner. You know, as soon as the bug comes to the CST system, they bug gets flagged as either security or not security. Once it's flagged as security, there, there is a second model that will classify the severity of the bug and the CST will track these bugs and understand how fast the teams are closing those bugs and how well they're dealing with the security bugs.Natalia Godyla:So as someone who works in the AI for Good group within Microsoft, what is your personal passion? What would you like to apply AI to if it, if it's not this project or, uh, maybe not a project within Microsoft, what is, what is something you want to tackle in your life?Mayana Pereira:Oh, love the question. I think my big passion right now is developing machine learning models for eradication of child sexual abuse medias in, across different platforms. So you can think about platform online from search engines to data sharing platforms, social media, anything that you can have the user uploading content. You can have problems in that area. And anything where you have using visualizing content. You want to protect that customer, that user, from that as well. But most importantly, protect the victims from those crimes and I think that has been, um, something that I have been dedicating s- some time now. I was fortunate to work with an NGO, um, recently in that se- in that area, in that specific area. Um, developed a few models for them. She would attacked those kind of medias. And these would be my AI for Good passion for now. The other thing that I am really passionate about is privacy, data privacy. I feel like we have so much data out there and there's so much of our information out there and I feel like the great things that we get from having data and having machine learning we should not, not have those great things because of privacy compromises. Mayana Pereira:So how can we guarantee that no one's gonna have their privacy compromised? And at the same time, we're gonna have all these amazing systems working. You know, how can we learn from data without learning from specific individuals or without learning anything private from a specific person, but still learn from a population, still learn from data. That is another big passion of mine that I have been fortunate enough to work in such kind of initiatives inside Microsoft. I absolutely love it. When, when I think about guaranteeing privacy of our customers or our partners or anyone, I think that is also a big thing for me. And that, that falls under the AI for Good umbrella as well since that there's so much, you know, personal information in some of these AI for Good projects. Natalia Godyla:Thank you, Mayana, for joining us on the show today.Nic Fillingham:We'd love to have you back especially, uh, folks, uh, on your team to talk more about some of those AI for Good projects. Just, finally, where can we go to follow your work? Do you have a blog, do you have Twitter, do you have LinkedIn, do you have GitHub? Where should, where should folks go to find you on the interwebs?Mayana Pereira:LinkedIn is where I usually post my latest works, and links, and interesting things that are happening in the security, safety, privacy world. I love to, you know, share on LinkedIn. So m- I'm Mayana Pereira on LinkedIn and if anyone finds me there, feel free to connect. I love to connect with people on LinkedIn and just chat and meet new people networking.Natalia Godyla:Awesome. Thank you. Mayana Pereira:Thank you. I had so much fun. It was such a huge pleasure to talk to you guys.Natalia Godyla:Well, we had a great time unlocking insights into security from research to artificial intelligence. Keep an eye out for our next episode. Nic Fillingham:And don't forget to Tweet us at MSFTSecurity or email us at firstname.lastname@example.org with topics you'd like to hear on a future episode. Until then, stay safe. Natalia Godyla:Stay secure.
Enterprise Resiliency: Breakfast of Champions
Prior to the pandemic,workdaysused to look a whole lot different.If you had a break,youcouldtake a walk to stretch your legs, shake the hands of your co-workers,orget some 1-on-1 face timewith the boss. Ahh... those were the days. Thatclose contact we once had is now somethingthat manyof usyearn for aswe’vehad to abruptlylift andshift fromliving in our office to working from our home.But communicating and socializing aren’t the only things that were easier back then. The walls of your office have expanded, and with them, the boundaries of your security protocols. Small in-office tasks like patching a server have now become multi-step processes that require remote management, remote updates, and remote administrative control. With that comes the prioritization of resilience and what it means for enterprises, customers, and security teams alike.That’swhere remote enterprise resiliency comes into play.Today on the pod,we explore the final chapter of the MDDR.Irfan Mirza,Director of Enterprise Continuity and Resilience atMicrosoft, wrapsupthe observationsfrom the report bygivinghostsNic FillinghamandNatalya Godylathe rundown on enterprise resiliencyand discusses how we canensure the highest levels of security while working from home.Irfan explains theZero trustmodel and how Microsoft is working to extend security benefits to your kitchen or home office, or...thatmake-shiftworkspacein your closet.In the second segment,Andrew Paverd,Senior Researcheron the Microsoft Security Response Center Teamandjackof all trades,stops by…andwe’renot convinced he’s fully human.He’shere to tell us about the many hats he wears,from safe systemsprogramming to leveraging AI to helpwith processes within the MSRC,andshares how he has to think like a hacker to prevent attacks. Spoiler alert:he’sa big follower of Murphy’s Law.In This Episode, You Will Learn:•How classical security models are being challenged•What the Zero Trust Model is and how it works•The three critical areas of resilience: extending the enterprise boundary, prioritizing resilient performance, and validating the resilience of our human infrastructure.•How hackers approach our systems and technologiesSome Questions We Ask:•How has security changed as a product of the pandemic?•Do we feel like we have secured the remote workforce?•What frameworks exist to put a metric around where an organization is in terms of its resiliency?•What is Control Flow Guard (CFG) and Control-Flow Integrity?•What’sthe next stage for the Rust programming language?Resources:Microsoft Digital Defense Report:https://www.microsoft.com/en-us/security/business/security-intelligence-reportIrfan’s LinkedInhttps://www.linkedin.com/in/irfanmirzausa/Andrew’s LinkedInhttps://www.linkedin.com/in/andrewpaverd/Nic’s LinkedInhttps://www.linkedin.com/in/nicfill/Natalia’s LinkedInhttps://www.linkedin.com/in/nataliagodyla/Microsoft Security Blog:https://www.microsoft.com/security/blog/Transcript(Full transcript can be found at https://aka.ms/SecurityUnlockedEp15)Nic Fillingham:Hello, and welcome to Security Unlocked, a new podcast from Microsoft, where we unlock insights from the latest in news and research from across Microsoft security, engineering and operations teams. I'm Nic Fillingham.Natalia Godyla:And I'm Natalia Godyla. In each episode, we'll discuss the latest stories from Microsoft Security, deep dive into the newest threat intel, research and data science. Nic Fillingham:And profile some of the fascinating people working on artificial intelligence in Microsoft Security. Natalia Godyla:And now let's unlock the pod. Hi Nic, I have big news.Nic Fillingham:Big news. Tell me a big news.Natalia Godyla:I got a cat. Last night at 8:00 PM, I got a cat. Nic Fillingham:Did it come via Amazon Prime drone? Natalia Godyla:No.Nic Fillingham:Just, that was a very specific time. Like 8:00 PM last night is not usually the time I would associate people getting cats. Tell me how you got your cat. Natalia Godyla:It was a lot more conventional. So I had an appointment at the shelter and found a picture of this cat with really nubby legs and immediately-Nic Fillingham:(laughs).Natalia Godyla:... fell in love obviously. And they actually responded to us and we went and saw the cat, got the cat. The cat is now ours. Nic Fillingham:That's awesome. Is the cat's name nubby. Natalia Godyla:It's not, but it is on the list of potential name changes. So right now the cat's name is tipper. We're definitely nervous about why the cat was named tipper. Nic Fillingham:(laughs).Natalia Godyla:We're hiding all of the glass things for right now. Nic Fillingham:How do we get to see the cat? Is there, will there be Instagram? Will there be Twitter photos? This is the most important question.Natalia Godyla:Wow. I haven't planned that yet.Nic Fillingham:You think about that and I'll, uh, I'll start announcing the first guest on this episode.Natalia Godyla:(laughs).Nic Fillingham:On today's episode, we speak with Irfan Mirza, who is wrapping up our coverage of the Microsoft Digital Defense Report with a conversation about enterprise resiliency. Now, this is really all of the chapters that are in the MDDR, the nation state actors, the increase in cyber crime sophistication, business email compromise that you've heard us talk about on the podcast, all gets sort of wrapped up in a nice little bow in this conversation where we talk about all right, what does it mean, what does it mean for customers? What does it mean for enterprises? What does it mean for security teams? And so we talk about enterprise resiliency. And we actually recorded this interview in late 2020, but here we are, you know, two months later and those findings are just as relevant, just as important. It's a great conversation. And after that, we speak with-Natalia Godyla:Andrew Paverd. So he is a senior researcher on the Microsoft Security Response Center team. And his work is well, well, he does a ton of things. I honestly don't know how he has time to pull all of this off. So he does everything from safe systems programming to leveraging AI, to help with processes within MSRC, the Microsoft Security Response Center. And I just recall one of the quotes that he said from our conversation was hackers don't respect your assumptions, or something to that effect, but it's such a succinct way of describing how hackers approach our systems and technology. So another really great conversation with a, a super intelligent researcher here at Microsoft.Nic Fillingham:On with the pod.Natalia Godyla:On with the pod. Today, we're joined by Irfan Mirza, Director of Enterprise Continuity and Resilience, and we'll be discussing the Microsoft Digital Defense Report and more specifically enterprise resilience. So thank you for being on the show today, Irfan.Irfan Mirza:Thanks so much glad to be here. And hope we have a, a great discussion about this. This is such an important topic now. Natalia Godyla:Yes, absolutely. And we have been incrementally working through the Microsoft Digital Defense Report, both Nic and I have read it and have had some fantastic conversations with experts. So really looking forward to hearing about the summation around resilience and how that theme is pulled together throughout the report. So let's start it off by just hearing a little bit more about yourself. So can you tell us about your day-to-day? What is your role at Microsoft? Irfan Mirza:Well, I lead the enterprise continuity and resilience team and we kind of provide governance overall at the enterprise. We orchestrate sort of all of the, the risk mitigations. We go and uncover what the gaps are, in our enterprise resilience story, we try to measure the effectiveness of what we're doing. We focus on preparedness, meaning that the company's ready and, you know, our critical processes and services are always on the ready. It's a broad space because it spans a very, very large global enterprise. And it's a very deep space because we have to be experts in so many areas. So it's a fun space by saying that.Natalia Godyla:Great. And it's really appropriate today then we're talking about the MDDR and enterprise resilience. So let's start at a high level. So can you talk a little bit about just how security has changed as a product of the pandemic? Why is resilience so important now? Irfan Mirza:Yeah, it's a great question. A lot of customers are asking that, our field is asking that question, people within the company are asking. Look, we've been 11 months under this pandemic. Maybe, you know, in some places like China, they've been going through it for a little bit longer than us, you know, a couple of months more. What we're finding after having sort of tried to stay resilient through this pandemic, uh, one obviously is on the human side, everyone's doing as much as we possibly can there. But the other part of it is on the enterprise side. What is it that we're having to think about as we think of security and as we think of enterprise resilience?Irfan Mirza:There are a couple of big things that I think I would note, one is that, look, when this pandemic hit us, our workforce lifted and shifted. I mean, by that, I mean that we, we, we got up out of our offices and we all left. I mean, we took our laptops and whatever we could home. And we started working remotely. It was a massive, massive lift and shift of personnel, right? We got dispersed. Everybody went to their own homes and most of us have not been back to the office. And it's not just at Microsoft, even, even a lot of our customers and our partners have not gone back to the office at all, right? So that, that's a prolong snow day, if you want to call it that.Irfan Mirza:The other thing that happened is our workload went with us. Wasn't just that, "Hey, you know, I'm taking a few days off, I'm going away or going on vacation and, and I'll be checking email periodically." No, I actually took our work with us and we started doing it remotely. So what that's done is it's created sort of a, a need to go back and look at what we thought was our corporate security boundary or perimeter.Irfan Mirza:You know, in the classical model, we used to think of the corporation and its facilities as the, the area that we had to go and secure. But now in this dispersed workforce model, we have to think about my kitchen as part of that corporate perimeter. And all of a sudden we have to ensure that, that my kitchen is as secure as the corporate network or as the facilities or the office that I was working from. That paradigm is completely different than anything we'd thought about before. Nic Fillingham:And so Irfan, in the MDDR, uh, this section, um, and if you've got the report open, you're playing along at home, I believe it's page 71. This enterprise resiliency is sort of a wrap-up of, of a lot of the observations that are in the MDDR report. It's not a new section. It's as you're getting towards the end of the report, you're looking for, okay, now what does this mean to me? I'm a CSO. I need to make new security policies, security decisions for my organization. This concept of enterprise resiliency is sort of a wrap up of everything that we've seen across cyber crime, across the nation state, et cetera, et cetera. Is that, is that accurate? Is that a good way to sort of read that section in the report? Irfan Mirza:Yeah. It is really the, the way to think of it, right.? It's sort of like a, the conclusion, so what, or why is this relevant to me and what can I do about it? When you think about the report and the way that it's structured, look, we, you know, the report goes into great detail about cyber crime as you called out Nic. And then it talks about nation state threats.Irfan Mirza:These are newer things to us. We've certainly seen them on the rise, actors that are well-trained, they're well-funded they play a long game, not necessarily a short game, they're looking, they're watching and they're waiting, they're waiting for us to make mistakes or to have gaps, they look for changes in tactics, either ours, uh, they themselves are quite agile, right? Irfan Mirza:So when you think about the environment in which we have to think about resilience, and we have to think about security, that environment itself has got new vectors or new threats that are, that are impacting it, right? In addition to that, our workforce has now dispersed, right? We're all over the, all over the globe. We see emerging threats that are, that are, non-classical like ransomware. We see attacks on supply chain. We continue to see malware and malware growing, right? Irfan Mirza:And, and so when you think about that, you have to think if I need to secure now my, my dispersed corporate assets and resources, my people, the workload, the data, the services and the processes that are all there, what are the, the sort of three big things I would need to think about? And so this report sort of encapsulates all, all of that. It gives the details of what, what's happening. And, and then page 71 is you say that resilience piece sort of comes back and says, "Look, your security boundaries extended. Like it or not, it is extended at this point. You've got to think beyond that on-site perimeter that we were thinking about before."Irfan Mirza:So we have to start thinking differently. And th- there's three critical areas that are sort of called out, acknowledging the security boundary has increased, thinking about resilience and performance, and then validating the resilience of our human infrastructure. This is like new ideas, but these are all becoming imperatives for us. We're having to do this now, whether we like it or not. Irfan Mirza:And so this report sort of gives our customers, and, and it's a reflection of what we're doing in the company. It's an open and honest conversation about how we propose to tackle these challenges that we're facing.Nic Fillingham:And so Irfan if we can move on to that critical area, number two, that prioritizing resilient performance. When I say the word performance and resilient performance, is that scoped down just to sort of IT infrastructure, or does that go all the way through to the humans, the actual people in the organization and, um, how they are performing their own tasks, their own jobs and the tasks that are part of their, their job and et cetera, et cetera? What's the, I guess what's the scope of that area too?Irfan Mirza:As we were thinking about resilience, as you know, shortly after we dispersed the workforce, we started thinking about, about what should be included in our classical understanding of resilience. But when you think about, about typical IT services and online services, and so on, a lot of that work is already being done with the life site reviews that we do and people are paying very close attention to service performance. We have SLAs, we have obligations, we have commitments that we've made that our services will be performing to a certain degree, but there are also business processes that are associated with these services very closely. Irfan Mirza:When you think about all of the processes that are involved and services that are involved from the time a customer thinks of buying Office, uh, 365, as an example, to the time that they provision their first mailbox, or they receive their first email, there are dozens of process, business processes. Irfan Mirza:Every single service in that chain could be working to 100% efficiency. And yet if the business processes, aren't there, for instance, to process the deal, to process the contract, to process, uh, the customer's payment or, uh, acknowledge receipt of the payment in order to be able to provision the service, all of these processes, all of a sudden have to, we have to make sure that they're also performing.Irfan Mirza:So when we start thinking about resilience, up to now, business continuity has focused on, are you ready? Are you prepared? Are your dependencies mapped? Have you, have you done a business impact analysis? Are you validating and testing your preparedness? You know, are you calling down your call tree for instance? But I think where we're going now with true enterprise resilience, especially in this sort of modern Irfan Mirza:... day, we're, we're looking at performance, right? What, what is your preparedness resulting in? So if you stop and you think about a child at school, they get homework. Well, the homework really, they bring it home. They do it. They take it back to the teacher. They get graded on it. That's wonderful. This means that the child is ready. But at some point in time, the class or the teacher is going to give them a test, and that test is going to be the measure of performance, right? Irfan Mirza:So we need to start thinking of resilience and continuity in the same way. We're prepared. We've done all our homework. Now let's go and see how many outages did you have? How critical were the outages? How long did they last? How many of them were repeat outages? How many of the repeat outages were for services that are supposed to have zero downtown, like services that are always supposed to on like your DNS service or your identity auth- authentication service, right? So, when you start thinking about, uh, resilience from that perspective, now you've got a new set of data that you have to go and capture, or data that you're capturing, you have to now have to have insights from it. You've got to be able to correlate your preparedness, meaning the homework that you've done with your actual performance, your outage and your, and your gap information. All right?Irfan Mirza:So that, that's what prioritizing resilient performance is all about. It's about taking realtime enterprise preparedness and mapping it to real time enterprise performance. That tells you if your preparedness is good enough or not, or what it is that you need to do. There's a loop here, a feedback loop that has to be closed. You can't just say that, well, you know, we've done all the exercises theoretically. We're good and we're ready to take on any sort of a crisis or, or, or disaster. Yeah, that's fine. Can we compare it to realtime what you're doing? Can we break glass and see what that looks like? Can we shut you down and or shut down parts of your operation as in the event of an earthquake for instance, or a hurricane wiping out, uh, access to a data center, right? Can we do those things and still be resilient when that happens? So this is what performance and resilience come together in that space.Natalia Godyla:So am I right in understanding that beyond, like you said, the theoretical where you think about the policies that you should have in place, and the frameworks that you should have in place, you have the analytics on, you know, the state of, the state of how performant your systems are to date. And then in addition, is there now the need for some sort of stress testing? Like actually figuring out whether an additional load on a system would cause it to break, to not be resilient? Is that now part of the new approach to resilience?Irfan Mirza:Yeah. There are, there are several, several things to do here, right? You absolutely said it. There's a stress test. Actually, this pandemic has, is already a stress test in and of itself, right? It's stressing us in a many ways. It's stressing, obviously the psyche and, and, you know, our whole psychology, and our ability to sustain in quarantine, in isolated, in insulated environments and so on. But it's also testing our ability to do the things that we just so, uh, so much took for granted, like the ability to patch a server that's sitting under my desk in the office whenever I needed to, right? That server now has to become a managed item that somebody can manage remotely, patch remotely, update remotely when needed, control administrative access and privileges remotely. But yes, for resilience, I think we need to now collect all of the data that we have been collecting or looking at and saying, can we start to create those correlations between our preparedness and between our real performance? Irfan Mirza:But there's another area that this dovetails into which is that of human resilience, right? We talked a little bit earlier about, you know, sort of the whole world enduring this hardship. We need to first and foremost look at our suppliers, subcontractors, people that we're critically dependent on. What is their resilience look like? That's another aspect that we have to go back. In the areas where we have large human resources or, or workforces that are working on our behalf, we need to make sure that they're staying resilient, right? Irfan Mirza:We talked on a lot about work/life balance before. Now I think the new buzzword in HR conference rooms is going to be work/life integration. It's completely integrated, and so we need to start thinking about the impact that would have. Are we tracking attrition of our employees, of certain demographics within the employees? Are we looking at disengagement? People just sort of, "Yeah, I'm working from home, but I'm not really being fully engaged." Right? The hallway conversations we used to have are no longer there. And we need to start thinking, are people divesting? Our resources, are they divesting in the workplace? Are they divesting in their, in their work or work/life commitment? These measures are all now having to be sort of like... Irfan Mirza:We used to rely on intuition, a look, a hallway gaze, look at the, the snap in somebody's walk as they walked away from you or out of your office. We don't have that anymore. Everybody's relatively stagnant. We're, we're, we're seated. We don't get to see body language that much. We don't get to read that. There's a whole new set of dynamics that are coming into play, and I think smart corporations and smart companies will start looking at this as a very important area to pay attention to.Nic Fillingham:How are we measuring that? What tools or sort of techniques, or, or sort of frameworks exist to actually put a metric around this stuff, and determine sort of where, where an organization is in terms of their level of resiliency?Irfan Mirza:This question is actually the whole reason why we brought this enterprise resilience sort of a conclusion to this fourth chapter, and, and, you know, the summation of this, of this report. Irfan Mirza:What we're doing now is we're saying, look. Things that used to be fundamentally within the domain of IT departments, or used to be fundamentally with, within the domain of live site, or used to be fundamentally in the domain of human resource departments are now all floating up to be corporate imperatives, to be enterprise imperatives. I think the thinking here is that we need to make sure that the data that we've been collecting about, as an example to answer your question, attrition, right? A certain demographic. Millennials, uh, changing jobs, leaving the company, just to pick an example more than anything else. This is no longer just data that the HR Department is interested in, or that recruiting would be interested in, or, or retention would be interested. This is data that's about to significantly impact the enterprise, and it needs to be brought into the enterprise purview.Irfan Mirza:Our classical and traditional models of looking at things in silos don't allow us to do that. What we're recommending is that we need to have a broader perspective and try to drive insights from this that do tell a more comprehensive story about our ent- enterprise resilience. That story needs to include the resilience of our services, our business processes, our suppliers, our human capital, our infrastructure, our extended security boundary, our data protection, uh, prevention of data loss, our intrusion detection. I mean, there's such a broad area that we have to cover. That's we're saying. And, and as we implement this new sort of zero trust model, I think the, the effectiveness of that model, how much progress we're making is becoming an enterprise priority, not just something that the IT department is going to go around on it's own.Nic Fillingham:Irfan, I wonder if I could put you on the spot, and were there any interesting bits of data that you saw in those first couple months of the shift to remote work where like, yeah, the number of unique devices on the Microsoft corporate network quadrupled in 48 hours. Like any, anything like that? I'd just wondering what, what little stats you may have in hand.Irfan Mirza:Yeah. The number of devices and sort of the flavors of devices, we've always anticipated that that's going to be varied. We're cognizant of that. Look, we have, you know, people have PCs. They have MACs. They have Linux machines, and, and they have service o- operating software. There's a lot of different flavors. And, and it's not just the device and the OS that matters, it's also what applications you're running. Some applications we can certify or trust, and others perhaps we can't, or that we still haven't gotten around to, to verifying, right? And all of these sit, and they all perform various functions including intruding and potentially exfiltrating data and Spyware and Malware and all of that. So when you think about that, we've always anticipated it. Irfan Mirza:But the one thing that, that we were extremely worried about, and I think a lot of our Enterprise customers were worried about, is the performance of the workforce. What we found very early on in, in the, in the lift and shift phase was that we needed to have a way of measuring is our, our built processes working? Are we checking in the same amount of code as we were before? And we noted a couple of interesting things. We looked at our, our VPN usage and said, what are those numbers look like? Are they going up and down?Irfan Mirza:And I think what we found is that initially, the effect was quite comparable to what we had, uh, when we experienced snow days. Schools are shut down. People don't go to work. They're slipping and sliding over here. We're just not prepared for snow weather in, in this state like some of the others. So what happened is, we saw that we were, we were sort of seeing the same level of productivity as snow days. We say that we had the same level of VPN usage as snow days, and we were worried because that, you know, when, when it snows, people usually take the day off, and then they go skiing. Irfan Mirza:So what happened? Well, after about a week things started picking back up. People got tired of sort of playing snow day and decided that, you know what? It's time to, to dig in, and human nature, I think, kicked in, the integrity of the workforce kicked in. And sure enough, productivity went up, VPN usage went up, our number of sessions, the duration of sessions. Meetings became shorter.Nic Fillingham:Can I tell you hallelujah? (laughs) Irfan Mirza:(laughs) Nic Fillingham:That's one of the, that's one of the great-Irfan Mirza:Absolutely.Nic Fillingham:... upsides, isn't it? To this, this new culture of remote work is that we're all meeting for, for less amount of time, which I think, I think is fantastic.Irfan Mirza:Look, you know, in times of crisis, whether it's a natural disaster, or a pandemic, or, or a manmade situation such as a war or a civil war, or whatever, I, I think what happens is the amount of resources that you are customarily used to having access to gets limited. The way in which you work shifts. It changes. And so the, the true test of resilience, I think, is when you are able to adapt to those changes gracefully without requiring significant new investment and you're able to still meet and fulfill your customer obligations, your operational expectations. That really is.Irfan Mirza:So what you learn in times of hardship are to sort of live, you know, more spartan-like. And that spartan-ism, if there's such a word as that, that's what allows you to stay resilient, to say what are the core things that I need in order to stay up and running? And those fundamental areas become the areas of great investment, the areas that you watch over more carefully, the areas that you measure the performance of, the areas that you look for patterns and, and trends in to try to predict what's happening, right?Irfan Mirza:So that is something that carries over from experiences of being in the front lines of a, uh, a war or, or from being, uh, you know, in the midst of a hurricane trying to recover a data center, or an earthquake, or any other, uh, type of power outage, right? These are all the sort of key scenarios that we would be going to look at. And that's one of the things they all have in common. It's really that you don't have the resources or access to the resources that you thought you did, and now you've got to be able to do some things slightly differently.Natalia Godyla:Thank you for joining us on the podcast today. It's been great to get your perspective on enterprise resilience. Really fascinating stuff. So, thank you.Irfan Mirza:Thank you, Natalia. And, and thank you, Nick. It's been a great conversation. As I look back at this discussion that we had, I feel even, even stronger now that the recommendations that we're making, and the guidance that we're giving our customers and sharing our experiences, becomes really, really important. I think this is something that we're learning as we're going along. We're learning on the journey. We're uncovering things that we didn't know. We're looking at data in a different way. We're, we're trying to figure out how do we sustain ourselves, Nic Fillingham:... not just through this pandemic, but also beyond that. And I think the, whatever it is that we're learning, it becomes really important to share. And for our customers and people who are listening to this podcast to share back with us what they've learned, I think that becomes incredibly important because as much as we like to tell people what we're doing, we also want to know what, what people are doing. And so learning that I think will be a great, great experience for us to have as well. So thank you so much for enabling this conversation. Natalia Godyla:And now let's meet an expert from the Microsoft security team to learn more about the diverse backgrounds and experiences of the humans creating AI and tech at Microsoft. Welcome back to another episode of Security Unlocked. We are sitting with Andrew Paverd today, senior researcher at Microsoft. Welcome to the show, Andrew. Andrew Paverd:Thanks very much. And thanks for having me. Natalia Godyla:Oh, we're really excited to chat with you today. So I'm just doing a little research on your background and looks like you've had a really varied experience in terms of security domains consulting for mobile device security. I saw some research on system security. And it looks like now you're focused on confidential computing at Microsoft. So let's start there. Can you talk a little bit about what a day in the life of Andrew looks like at Microsoft? Andrew Paverd:Absolutely. I think I have one of the most fascinating roles at Microsoft. On a day-to-day basis, I'm a researcher in the confidential computing group at the Microsoft Research Lab in Cambridge, but I also work very closely with the Microsoft Security Response Center, the MSRC. And so these are the folks who, who are dealing with the frontline incidents and responding to reported vulnerabilities at Microsoft. But I work more on the research side of things. So how do we bridge the gap between research and what's really happening on the, on the front lines? And so I, I think my position is quite unique. It's, it's hard to describe in any other way than that, other than to say, I work on research problems that are relevant to Microsoft security. Natalia Godyla:And what are some of those research problems that you're focused on? Andrew Paverd:Oh, so it's actually been a really interesting journey since I joined Microsoft two years ago now. My background, as you mentioned, was actually more in systems security. So I had, I previously worked with technologies like trusted execution environments, but since joining Microsoft, I've worked on two really, really interesting projects. The, the first has been around what we call safe systems programming languages. Andrew Paverd:So to give a bit more detail about it in the security response center, we've looked at the different vulnerabilities that Microsoft has, has patched and addressed over the years and seen some really interesting statistics that something like 70% of those vulnerabilities for the pa- past decade have been caused by a class of vulnerability called memory corruption. And so the, the question around this is how do we try and solve the root cause of problem? How do we address, uh, memory corruption bugs in a durable way? Andrew Paverd:And so people have been looking at both within Microsoft and more broadly at how we could do this by transitioning to a, a different programming paradigm, a more secure programming language, perhaps. So if you think of a lot of software being written in C and C++ this is potentially a, a cause of, of memory corruption bugs. So we were looking at what can we do about changing to safer programming languages for, for systems software. So you might've heard about new languages that have emerged like the Rust programming language. Part of this project was investigating how far we can go with languages like Rust and, and what do we need to do to enable the use of Rust at Microsoft.Natalia Godyla:And what was your role with Rust? Is this just the language that you had determined was a safe buyable option, or were you part of potentially producing that language or evolving it to a place that could be safer? Andrew Paverd:That's an excellent question. So in, in fact it, it was a bit of both first determining is this a suitable language? Trying to define the evaluation criteria of how we would determine that. But then also once we'd found Rust to be a language that we decided we could potentially run with, there was an element of what do we need to do to bring this up to, let's say to be usable within Microsoft. And actually I, I did quite a bit of work on, on this. We realized that, uh, some Microsoft security technologies that are available in our Microsoft compilers weren't yet available in the Rust compiler. One in particular is, is called control flow guard. It's a Windows security technology and this wasn't available in Rust. Andrew Paverd:And so the team I, I work with looked at this and said, okay, we'd like to have this implemented, but nobody was available to implement it at the time. So I said, all right, let me do a prototype implementation and, uh, contributed this to the open source project. And in the end, I ended up following through with that. And so I've, I've been essentially maintaining the, the Microsoft control flow guide implementation for the, the Rust compiler. So really an example of Microsoft contributing to this open source language that, that we hope to be using further.Nic Fillingham:Andrew, could you speak a little bit more to control flow guard and control flow integrity? What is that? I know a little bit about it, but I'd love to, for our audience to sort of like expand upon that idea. Andrew Paverd:Absolutely. So this is actually an, an example of a technology that goes back to a collaboration between the MSRC, the, the security response center and, and Microsoft Research. This technology control flow guard is really intended to enforce a property that we call control flow integrity. And that simply means that if you think of a program, the control flow of a program jumps through two different functions. And ideally what you want in a well-behaved program is that the control always follows a well-defined paths. Andrew Paverd:So for example, you start executing a function at the beginning of the function, rather than halfway through. If for example, you could start executing a function halfway through this leads to all kinds of possible attacks. And so what control flow guard does is it checks whenever your, your program's going to do a bronch, whenever it's going to jump to a different place in the code, it checks that that jump is a valid call target, that you're actually jumping to the correct place. And this is not the attacker trying to compromise your program and launch one of many different types of attacks.Nic Fillingham:And so how do you do that? What's the process by which you do en- ensure that control flow?Andrew Paverd:Oh, this is really interesting. So this is a technology that's supported by Windows, at the moment it's only available on, on Microsoft Windows. And it works in conjunction between both the compiler and the operating system. So the compiler, when you compile your program gives you a list of the valid code targets. It says, "All right, here are the places in the program where you should be allowed to jump to." And then as the program gets loaded, the, the operating system loads, this list into a highly optimized form so that when the program is running it can do this check really, really quickly to say, is this jump that I'm about to do actually allowed? And so it's this combination of the Windows operating system, plus the compiler instrumentation that, that really make this possible. Andrew Paverd:Now this is quite widely used in Windows. Um, we want in fact as much Microsoft software as possible to use this. And so it's really critical that we enable it in any sort of programming language that we want to use. Nic Fillingham:How do you protect that list though? So now you, isn't that now a target for potential attackers?Andrew Paverd:Absolutely. Yeah. And, and it becomes a bit of a race to, to-Nic Fillingham:Cat and mouse.Andrew Paverd:... protect different-Natalia Godyla:(laughs).Andrew Paverd:A bit of, a bit of a cat, cat and mouse game. But at least the nice thing is because list is in one place, we can protect that area of memory to a much greater degree than, than the rest of the program. Natalia Godyla:So just taking a step back, can you talk a little bit about your path to security? What roles have you had? What brought you to security? What's informing your role today? Andrew Paverd:It's an interesting story of how I ended up working in security. It was when I was applying for PhD programs, I had written a PhD research proposal about a topic I thought was very interesting at the time on mobile cloud computing. And I still think that's a hugely interesting topic. And what happened was I sent this research proposal to an academic at the University of Oxford, where I, I was looking to study, and I didn't hear anything for, for a while. Andrew Paverd:And then, a fe- a few days later I got an email back from a completely different academic saying, "This is a very interesting topic. I have a project that's quite similar, but looking at this from a security perspective, would you be interested in doing a PhD in security on, on this topic?" And, so this was my very mind-blowing experience for me. I hadn't considered security in that way before, but I, I took a course on security and found that this was something I was, I was really interested in and ended up accepting the, the PhD offer and did a PhD in system security. And that's really how I got into security. And as they say, the rest is history.Natalia Godyla:Is there particular part of security, particular domain within security that is most near and dear to your heart?Andrew Paverd:Oh, that's a good question.Natalia Godyla:(laughs).Andrew Paverd:I think, I, I think for me, security it- itself is such a broad field that we need to ensure that we have security at, at all levels of the stack, at all, places within the chain, in that it's really going to be the weakest link that an attacker will, will go for. And so I've actually changed field perhaps three times so far. This is what keeps it interesting. My PhD work was around trusted computing. And then as I said, I, since joining Microsoft, I've been largely working in both safe systems programming languages and more recently AI and security. And so I think that's what makes security interesting. The, the fact that it's never the same thing two days in a row.Natalia Godyla:I think you hit on the secret phrase for this show. So AI and security. Can you talk a little bit about what you've been doing in AI and security within Microsoft? Andrew Paverd:Certainly. So about a year ago, as many people in the industry realized that AI is being very widely used and is having great results in so many different products and services, but that there is a risk that AI algorithms and systems themselves may be attacked. For example, I, I know you had some, some guests on your podcast previously, including Ram Shankar Siva Kumar who discussed the Adversarial ML Threat Matrix. And this is primarily the area that I've been working in for the past year. Looking at how AI systems can be, can be attacked from a security or a privacy perspective in collaboration with researchers, from MSR, Cambridge. Natalia Godyla:What are you most passionate about? What's next for a couple of these projects? Like with Rust, is there a desire to make that ubiquitously beyond Microsoft? What's the next stage? Andrew Paverd:Ab- absolutely. Natalia Godyla:Lots of questions. (laughs).Andrew Paverd:Yeah. There's a lot of interest in this. So, um, personally, I'm, I'm not working on the SSPL project myself, or I'm, I'm not working on the safe systems programming languages project myself any further, but I know that there's a lot of interest within Microsoft. And so hopefully we'll see some exciting things e- emerging in that space. But I think my focus is really going to be more on the, both the security of AI, and now we're also exploring different areas where we can use AI for security. This is in collaboration, more with the security response center. So looking into different ways that we can automate different processes and use AI for different types of, of analysis. So certainly a lot more to, to come in that space.Nic Fillingham:I wanted to come back to Rust for, for a second there, Andrew. So you talked about how the Rust programming language was specifically designed for, correct me on taxonomy, memory integrity. Is that correct?Andrew Paverd:For, for memory safety, yeah. Nic Fillingham:Memory safety. Got it. What's happening on sort of Nic Fillingham:... and sort of the, the flip side of that coin in terms of instead of having to choose a programming language that has memory safety as sort of a core tenet. What's happening with the operating system to ensure that languages that maybe don't have memory safety sort of front and center can be safer to use, and aren't threats or risks to memory integrity are, are sort of mitigated. So what's happening on the operating system side, is that what Control Flow Guard is designed to do? Or are there other things happening to ensure that memory safety is, is not just the responsibility of the programming language?Andrew Paverd:Oh, it's, that's an excellent question. So Control Flow Guard certainly helps. It helps to mitigate exploits once there's been an, an initial memory safety violation. But I think that there's a lot of interesting work going on both in the product space, and also in the research space about how do we minimize the amount of software that, that we have to trust. If you accept that software is going to have to bugs, it's going to have vulnerabilities. What we'd like to do, is we'd like to trust as little software as possible.Andrew Paverd:And so there's a really interesting effort which is now available in, in Azure under the, the heading of Confidential Computing. Which is this idea that you want to run your security sensitive workloads in a hardware enforced trusted execution environment. So you actually want to take the operating system completely out of what we call the trusted computing base. So that even if there are vulnerabilities in, in the OS, they don't affect your security sensitive workloads. So I think that there's this, this great trend towards confidential computing around compartmentalizing and segmenting the software systems that we're going to be running.Andrew Paverd:So removing the operating system from the trusted computing. And, and indeed taking this further, there's already something available in Azure, you can look up Azure Confidential Computing. But there's a lot of research coming in from the, the academic side of things about new technologies and new ways of, of enforcing separation and compartmentalization. And so I think it's part of this full story of, of security that we'll need memory safe programming languages. We'll need compartmentalization techniques, some of which, uh, rely on new hardware features. And we need to put all of this together to really build a, a secure ecosystem.Nic Fillingham:I only heard of Confidential Computing recently. I'm sure it's not a new concept. But for me as a sort of a productized thing, I only sort of recently stumbled upon it. I did not realize that there was this gap, there was this delta in terms of data being encrypted at rest, data being encrypted in transit. But then while the data itself was being processed or transformed, that that was a, was a gap. Is that the core idea around Confidential Computing to ensure that at no stage the data is not encrypted? Is, is that sort of what it is?Andrew Paverd:Absolutely. And it's one of the key pieces. So we call that isolated execution in the sense that the data is running in a, a trusted environment where only the code within that environment can access that data. So if you think about the hypervisor and the operation system, all of those can be outside of the trusted environment. We don't need to trust those for the correct computation of, of that data. And as soon as that data leaves this trusted environment, for example if it's written out of the CPU into the DRAM, then it gets automatically encrypted.Andrew Paverd:And so we have that really, really strong guarantee that only our code is gonna be touching our data. And the second part of this, and this is the really important part, is a, a protocol called remote attestation where this trusted environment can prove to a remote party, for example the, the customer, exactly what code is going to be running over that data. So you have a, a very high degree of assurance of, "This is exactly the code that's gonna be running over my data. And no other code will, will have access to it."Andrew Paverd:And the incredibly interesting thing is then, what can we build with these trusted execution environment? What can we build with Confidential Computing? And to bring this back to the, the keyword of your podcast, we're very much looking at confidential machine learning. How do we run machine learning and AI workloads within these trusted execution environments? And, and that unlocks a whole lot of new potential.Nic Fillingham:Andrew, do you have any advice for people that are m- maybe still studying or thinking about studying? Uh, I see so you, your initial degree was in, not in computer engineering, was it?Andrew Paverd:No. I, I actually did electrical engineering. And then electrical and computer engineering. And by the time I did a PhD, they put me in a computer science department, even though-Nic Fillingham:(laughs).Andrew Paverd:... I was doing software engineering.Nic Fillingham:Yeah. I, so I wonder if folks out there that, that don't have a software or a computer engineering degree, maybe they have a, a different engineering focus or a mathematics focus. Any advice on when and how to consider computer engineering, or sort of the computing field?Andrew Paverd:Yeah. Uh, absolutely. Uh, I think, eh, in particular if we're talking about security, I'd say have a look at security. It's often said that people who come with the best security mindsets haven't necessarily gone through the traditional programs. Uh, of course it's fantastic if you can do a, a computer science degree. But if you're coming at this from another area, another, another aspect, you bring a unique perspective to the world of cyber security. And so I would say, have a look at security. See if it's something that, that interests you. You, you might find like I did that it's a completely fascinating topic.Andrew Paverd:And the from there, it would just be a question of seeing where your skills and expertise could best fit in to the broad picture of security. We desperately need people working in this field from all different disciplines, bringing a diversity of thought to the field. And so I, I'd highly encourage people to have a look at this.Natalia Godyla:And you made a, quite a hard turn into security through the PhD suggestion. It, like you said, it was one course and then you were off. So, uh, what do you think from your background prepared you to make that kind of transition? And maybe there's something there that could inform others along the way.Andrew Paverd:I think, yes, it, it's a question of looking at, uh, of understanding the system in as much detail as you possibly can. And then trying to think like, like an attacker. Trying to think about what could go wrong in this system? And as we know, attackers won't respect our assumptions. They will use a system in a different way in which it was designed. And that ability to, to think out of the box, which, which comes from understanding how the system works. And then really just a, a curiosity about security. They call it the security mindset, of perhaps being a little bit cautious and cynical. To say-Natalia Godyla:(laughs).Andrew Paverd:... "Well, this can go wrong, so it probably will go wrong." But I think that's, that's the best way into it.Natalia Godyla:Must be a strong follower of Murphy's Law.Andrew Paverd:Oh, yes.Natalia Godyla:(laughs).Nic Fillingham:What are you watching? What are you binging? What are you reading? Either of those questions, or anything along in that flavor.Andrew Paverd:I'll, I'll have to admit, I'm a, I'm a big fan of Star Trek. So I've been watching the new Star Trek Discovery series on, on Netflix. That's, that's great fun. And I've recently been reading a, a really in- interesting book called Atomic Habits. About how we can make some small changes, and, uh, how these can, can help us to build larger habits and, and propagate through.Nic Fillingham:That's fascinating. So that's as in looking at trying to learn from how atoms and atomic models work, and seeing if we can apply that to like human behavior?Andrew Paverd:Uh, no. It's just the-Nic Fillingham:Oh, (laughs).Andrew Paverd:... title of the book.Natalia Godyla:(laughs).Nic Fillingham:You, you had me there. Natalia Godyla:Gotcha, Nick.Nic Fillingham:I was like, "Wow-"Natalia Godyla:(laughs).Nic Fillingham:" ... that sounds fascinating." Like, "Nope, nope. Just marketing." Marketing for the win. Have you always been Star Trek? Are you, if, if you had to choose team Star Trek or team Star Wars, or, or another? You, it would be Star Trek?Andrew Paverd:I think so. Yeah.Nic Fillingham:Yeah, me too. I'm, I'm team Star Trek. Which m- may lose us a lot of subscribers, including Natalia.Andrew Paverd:(laughs).Nic Fillingham:Natalia has her hands over her mouth here. And she's, "Oh my gosh." Favorite Star Trek show or-Andrew Paverd:I, I have to say, it, it would've been the first one I watched, Deep Space Nine.Nic Fillingham:I love Deep Space Nine. I whispered that. Maybe that-Natalia Godyla:(laughs).Nic Fillingham:... it's Deep Space Nine's great. Yep. All right, cool. All right, Andrew, you're allowed back on the podcast. That's good.Andrew Paverd:Thanks.Natalia Godyla:You're allowed back, but I-Nic Fillingham:(laughs).Natalia Godyla:... (laughs).Andrew Paverd:(laughs).Nic Fillingham:Sort of before we close, Andrew, is there anything you'd like to plug? I know you have a, you have a blog. I know you work on a lot of other sorta projects and groups. Anything you'd like to, uh, plug to the listeners?Andrew Paverd:Absolutely, yeah. Um, we are actually hiring. Eh, well, the team I work with in Cambridge is, is hiring. So if you're interested in privacy preserving machine learning, please do have a look at the website, careers.microsoft.com. And submit an application to, to join our team.Natalia Godyla:That sounds fascinating. Thank you.Nic Fillingham:And can we follow along on your journey and all the great things you're working at, at your website?Andrew Paverd:Eh, absolutely, yeah. And if you follow along the, the Twitter feeds of both Microsoft Research Cambridge, and the Microsoft Security Response Center, we'll, we'll make sure to tweet about any of the, the new work that's coming out.Nic Fillingham:That's great. Well, Andrew Paverd, thank you so much for joining us on the Security Unlocked Podcast. We'd love to have you come back and talk about some of the projects you're working on in a deep-dive section on a future episode.Andrew Paverd:Thanks very much for having me.Natalia Godyla:Well, we had a great time unlocking insights into security, from research to artificial intelligence. Keep an eye out for our next episode.Nic Fillingham:And don't forget to tweet @MSFTSecurity. Or email us at email@example.com with topics you'd like to hear on a future episode. Until then, stay safe.Natalia Godyla:Stay secure.
Pluton: The New Bedrock for Device Security
Close your eyes, and imagine a world where booting up your computer wasn’t a susceptibility point for attacks. Imagine a Root of Trust that’s integrated into the CPU. Imagine all of your devices being protected against advanced attacks. Now, what if I told you there’s a cutting-edge processor that’s battle-tested for hardware penetrations, easy to update, and protects credentials, encryption keys, and personal data all at once? What if I told you it was already here, and your systems might already be using it?! Open your eyes, and get ready to be amazed! It’s Pluton, baby! Peter Waxman, Group Program Manager at Microsoft, joins hosts Nic Fillingham and Natalia Godyla in a tell-all about Pluton. Trust us, Pluton is sure to knock your SOCs off (that’s System on a Chip)!Now that your eyes have been opened to a more secure system, we’d like to ask you to keep the volume down, because you’ve just entered the Library of Threats. While it may sound like inspiration for the next installment of National Treasure, you won’t find Nicolas Cage in this library (at least you shouldn’t). However, you will find Madeline Carmichael, MSTIC’s Threat Intel Librarian, whose movie-worthy title is just as impressive as it sounds. To be honest though, you might not find anyone in the library, as it bears more resemblance to Professor X’s Cerebro than it does your local hardcover sanctuary.In This Episode, You Will Learn: •What the Pluton Security Processor is and how it was created•The architecture of the Pluton Security Processor•What challenges were faced while bringing the Pluton Security Processor to life•The Root of Trust today vs. The Future with Pluton•The naming systems for threat actors, from periodic elements to volcanoesSome Questions We Ask:•What differentiates the Pluton Security Processor from previous methodologies?•Why is the Pluton Processor better than what we have used in the past? •What challenges lie ahead with the next steps around Pluton?•What has changed since Pluton was in Xbox to where it is now?•What tools and platforms does a Threat Intel Librarian utilize?Resources:Microsoft Pluton Announcement:https://www.microsoft.com/security/blog/2020/11/17/meet-the-microsoft-pluton-processor-the-security-chip-designed-for-the-future-of-windows-pcs/Peter’s LinkedInhttps://www.linkedin.com/in/peter-waxman-ba5555/Madeline’s LinkedInhttps://www.linkedin.com/in/madeline-carmichael-081540b2/Nic’s LinkedInhttps://www.linkedin.com/in/nicfill/Natalia’s LinkedInhttps://www.linkedin.com/in/nataliagodyla/Microsoft Security Blog:https://www.microsoft.com/security/blog/Transcript(Fulltranscriptcan be found athttps://aka.ms/SecurityUnlockedEp14)Nic Fillingham:Hello, and welcome to Security Unlocked, a new podcast from Microsoft where we unlock insights from the latest in news and research from across Microsoft's Security Engineering and Operations teams. I'm Nic Fillingham.Natalia Godyla:And I'm Natalia Godyla. In each episode, we'll discuss the latest stories from Microsoft Security, deep dive into the newest threat intel, research, and data science.Nic Fillingham:And profile some of the fascinating people working on artificial intelligence in Microsoft Security. Natalia Godyla:And now, let's unlock the pod. Hey, Nic, how's it going?Nic Fillingham:Hey, Natalia. I am good, I am excited. I've been excited for every episode, but I think this is the episode where we may be able to spin off into a major, major motion picture. I'm quite convinced that one of our guests, their story is compelling enough that a Nicolas Cage-style act, maybe even Nicolas Cage would be willing to turn this into a film.Natalia Godyla:Let's line up the two guests, and l- let our audience figure out which one is the next National Treasure.Nic Fillingham:First up, we have Peter Waxman, who's gonna talk to us about the Microsoft Pluton announcement from back in November of last year. This is a continuation from a conversation we had with Nazmus Sakib a few episodes ago where we talked about ensuring integrity at the firmware layer up and secured-core PCs, and now we're sorta continuing that conversation, deep-diving into what is the Pluton. Our Microsoft Pluton technology was announced in November. Fascinating conversation. And then we speak with?Natalia Godyla:Madeline Carmichael, who has a background in library science and worked in physical libraries, and now she is a threat intel librarian. So her title is MSTIC Librarian, she helps to catalog the different threat actor groups that we monitor. So it's a callback to a conversation that we had with Jeremy Dallman about tacking nation-state actors. Nic Fillingham:Yeah. So Madeline's job, apart from, uh, you know, one of the things that she does is she helps name these nation-state actors. And so we, Jeremy walked us through the, uh, periodic table of elements that is used to actually name who these nation-state groups are. So I just think that's fa- that's fascinating to go from a physical library and sort of library sciences into the deepest, darkest recesses of nation-state threats and nation-state actors. I- I think that is a Nicolas Cage vehicle waiting to happen, and I can't wait to go back into the cinema and we can sit down with our popcorn and we can watch National Treasure 7: MSTIC Librarian. This time, it's elementary? (laughs)Natalia Godyla:(laughs).Nic Fillingham:National Treasure 7: Threat Catalog- Catalog. Don't judge a threat actor by its name. No. Natalia Godyla:I see it. I know why you picked Madeline's. I feel like we probably need a little bit more help on that tag line, so if anyone wants to give us some feedback, firstname.lastname@example.org, let us know. We are actively working on this script. Nic Fillingham:On with the pod?Natalia Godyla:On with the pod.Nic Fillingham:Welcome to Security Unlocked. Peter Waxman, thanks for joining us.Peter Waxman:Thank you, great to be here.Nic Fillingham:So this is gonna be the second of three deep dives we do on the sort of very broad topic of ensuring the integrity and the security of physical devices through things like protecting firmware, and obviously we'll expand upon that in this conversation here. Peter, you're joining us today to talk about the recently-announced Microsoft Pluton processor, so that, this is gonna be great. We're excited to chat with you. Nic Fillingham:Um, before we get into that, we'd love to ask. Tell us a little bit ab- about yourself. What's your job? What team are you in? What's the mission of the team? What's your day-to-day look like?Peter Waxman:Awesome, awesome. At Microsoft, I work in, uh, the Enterprise Security team, part of the so-called Azure application platform. Basically what we do broadly is build all the operating system platform and everything underneath. You can think about it as Windows, the operating system, you know, Windows that powers Azure. Even what powers Xbox and some of our other devices. Peter Waxman:And in particular, what I do is I focus on the operating system security and the low-level platform security that that operating system depends upon. Think about the hardware and firmware that our partners produce, to go make sure that that experience is completely secure. It protects our customers' data, it protects their identities, it makes sure that their application run with integrity and that they don't get hacked. And if they do get hacked, that we have an easy way to update and renew the system to get them in a good state again.Natalia Godyla:And so, we recently announced on November 17th the Pluton processor. Can you tell us about that? What- what is Pluton?Peter Waxman:Yes. Yeah. This is a big, exciting thing. It's something that we've been working on for quite some time. What Pluton essentially is is it's basically a security chip that lives inside of a larger chip. We call it basically the Pluton security processor, and this is like the heart of the security system in a PC or in a device. Peter Waxman:If you think about the security of a device, when you push power on that, when you push power on your laptop or computer, the, and the CPU comes up, one of the most important things is that the way that that system boots up and starts happens in a secure fashion. Because if it doesn't happen in a secure fashion, then it's very easy for bad actors to basically get in underneath and to root the system and cause all sorts of problems. Peter Waxman:So what Pluton is is basically this root of trust, the security processor that we, Microsoft, are integrating, and which is what we announced along with our major silicon partners in AMD, Intel, and Qualcomm, into the fabric of their products, in to the fabric of their chips. And so, by having that tight integration, it ensures that basically those chips and those products come up and boot in a secure fashion, and that we can then run Windows on this trusted foundation where we know the system is secure and basically we have, uh, much stronger footing with Pluton in the system going forward.Natalia Godyla:So what differentiates the Pluton security processor from previous methodologies? What were you using in the past? Why is this better?Peter Waxman:So traditionally in, uh, most PCs, the root of trust today is actually a separate chip. You know, very typically a discrete TPM. And that is something that lives on the motherboard as a separate unit, but it basically communicates over an insecure bus to the CPU. And the problem with that is that it just, it lends itself to all sorts of attacks. There's been a variety of ones that have been published. One of the common things that it's been known and in a published attack, basically there's one called TPM Genie. That bus, because it's insecure, even though the TPM chip itself may be highly secure, the system overall is not. Peter Waxman:And so, attackers can go in with very inexpensive hardware, a logic analyzer, $50 worth of equipment, and go and basically intercept and alter the communications between the CPU and the TPM. And end up basically, you end up with an insecure system as a result. You could actually be booting malware in the firmware. You could basically be booting with exploits all through the boot chain, and Windows wouldn't know about it. The customer's data and experience would be compromised as a result. And so, by moving the root of trust into the CPU die, we're basically taking a whole class of attacks out of the scope, resulting in a system that is more secure overall in terms of how it comes up and the foundation. Peter Waxman:It's also something, though, that one of the challenges that exists with the existing roots of trust is that they're very hard to update. Like other components in the system, right? They have their own firmware, the firmware can have vulnerabilities, and in fact, there have been notable vulnerabilities that have existed in TPM firmware. And when we look and see across the inventory of Windows 10 systems out there, there's actually a very large number of TPMs that are running out-of-date, unpatched firmware.Peter Waxman:Uh, as a result of having Pluton integrated into the CPU and having tighter control of it from Windows, we can leverage the decades of experience and billion-plus endpoint reliability that we have in Windows Update to offer customers the ability to much more easily and automatically update firmware on the root of trust of the system. If there's ever any security issue that we find, we can very quickly get an update out. We can also, importantly, update with new capability, so as new scenarios come online, where customers want to take advantage or applications want to take advantage of this root of trust, we have the ability to add that capability to Pluton in a easy, quick ability through Windows Update. Natalia Godyla:So what challenges did you have with bringing this security processor to life, with bringing it to PCs, in particular with the partners and OEMs that we were bringing it into the market with? And- and what challenges still lay ahead with the next steps that you have around Pluton?Peter Waxman:Yeah, so there's plenty. I mean, there's a- there's a tremendous, uh, satisfaction that we have and, you know, came to the point where we have been able to announce with our major silicon partners that we're bringing this to market. But I'm humbled by it, but at the same point we still have a ways to go before this comes to market. And to continue really in seeing to the vision, which is really to enable Pluton everywhere and to be ubiquitous even beyond PCs and- and gaming consoles and- and IoT devices.Peter Waxman:So- so a lot more work to do. Working with the ecosystem is something that takes a lot of time. It's been a tremendous effort, it's been several years in the making just to get to this point where, you know, we're far enough along with our partners that we can announce it, that we feel confident around landing these products. Both with the silicon partners that we announced, as well as with a range of PC OEMs that have been with us on this journey over the last year.Peter Waxman:We're at a point, though, because, you know, we're basically taking Microsoft technology and integrating it with our- our silicon partners, it's our silicon partners' products that are the ones that will bring this to market on OEM devices. They are not yet ready to announce sort of their particular timeframe intercepts, so unfortunately I won't speak to exactly when products land. But, you know, they are coming, folks should stay tuned. Peter Waxman:And when you think about Intel or AMD or Qualcomm chip, kind of the rule of thumb is it takes three years to go from the time that you start the design to the time that you have the chip in hand. So that's a long process. We're well away, well along that path in terms of where we're at, but it's lot of, obviously, detailed architectural work. Peter Waxman:We're excited about, uh, the product finalization and also thinking about sort of the next set of steps and next silicon products for integration. But it's- it's a huge effort across a range of companies to- to land something like this.Nic Fillingham:Is the goal to be integrated across the entire silicon spectrum in terms of consumer, low-end, affordable consumer devices, all the way through to secure e-work stations, uh, and sort of everything in between? Or it specifically a solution for more security-conscious, sort of enterprise customers?Peter Waxman:Great question. Yeah. No, so this is important. We see this capability as something that just is a fundamental security property that needs to be there on a modern device. We have seen, we've all seen how over the last 10, 15 years there's just been an increasing amount of sophistication, not just in software attacks but in attacks that basically deal with low-level aspects of vulnerabilities in firmware, hardware attacks that exist. You can get up to nation-state stuff, and we see things, whether it's in the Snowden leaks or particular instances of nation-state attacks, that are taking advantage of, say, firmware vulnerabilities.Peter Waxman:But it's more common that than. I mean, there are criminal networks that have exploited UEFI components in PCs to basically connect PCs to botnet networks to cause a variety of- of issues there. There continue to be, on a week-in, week-out basis, month-in, month-out basis, vulnerabilities that are reported that exist in a variety of firmware components or new hardware disclosures that exist. Peter Waxman:So it is something that is cross-cutting, it's something that is not just an enterprise issue. It's something where, you know, this raises the security of all devices, and is basically something that the average consumer has a right to expect of their device. That expectation Peter Waxman:Absolutely needs to be there from the lowest end consumer device to the highest end enterprise device. We... And, and Microsoft just committed to that. Natalia Godyla:So with Pluton becoming a new industry gold standard, I'm sure that also means that it'll become a target or a goal for hackers to try to break into. So, what are the challenges for hackers? What would they need to overcome in order to actually hack to Pluton processor in a, in a hypothetical situation? Peter Waxman:Yeah, it's a good question. I mean, there's certainly, especially in the research community, there's a lot of established, uh, research and techniques that folks do to, uh, break into hardware products. I mean, we've seen that certainly, like, going back to the Xbox days, right? There's, uh... One of the things that's interesting about sorta the consumer gaming security space is that in order for the adversaries to thrive, they're not necessarily a criminal network, they're not a nation-state, and they need to share information so you can kind of observe them more easily. But there are techniques and capabilities that folks have addressed and, obviously, with Pluton we're trying to ensure that we are targeting a bar that makes it very challenging for them to attack the system. Peter Waxman:It is one, though, we're never gonna say that there's any perfect security system, and so you have to design your system to be renewable. You have to allow for the fact that they're going to be, gonna be issues that are gonna be found and make sure that you can update, you can patch, and also that you have defense in depth. So, if a hardware measure is defeated, you have something backing that up. We feel confident about, uh, Pluton just in terms of its, it, it is battle-tested. Peter Waxman:This is something that we started on this journey 10 years ago. We've continued to invest in the capability and we're not done investing in the capability. We will continue to harden and strengthen it over time. But it's, you know, we're, we're talking about super cool equipment that a variety of folks'll go over to try to glitch and figure out what timing abilities does an attacker have to figure out if they issue a, a 20 nanosecond pulse on exactly this pin and exactly ti- this time at boot can they glitch the system to cause a, a, or, say, a crypto operation or what have you to basically fail. Peter Waxman:These are the rates of attacks that come into a scope when you get into hardware security and, so, we've got a bunch of super bright folks that are experienced in this space, but, uh, we'll be interested to see how the threat actors respond and... It's also important to note that Pluton, we don't trust in the system, there's a critical security component, but it's not the only security component, right? The whole stack of, uh, security that, you know, st- stands on top whether it's an OEM device and their firmware or in Windows itself or in applications. These all matter, too. Peter Waxman:An application can still have a vulnerability in it that is remotely exploited regardless of Pluton being in the system. And, so, you've got to look at the whole system from a security perspective to make sure that, uh, we're continuing to drive security across, up, and down the stack. Nic Fillingham:And, Peter, I assume, uh, Microsoft, as well as the actual silicon manufacturers, you know, they're actively gonna be pen testing, uh, the Pluton processor over time, right? So, as Pluton is defined and as it goes into production and as it actually gets into the hands of, of customers, there'll be a continual effort on behalf of Microsoft and, I assume, also the silicon partners, too. Keep it secure and, and see if we can hack it ourselves to, to deter and find any potential vulnerabilities and address them. Is that part of the process?Peter Waxman:Absolutely. Absolutely. Nic, so, Microsoft, the history that we've got with Pluton, we have both ourselves and involved third parties in doing hardware penetration tests, hard- hardware hacking on it to assess its strength. We have a, a long history of working with our hardware partners on hardware security and working with them on basically issues in firmware and hardware in their silicon. And, obviously, for the particular partnerships, both parties, you know, in this case Intel, AMD, and Qualcomm, are fully aligned with us in ensuring that their security teams, our security teams, red team and pen test teams, and external evaluation that, basically, we get as much eyes on this to find any issues before anyone else does and, hopefully, to not find anything, which has been the case to date. When we do, to basically respond and, and react to, uh, accordingly with our partners. Natalia Godyla:And, what learnings did you have so far from the days in which you put Pluton into an Xbox and now? Like, what have you changed in the processor for the PCs for this new announcement? If, if anything?Peter Waxman:We've evolved in a number of areas. I think that one is that just the application of it is different somewhat in the PC than it is in an Xbox than it is in an IoT device. So, for example, TPM functionality, which we talked about earlier is something that we don't need a standardized TPM in the Xbox. It's all sort of vertically integrated. Stack, we do things that are similar to a TPM, but we don't need that capability. But in a PC, that's a standardized functionality that exists in pretty much every PC today. And, so, there are capabilities that we've added to be able to, say, support that from a firmware perspective and where needed to add additional hardware blocks.Peter Waxman:We have advanced. There's places where it's just a matter of hardening the design that we have in Pluton. So, some amount of resistance to physical attacks that we've increased over time. And, it's also, you know, supporting newer capabilities that may exist in, in the industry. If I think back to Xbox days, the expectations around crypto key lengths, for example, right? We didn't have as many crypto algorithms or quite as long key lengths. We supported, say, in the, you know, early implementations of HSP versus today. Now that we have quantum crypto creeping up on us over the next 10 to 15 years, right? There's a much higher focus, for example, on longer crypto key lengths to make sure that we can maintain resistance until we get to sorta implementation, more common implementations of post-quantum crypto algorithms. Peter Waxman:So, some examples of places where we have just evolved and, um, you know the way Microsoft views it the Pluton-based, the, the architecture and design is something that we evolved for all end points and, so, you'll see, for example, that the Pluton is in the latest Xbox series X and S that we announced, came to market with, and launched in November is a more advanced version, right, based upon that newer capability set then what was there in the Xbox One. So, as I mentioned, continue to sort of update this technology and continue to make it available through these range of markets.Nic Fillingham:I want to ask about the architecture of the Pluton security processor. When it goes onto the actual CPU die, is it going to be a tax on the CPU? Is it, or is it sort of occupying such a trivial amount of sort of transistors and, you know, storage elements that you're not gonna know that your computer is Pluton powered? It's just gonna be happening silently and completely invisibly in the background.Peter Waxman:Yeah. That's r-, that's right. It is, from a power perspective or sort of any other aspect from an end-user, you're... Basically it's a small component when you think about it in relation to a modern SOC or modern CPU. It's not taking any relevant amount of power that's at all gonna be noticeable from the device perspective. It's basically this hidden component inside the SOC, system on a chip, complex that, uh, is basically working on your behalf ensuring you have a much higher security experience as a result, but you will not notice it being there. That's right. It's basically invisible. Nic Fillingham:And, and just circling back to that Xbox comment, so, so I've got an Xbox One, uh, here at home. It's the Xbox One S.Peter Waxman:Yep.Nic Fillingham:So, there is a version or a precursor to the Pluton on my Xbox. Is it Pluton v. 1 or is it pre-Pluton? How should I sort of think about that? Peter Waxman:You've got Pluton. You've got Pluton.Nic Fillingham:I've got Pluton? Peter Waxman:You got Pluton.Nic Fillingham:Yeah. Peter Waxman:Yes.Natalia Godyla:(laughs)Peter Waxman:(laughs)Nic Fillingham:Can I get a sticker? Can I get a sticker to put on my Xbox that says you got Pluton, baby?Peter Waxman:I will get to work on that, Nic. I love the idea. I love the idea. I think... I... Your t-shirts and stickers. I think that's, you know, that may be the, uh, the holiday project coming up. Nic Fillingham:And, then, so, moving forward, at some point, when I'm buying a new piece of computing, whether it's a laptop, whether it's an IoT device, or I get something else with a CPU inside it, I'm gonna want to look for probably a Pluton sticker or a Pluton badge or something that lets me know that the CPU or the SOC contains the Pluton architecture. Is that, again, part of the vision for Pluton?Peter Waxman:It's a great question. I don't think we've come to a conclusion on it. I'm not sure that we're gonna get to the dancing Intel guys in their, uh, clean suits, uh, commercials on T.V.Nic Fillingham:That's a, that's a callback to, like, is it the 90s? When they do that? That was a long time ago.Peter Waxman:(laughs) Yeah. That's, that's showing my age there, perhaps. Nic Fillingham:Natalia wasn't born then. She doesn't know what that is. Peter Waxman:(laughs). Natalia Godyla:Right over my head. Peter Waxman:(laughs)Nic Fillingham:(laughs) But, I mean, in terms of as a consumer, or a potential consumer, or even just a, you know, an employee at a company, do you envisage that it'll get to a point where I'll have, you know, an opportunity to buy a Pluton secured device and a non-Pluton secured device and so, therefore, I'm gonna wanna think about my needs, my security needs, and make sure I'm getting that Pluton secured device or, again, maybe to what you said earlier, it's just gonna be completely invisible, completely integrated into the silicon? You're not gonna worry about it, but you're just gonna know that there's, there's a higher grade of sort of fidelity and security on that device because of the architecture in the CPU. Peter Waxman:Yeah, I mean, our goal is really to get to that point where it's ubiquitous and it's just there. I mean, it's, again, if we're gonna provide, uh, customers with the level of security that is required in today's day and age, we've got to get to a point where this is like oxygen. It's everywhere. It's just a common ingredient that exists. We have to work with our ecosystem. We have to basically work to a path where, you know, we get there. It's not on the market yet. It's gonna take some time. There will be points in time where it's a journey to get there and not every system is, is certainly gonna have it, but our vision is this just needs to be everywhere. Peter Waxman:It's something where, you know, we're doing this not to make money off of this thing. Not to basically drive specific scenarios. Not to charge and up-prem as we talked about earlier for enterprises. This is about how do we make sure that everyone from consumers to enterprises to you name it has something where we're taking the last 15 years of hardware and systems security, hard learnings, and bringing it and modernizing the PC space based upon those learnings. Nic Fillingham:How did you come up with Pluton? I had not heard Pluton before I plugged it into Wikipedia, which is the font of all knowledge and it tells me that it is an igneous intrusion... No. No. It is a body of intrusive-Peter Waxman:(laughs).Nic Fillingham:... igneous rock. So, how'd you get Pluton, but, maybe more importantly, tell me some of the names that you considered, but didn't go with? Can you-Peter Waxman:(laughs)Peter Waxman:... can you let a few cats out of the bag? Proverbial cats out of the proverbial bags? Natalia Godyla:Most important question. (laughs)Peter Waxman:So, this one, Nic, I think we're gonna have to put the pause button on the recording-Nic Fillingham:Ahhh.Peter Waxman:... and I actually have no good answer nor do I have a great joke to go, uh-Natalia Godyla:(laughs)Peter Waxman:... to go, to go make fun. You know, so, it's, like, code name/buzzword that we use publicly. It's one word. It sounds cool. Nic Fillingham:It does. Sounds very cool.Peter Waxman:It's not named by anything else. And, uh, it's... If you think about hey, this thing is going to set the direction and do something leading, it's, like, a north star that's out there. Sounds cool. I don't know what it means. Nic Fillingham:(laughs)Natalia Godyla:(laughs)Peter Waxman:I didn't even know it was an igneous rock until you mentioned it, honestly. But, uh, yeah. Exactly. I...Nic Fillingham:It is an igneous intrusion.Peter Waxman:Igneous intrusion. I stand corrected. Natalia Godyla:(laughs) Peter Waxman:God. I'm gonna have to go look up that 'cause that, that's kind of freaky and scary. Natalia Godyla:I feel like that's the best answer.Peter Waxman:(laughs).Natalia Godyla:It sounds cool. Nic Fillingham:It sounds cool. That's totally-Peter Waxman:It's authentic. Natalia Godyla:(laughs)Nic Fillingham:Yeah. That's totally fine for it to sound cool. I did wonder if there might have been something a little bit more sort of esoteric and, and deep to it, but I'm totally happy with it sounding cool. We'll have to, we'll have to go and talk to some of your colleagues to see if, uh, maybe Dave Weston can let us in on a few, uh, names that didn't make it that we could, we could make fun of on another podcast episode. Peter Waxman:Yeah. Microsoft Bob was one option, but it was taken. So, uh...Nic Fillingham:(laughs) Peter Waxman:Yeah. No. Dave will be good to, uh, get history there.Nic Fillingham:Peter Waxman, thank you so much for your time and for joining us. And, uh, I would love to have you back on the podcast on another episode to discuss the history of Xbox security and maybe mod chips and Xbox hacking and all that cool stuff that we all did in the early 90s. Oh, the early 2000s-Peter Waxman:(laughs)Nic Fillingham:... I should say. Peter Waxman:Awesome. Awesome. I really appreciate it, Nic. Natalia, it's been an awesome discussion so thank you very much.Natalia Godyla:Yeah, thanks for being on the show. Natalia Godyla:And, now, let's meet an expert from the Microsoft security team to learn more about the diverse backgrounds and experiences of the humans creating AI and tech at Microsoft. Natalia Godyla:Hello, Madeline Carmichael. Welcome to the show. Madeline:Hi, thanks for having me. Natalia Godyla:It's great to have you on the show. I have never talked to a threat intel librarian before so let's start with that. Can you, can you tell us about that role? What does your day-to-day look like? How did get into Natalia Godyla:... becoming a Threat Intel Librarian.Interviewee:Yeah. I mean, I can pretty safely say you're among good company in not having met someone with that job title (laughing). I get a lot of really interesting reactions to the title. And, to be honest, it's kind of self-styled (laughs), so it's not like an official Microsoft HR title. But that's the one I go with for my day to day function and what I actually do. So, basically, I work as part of the Threat Intel team in the Microsoft Threat Intelligence Center and as a Threat Intel Librarian for them. And that means I'm sort of responsible for organizing a nation-state threat actors that we track and supporting the end-to-end business process that enables the team to do that as efficiently as possible.Interviewee:So, recently, I've added being a MITRE attack evangelist to my description and my role. So I look at how we can integrate that framework into our workflows and how that can help us do more with our data to support internal workflows. But also how we can share better Intel with our partners. And the MSTIC team sort of tracks nation-state actors, primarily. There's a little bit of wiggle room around human-operated ransomware. It's becoming a, a more concerning threat and we're, we're onboarding some of that. We currently have more than 270 groups on our radar and that's between named groups that we, we name after the periodic table of elements.Interviewee:So, so when we speak publicly, you'll hear things, uh, named after that. And then we have what we call dev groups, which are sort of the pre-stage, it's for our internal tracking and to keep, keep things in order. But we don't tend to discuss those publicly. Yeah, we do like security detection, analytics, um, response capabilities for Microsoft end customers. And that kind of entails providing threat intel to Microsoft and defender teams across the company, and then out to customers through security products. So I originally started as a, well, thought I was going to be a librarian and probably a public librarian at that. I was doing that degree and there was an option to do, uh, an internship or a co-op for credit, not a requirement, but I found an interesting job posting.Interviewee:So took a chance and applied for it and got it. And that was with a research library for the government of Canada. And that was great. I really, really enjoyed working there, and actually, ended up finishing my last (laughs) two degree credits distance while I was still working. That kind of led to moving on to a team that my role was doing aggregate reporting and sort of trend analysis a little bit for the executive leadership at the org. And from there, just got interested in the actual cybersecurity analyst part of the team, and eventually, moved over to that, which was where I got the skills that kind of transitioned into my role at Microsoft.Natalia Godyla:I'm just going to un- unpack some of the roles there and some of the skills that you're, you're bringing to role as a Threat Intel Librarian. So in the research library, when you're saying that you got into data reporting, what, what were you reporting on?Interviewee:So that was mostly incidents that have been tracked by that team during the month or the quarter. And so it was just kind of aggregating that data in sort of human-readable format that could be sent up to executive leadership. So they were aware of kind of the high level trends that were happening.Nic Fillingham:But, you, so when you were studying, you said you, you found a job posting, you said it was an internship, is that correct?Interviewee:Yeah, co-op internship. However you want to call.Nic Fillingham:Got it, a co-, a co-op, and that was with the government of Canada/Interviewee:Yep.Nic Fillingham:And is it accurate to say that was sort of more of a traditional librarian style role? You, you are physically in a building that had a lot of sort of printed stuff or am I like way too old school and antiquated in my thinking (laughing)?Interviewee:No, it was kind of in the middle of that. There was a physical library, and yeah, definitely more towards the traditional end. Slightly untraditional, I guess, in the sense that it was like a focused collection. So it was specific to the type of research that, that group was doing. But, otherwise, yeah, books and cataloging and, uh, organizing that.Natalia Godyla:Why cybersecurity or how were you exposed to cybersecurity? Was it part of the research that the library had or was it just that subsequent roles brought you closer and closer to the field?Interviewee:Mostly the sort of subsequent role is getting closer and closer. It feels pretty serendipitous when I look back at it now. Like I didn't intentionally set out for a career in cybersecurity or Microsoft or where, where I am. I, uh, did a presentation a couple of years ago for a conference, uh, in the UK that's run by a woman at Microsoft and it's called TechHer, more, more like TechHer. So I did this presentation at TechHer, which is a, a conference run by Microsoft UK. And it aims to kind of give women more networking opportunities and sort of more visibility into technical roles. And during that presentation, I, I called myself an Accidental Threat Intel Analyst.Interviewee:At the time I was still in that analyst role, more the, the Threat Intel Librarian role. And it's kind of true, like I never intended for that. Accidental is maybe giving myself too little credit for taking some, some opportunities that presented themselves (laughs). But, yeah, it was just kind of each pivot kind of brought me one, one step closer and I thought it was really interesting. And I've been lucky to work with people who are really engaging and their passion for it is contagious. So, yeah, I guess that's why I stuck around.Nic Fillingham:So what do you do as the Threat Intel Librarian to expand the collection of knowledge and data and, and papers and content in a particular direction? Who, who are your customers and, and how do you go about expanding that collection?Interviewee:My customers, I guess, or my, my user base would be the threat analysts on the team. And the collection of data is their analytic output, essentially. So it's less curating new collection and less providing resources as it is organizing the output that they're producing. So we have a, a knowledge base that holds all of the threat intelligence that the team produces. And the aim there is to organize that in a way that makes it more friendly for capturing data, but also, um, produces more usable output for downstream users, whether they be in Microsoft as other security teams or Microsoft customers through security products.Nic Fillingham:And what tools or sort of platforms do you use, you know, this knowledge base? Are you, is it SharePoint or is it some other sort of more secure encrypted storage system? I mean, uh, maybe you can't talk about it, but, but what sort of in, in a general sense do you, are your tools that you're using day in, day out?Interviewee:So that's changed over the years since I've been here. I've had a number of iterations where we store things, we, we're using, uh, DevOps at one point and kind of mashing that into our scenarios. But we're now using a proprietary knowledge base that's being developed by a dev team out of ILDC.Natalia Godyla:So what big goals do you have around the library that you are maintaining, building? What's, what's next for you to optimize? What are some challenges that you're trying to tackle?Interviewee:Well, yeah, so the, the nature of tracking nation state threats and like threat actors is that capturing the relevant threat intel means you often end up with a lot of data that's constantly evolving based on what the actors are doing. It's hard to keep tidy. So the ultimate goal, I guess, is to make our knowledge base as organized as possible to enable as much automation as possible. The threat analysts do a lot of repeatable pivots or queries. And those are really important for, for maintaining an ongoing awareness of what the, the threat actors are doing. But a lot of that can be codified and then made into a repeatable process where they just have to like check in and make sure it's functioning accurately.Interviewee:And then that allows time for them to do the really clever stuff that takes nuance and a human sort of intuition and experience with tracking for actors to do well. Not all of it can be reproduced by a computer. So as much of the sort of day-to-day stuff that we can automate as possible, that's, that's great. And we do that by having well-labeled classified data that's organized, and yeah, we can feed it to an automation pipeline and then let the analysts do the fun stuff.Natalia Godyla:So speaking of classification, we, we chatted with Jeremy about how we came to the names of some of the threat actors. I know you mentioned we use the periodic table. What was the impetus for that? Why are we using the periodic table and wha- what's going to happen after the periodic tables run-up?Interviewee:(laughs) Uh, well, that was in place before I started. So I, unfortunately, can't take credit for (laughing) why it was chosen. I think it was probably chosen because it's a, a, a ready set of names that are easily identifiable to the general public. You can kind of say we named things after periodic elements and most people will know or have some familiarity with that. So there's some, not really branding, but that kind of familiarization so that if you hear a name like that, you think MSTIC and Microsoft. It's also not rooted in a specific culture, really, so there's not any cultural connections or connotations that you need to worry about for applying a name. It's going to be used publicly and associated with Microsoft (laughs), so.Nic Fillingham:One of the questions we asked Jeremy was, is there a logic behind why one particular group would be given a particular element? Like, you know, are all the inert gases, are they, are they a particular continent or something? Or were they all discovered in the 2000s? Is, is there, is there any logic or is it, is it... because I think the, the joke we made with, with Jeremy was whether or not there was a, a big periodic table of elements against a wall? And then there was a bucket of dots (laughing). And as a new group comes out, you grab a, you grab a dart and you throw it at the wall. Uh, where are you in that continuum?Natalia Godyla:It's funny the second time around too.Interviewee:Yeah, I mean, honestly, I wish that was the case. It would be pretty cathartic, I think. But, no, there- there's no logic to the, the name choices we decided or my predecessors decided not to add that layer to the naming. So they're meant to just be just a name. We're, I think, careful as Microsoft about what kind of associations or what we mean when we say, like, we, we choose what we say carefully. And I think it was intentional not to associate that sort of, um, this type of name means this origin for an actor. We, we wanted to have that level of abstraction still.Natalia Godyla:There are more groups, though, don't you track more groups than there are elements in the table? Is that, am I right there?Interviewee:Yeah, so we have two types of groups. The ones that have element names are what we would call sort of permanent groups, or it's a permanent name. And that kind of is just the level of, uh, awareness we have for the group. So it's a more mature understanding of the threat actor that has that name. Um, we have a second type of name and we, we call them dev groups, um, dev for development. And it just means they're, they're in development and they're not as fully f- fleshed out as the element names. So it gives us a little more flexibility to kind of label clusters of activity without having to do as much rigor b- behind that sort of is that cluster and what its scope and breadth is.Interviewee:So there's definitely cases where multiple dev numbers or dev groups will merge into one named element group as we develop more of an understanding about who the threat actor is. Um, yeah, so I think we have over 185 dev groups on the go at the moment, and then 89 element groups. And that will probably change very quickly. So the numbers are not actually that useful (laughs), uh, uh, long-term, but yeah. It, we, we have more dev groups because they're easier to spin up and faster and they're, they're meant to be precursors for the named groups. But as, as you say, there are not that many elements. So we, uh, we'll be running out rather soon (laughs). I'm not sure what's going to come out.Nic Fillingham:You'll be into the theoretical element-Interviewee:Yes.Nic Fillingham:... category, genre. What's the one from, uh, Avatar? Unobtainium or something?Interviewee:Yeah, yeah, I think that might be it (laughing).Nic Fillingham:Was that right? And then there's, what's the one that's bonded to Wolverine skeleton? That's, that's a made-up one too, isn't it?Natalia Godyla:Oh, you have an, uh-Nic Fillingham:Adamantium, Adamantium (laughing).Natalia Godyla:... wealth of knowledge about this (laughing).Nic Fillingham:Yeah.Interviewee:We recently actually added another name schema and they're named after volcanoes. I don't know if that came up in your conversation with Jeremy, but as we put more focus on tracking human-operated ransomware groups, we thought they're distinct enough from the nation-state groups that we would have a separate schema for those. So there's some, some volcano names that are out Interviewee:... they're now, and it's the same kind of idea where dev numbers still support both names. And as we develop maturity, it, of awareness on a group, if it's a nation-state, it'll get an element and if it's human-operated ransomware, it gets a volcano.Nic Fillingham:You know what? I probably should've asked this at the tippy-top of the conversation, but why do we name these groups? What is the value in assigning a name and then actually sort of publicizing the name of that group? Where, where is the value to threat hunters to analysts to customers? What- what's the rationale behind this?Interviewee:Yeah. So, I guess it's mostly for consistency. It's, it's kind of a language of its own. And you use language to communicate, so having a name and being able to explain what that name means is important. So, one of the other things that our team does is write activity group profiles. They go along with alerts in security products. Interviewee:So, a customer might get an alert and they'll get this, this document that contains context of what that means for them, and that will include things like the TTPs that that group uses, some of their infrastructure, or like malware that goes along with it, and context that kind of explains their typical motivations or their typical targeting. Interviewee:So if you're in an industry that is a, a usual target for that group, it might make sense for you to say, "Oh, yeah. Like, it makes sense that we were targeted, it makes sense that this alert is hitting our network, or our endpoints." Interviewee:But it is also useful to know if you're an outlier in that circumstance. That might mean you pay more attention to it because you're not a typical target for that group. But yeah, so having a name is just a, a way to kind of say, "We mean this group," and here is the context that goes with it, and it's a consistent message.Natalia Godyla:What other ways are customers benefiting from this library? So, you noted that the alerts will have some of this context that you've been gathering. What other features or capabilities are based on the library?Interviewee:So, yeah, it's our awareness of the group long term. So, it allows us to kind of see what we would expect of them. We, because we have this body of knowledge built up, we can then see quickly if a tactic or a technique that they're now undertaking is brand now. That's kind of a departure from their normal M.O., that's more interesting. It's useful context. Interviewee:Yeah, for Microsoft as well as customers, we use our own TI to help defend ourselves. And, yeah, I guess it's just a, a way to kind of contextualize what is happening with IOCs or indicators of attack. They're kind of distinct bits of information that help you detect or protect or respond to a threat.Interviewee:They contextualize indicators of attack or IOCs, and those, those can be really s- like, small bits of information that help you detect a threat actor. And just having an IP address doesn't really tell you a lot, so that's useful to kind of have that explanation that goes with it that says, "This IP address is used by this group in this way," and that informs how you respond to it as well, depending on the, the attack slide, is useful for how you mitigate that. Interviewee:And that's a, a big part of why we're starting to add the, the MITRE ATT&CK classification to our data as well. It's a clearer language or repeatable way of describing something to your customers. And the customers as well have started to use attack labeling in their own data sets, so it's a good way to kind of match things up.Interviewee:And you can layer customer protections that have been mapped to the attack framework with detections on our side that have those attack techniques labeled. And when you layer those on top of each other, you can find gaps really easily and find how they might need to improve their security posture in a certain area.Interviewee:If, say, its reactor uses a certain technique and that, that customer has a, a gap in detections in that area, they can go, "Oh, well, we are a typical target for this group. We're not super well secured in that area. Maybe we should focus our investment there."Nic Fillingham:So, is it accurate to say that naming these groups and sort of building and maintaining a profile on them allows both hunters and analysts and then customers to better understand where they may or not be a target, and then therefore, how their security strategy should evolve?Interviewee:Yeah, definitely. Yeah. Natalia Godyla:(laughs) Nic Fillingham:Cool. I got my head around it. I must admit, the very first time I read a, a blog post from Mystic and I, I saw, you know, the name, like, "Here's the name of the threat actor and here's what other industry groups sort of name them," I was like, "I don't get it. Why, why are we naming them?"Interviewee:(laughs) Nic Fillingham:But, I, I got it now. So, thank you so much.Interviewee:(laughs) Cool, glad that came through. (laughs) Nic Fillingham:I'm glad that this podcast exists, exclusively for me to, to get my, (laughs) get my questions answered. Natalia Godyla:(laughs) Interviewee:(laughs)Nic Fillingham:Hopefully someone had a similar question and we, we helped answered them. Thank you.Natalia Godyla:So now that you've been in the cybersecurity space for several years now, come to a role that feels like it marries a lot of what you've studied and done throughout your career, the cybersecurity and library are coming together in the name. What comes next that is... Does this feel like it's a merging of the worlds or is there something you want to do after this, either in the cybersecurity space or not?Interviewee:That's a great question. Yeah, I wish five-year planning came easier to me. (laughs) Natalia Godyla:(laughs) Interviewee:Although in, in the world of COVID, I don't know that anyone can plan that far ahead. But yeah, I, I don't know. And I think because I got sort of sidetracked from my original public library path, I haven't really thought about how I would go back to that. Interviewee:I mean, libraries are becoming much more digital now anyways. It's a great way to serve more content to your patrons and your, your, your users in the world of e-readers and eBooks and podcasts and things like that.Interviewee:Libraries procure that kind of content for their users all the time, but yeah, I don't know. I don't, I don't know what's next. I mean, I'm happy where I am. So, yeah, stick here for a little while. Nic Fillingham:Madeline, one of the questions we'd like to ask in, in this part of the podcast is what from your personal life, your hobbies, your interests outside of work, so first of all, what are they? And second of all, do any of them, do you bring any of them into your day job?Interviewee:Yeah. I mean, I feel like this is where your assertion earlier that I broke all of the librarian stereotypes will fall down, because I do love to read and I have two cats. Um... (laughs) Natalia Godyla:(laughs) Nic Fillingham:(laughs) And you just travel round to libraries with your-Natalia Godyla:(laughs) Nic Fillingham:... with your cats and your, and your book bag? That's all you do? Interviewee:Uh, yeah, yeah. I mean, if the cats were allowed in the library, that would definitely be something.Natalia Godyla:(laughs)Interviewee:But I think library tourism is a very underrated area. Expedia should look into that. Nic Fillingham:And apart from reading, cats, and visiting other libraries, is there anything else you're willing to divulge?Interviewee:(laughs) I don't know that a lot of it actually makes its way into my day job. Baking is another hobby, but we're not in the office, (laughs) so I can't really share that with anybody. Nic Fillingham:What's your favorite baking show to binge? Are you a Great British Bake Off fan?Interviewee:I am. Since moving here, I've definitely started watching that.Natalia Godyla:(laughs) Nic Fillingham:Have you thought about entering? Do you wanna be a contestant?Interviewee:I did actually consider it at the end of this year's series, but I haven't got up the nerve to actually apply yet, and I don't know that I could take the pressure of having to figure out all of those (laughs) different baking techniques without a recipe. (laughs) Natalia Godyla:What is one of your favorite books of all time? I was gonna say, what's your favorite booK? But I feel like that's just an impossible question to answer, unless you have one.Interviewee:I, so I generally read fiction. That's my primary genre, but that kind of covers a lot of different (laughs) sub- sub-genres of fiction.Natalia Godyla:(laughs) Interviewee:I think my go-to answer for my favorite book is usually Anna Karenina by Tolstoy. (laughs)Nic Fillingham:In the original Russian? Interviewee:Of course, yeah. No. (laughs) Nic Fillingham:(laughs) Natalia Godyla:(laughs) Interviewee:No. Yet, I should say. Um-Nic Fillingham:There, there's different translations, right? Is-Interviewee:There are, yeah.Nic Fillingham:Which one do you like? Interviewee:It's by Richard Pevear and Larissa Vol- Volokhonsky, I think. I'm probably not pronouncing her last name very well. But yeah, it's, it's a great book. And it's long and you have to flip back to the, the list of character names every five pages or so and every character seems to have five names.Nic Fillingham:(laughs)Natalia Godyla:All the diminutives. Yep. (laughs) Interviewee:Yes, yeah, (laughs) precisely. Nic Fillingham:(laughs) Interviewee:Uh, but it's good. I, I just, it has always stuck with me as a book I really enjoyed. Natalia Godyla:Well, thank you, Madeline, for being on the show. Interviewee:Yeah, it was great to speak with you guys. Thanks for having me. Natalia Godyla:(singing) Well, we had a great time unlocking insights into security. From research to artificial intelligence, keep an eye out for our next episode.Nic Fillingham:And don't forget to tweet us @msftsecurity or email us at email@example.com with topics you'd like to hear on a future episode. Until then, stay safe.Natalia Godyla:Stay secure.
BEC: Homoglyphs, Drop Accounts, and CEO Fraud
CCI: Cyber Crime Investigation. Another day, another email attack - something smells “phishy” in the network. *Slowly puts on sunglasses and flips up trench coat collar* Time to go to work.Just how easy is it for someone to steal your credentials? Because once they’re stolen, and sold for pocket change, it’s open season. Homoglyphs, drop accounts, email forwarding… is it any wonder billions of dollars have been lost to BEC (business email compromise)?Join hosts Nic Fillingham and Natalia Godyla for a fascinating conversation with Peter Anaman, Director and Principal Investigator of the CELA Digital Crimes Unit, as they unpack the cybercrime section of the Microsoft Digital Defense Report to see what these phishers are up to. Scott Christiansen joins us later in the show to recount his journey to security and his role as an Adjunct Professor for Bellevue University's Master of Science in Cybersecurity, along with some great advice for choosing security as a profession.In This Episode, You Will Learn: •The difference between consumer and enterprise phishing•The types of people and professions that are usually targeted in cyber attacks•How putting policies on backups and policies to protect the organization in place will help prevent digital crimes•The four categories of the internet: the dark web, the surface web, the deep web, and the vetted webSome Questions We Ask: •What would an example of credential phishing look like?•What is the end goal for phishers?•How are phishing and business email compromise techniques leveraged during the pandemic?•What patterns are being seen when it comes to credential phishing?•How do you use ML to classify whether a bug is security-related or not?Resources: Microsoft Digital Defense Report:https://www.microsoft.com/en-us/security/business/security-intelligence-reportPeter’s LinkedInhttps://www.linkedin.com/in/anamanp/Scott’s LinkedInhttps://www.linkedin.com/in/scottchristiansen/Nic’s LinkedInhttps://www.linkedin.com/in/nicfill/Natalia’s LinkedInhttps://www.linkedin.com/in/nataliagodyla/Microsoft Security Blog:https://www.microsoft.com/security/blog/ Transcript(Full transcript can be found athttps://aka.ms/SecurityUnlockedEp13)Nic Fillingham:Hello and welcome to Security Unlocked, a new podcast from Microsoft, where we unlock insights from the latest in news and research, from across Microsoft Security, Engineering, and Operations teams. I'm Nic Fillingham-Natalia Godyla:And I'm Natalia Godyla. In each episode, we'll discuss the latest stories from Microsoft Security, deep dive into the newest thread intel, research, and data science.Nic Fillingham:And profile some of the fascinating people working on artificial intelligence in Microsoft Security. If you enjoy the podcast, have a request for a topic you'd like covered, or have some feedback on how we can make the podcast better-Natalia Godyla:Please contact us at firstname.lastname@example.org or via Microsoft Security on Twitter. We'd love to hear from you.Natalia Godyla:Hi Nic. Welcome to Episode 13.Nic Fillingham:Thank you, Natalia. Uh, welcome to you as well. I'd just like to say, for the record, I like the number 13. I'm embracing 13. Do we know why 13 is unlucky number? Is there ... Is it just superstition?Natalia Godyla:There are a lot of theories. 13 people at the Last Supper, that's part of the reason. 13-Nic Fillingham:At, really?Natalia Godyla:... steps to the gallows.Nic Fillingham:I'd, I think this is baloney. I don't think-Natalia Godyla:(laughs)Nic Fillingham:... this is real. I think-Natalia Godyla:I think-Nic Fillingham:... 13's a great number. I think we should celebrate it-Natalia Godyla:You know what? That's a, that's a good approach. Let's do it.Nic Fillingham:And we should celebrate it-Natalia Godyla:With jokes-Nic Fillingham:With a joke (laughs). So, before we started rolling, we were lamenting the fact that there are very few, if any, like, true, sort of security, cybersecurity-flavored jokes. So, we sort of created some, or we, we've evolved some. Do you wanna go first, Natalia? 'Cause you've got a joke that I've not heard. So this would be, in theory, a genuine reaction. Do you wanna give me your joke?Natalia Godyla:Yeah. Ready?Nic Fillingham:Yep.Natalia Godyla:What's a secret agent's go-to fashion?Nic Fillingham:I don't know. What's a secret agent's go-to fashion?Natalia Godyla:Spyware.Audience:(laughs)Nic Fillingham:Spyware. Yes. That's all right.Natalia Godyla:Wow. Didn't-Nic Fillingham:It's okay.Natalia Godyla:... even try for a chuckle.Nic Fillingham:I did. No, I genuinely did. I was like-Natalia Godyla:I barely got a smile, guys.Nic Fillingham:Aw, I was hoping to like that one. It just-Natalia Godyla:(laughs)Nic Fillingham:... spyware, yeah. No, it's okay. So, you've heard this already, but the audience haven't, and I know that they're all gonna be absolutely cracking up when they hear this. So, what do you do when your pyramid gets infected with Ransomware? You encrypt it. That's pretty good, right? That's pretty good.Natalia Godyla:I've got a new one. We're gonna try-Nic Fillingham:Okay.Natalia Godyla:... a new one.Nic Fillingham:I'm gonna try and laugh. Like, I'm gonna be in the right frame of mind for, if it is funny, I'm gonna try and laugh. You ready? (laughs)Natalia Godyla:I like that little "If it is funny." All right-Nic Fillingham:Well.Natalia Godyla:Why doesn't Superman fight cyber crime?Nic Fillingham:Why?Natalia Godyla:Because he's scared of cryptocurrency.Nic Fillingham:Oh, no, no, no, no, no, no, no, no. Okay, so it's a joke about. It's a jo, no, no we're gonna pull this one apart and we're gonna fix it.Natalia Godyla:Right. Right.Nic Fillingham:So it's a word play on cryptocurrency. So, it's gotta be something like, Superman's laptop, no that's not it. But we're gonna work on this.Natalia Godyla:Strong start.Nic Fillingham:If you're a, a dear listener of the podcast, if you think you can make this Superman joke work for us, let us not. Securityunlocked@microsoft.com or hit up on the Twitter's MSFD Security.Natalia Godyla:So do we wanna tell everyone about this week's episode?Nic Fillingham:(laughs) I, I guess we probably should. On today's episode, we speak to Peter Anaman who is gonna talk to us about business email compromise. This is the fourth of five conversations we're having on the podcast to cover content from the MDDR. Peter explains to us the difference between sort of general phishing in the consumer email space, and phishing and email compromise in sort of sort of business corporate world, and also what the attackers are doing once they do compromise a business email account. Make sure to follow along at home by downloading the Digital Defense Report aka.ms/whackdigitaldefense. And then after that, we speak with-Natalia Godyla:Scott Christiansen a senior program editor at Microsoft who as he says it "is the security conscience for our company". So, he does a lot of work on the software development lifecycle and ensuring that we are delivering secure code, that we're adhering to our policies and standards around what it means to have secure code. And, in addition to all of that, he's a professor so he talks to us about the cybersecurity program that he's part of and it's a great conversation.Nic Fillingham:It is. On with the pod.Natalia Godyla:On with the pod. Nic Fillingham:Peter Anaman welcome to the security unlock podcast. Thanks for joining us.Peter Anaman:Thank you for inviting me.Nic Fillingham:Well, we'd like to start the podcast off with getting our interviewees to give us a quick introduction to who they are. Obviously we'd love to know your title but more uh, interestingly is tell us about what you do uh, day to day. What's your, what's your job look like?Peter Anaman:So my name is Pierre or Peter Anaman and I work in the digital crimes unit in the Microsoft [inaudible 00:05:08] Organization, which is the legal group. And within this group I'm part of the Global Strategic Enforcement Team, and we currently are focusing on BEC or Business Email Compromise. As regard to my title, Cyber crime Investigator, so I focus on developing cases that we then either pursue with a civil lawsuit or, you know, or to identify the thread actors, or we develop cases that are then subject to a criminal refer to law enforcement where we believe the thread actors are located. So, that's what I do on my day to day basis. As far as looking at prints, looking at intelligence, dark web data to try and see how the criminal, online criminals are using different tools in order for us to try and be ready and up to date. Nic Fillingham:That's an amazing title. I'd love to have that on a business card.Peter Anaman:(laughs)Nic Fillingham:So is your background law enforcement? Are you a lawyer? This might be a very uh, broad question but how did you get to where you are? Peter Anaman:So I started off pursuing um, once I finished my high school I always wanted to be a lawyer, and so I pursued legal studies and went to law school in the UK. And when I finished law school I, I had a, uh, a passion for pursuing like legal, um, law enforcement related activities, and the law and police was one but I heard the army had a very stringent course in France, and so I pursued a full month uh, accelerated course to become an officer in the French Army. And uh, so, and thereafter I was a Lieutenant. I had to leave but always had a purs, um, a passion for enforcement and from there I ended up working in a law firm trying to combat online piracy as well as different types of cyber crimes. Peter Anaman:So, it, it included piracy but it was also, child sexual abuse material where you know, we uh, support the law enforcement where we can. And that just developed. And I developed skills. I did amass this in information security to learn some of the tools, how the internet works, and just learned what I needed to and was curious. I spoke with a lot of experts that they taught me so many things on the way. And now I ended up working in this amazing organization.Nic Fillingham:On today's episode in this discussion, we're talking once again about the, the Microsoft Digital Defense Report, the MDDR which came out uh, in September of, of this year of 2020. And Peter, you're here to talk to us about a section or, or part of the state of cyber crime which is called phishing and business email compromise. You, you contributed heavily to this report. Could you just sort of tee us up, if, if, if you've not heard about the MDDR, the Microsoft Digital Defense Report and you're sort of you know, interested in downloading it and learning more, tell is about this section of phishing and business email compromise. What, what's the scope of this section and what, what are you gonna learn in it?Peter Anaman:Phishing has been um, you know with a Ph for those who don't know, involves where, typically involves where people [inaudible 00:07:57] are sent emails to people, and once in the inbox entice you to click a link, you know to upgrade, update your password or something of that nature, increasingly is being related to themes like news, like Covid-19, or election related. And when you click the link you go to a site where they ask you for your credentials, and once they have your credentials then they in most cases, may have access to your account. Unless you've got two factor authentication or some other security measures. Peter Anaman:And so, this section what we try to deep dive, is try to explain the different types of cases that may fall in that, in that category of online crime. And what I mean by that is you see from the sections there's one on credential phishing, there's a second which is more based on BEC Business Email Compromise, sometimes called CEO Fraud and we can speak about it a bit later. And then there's a third category which is really a combination of first two where the thread actors use credential phishing and then lead to some kind of fraud, financial fraud.Natalia Godyla:So wha, what patterns are you seeing when it comes to credential phishing? How does this manifest in an attack? What would an example of credential phishing look like? Peter Anaman:So when you look at each of these sections, the three of them, I can provide a little bit more depth. And so, in the first instance, credential phishing, as I mentioned earlier, it would be when a person would receive and email claiming to be you know, security department or a, you know, some h, highly important thing that they have to do, and when the person clicks the link, they are then sent to a webpage which looks like the, the legitimate office 365 login page as an example. And when they enter their credentials, the source code of that webpage has a form and the form has instructions. And those instructions are, when someone clicks submit, collect information in the username and password, and send it to what we call a drop account. Right? It's like an email address that collects the information submitted on that page.Peter Anaman:Now, we know this because through our investigations, we analyze you know, a p, I think we're on about ten [inaudible 00:10:06], hundreds of thousands of URL's every day to determine if they are phishing or not. And so we have seen how the in, information submitted from the email and from that email, what they do in some instances, in credential phishing is that they know that some people, like researchers will submit dummy information. So what whey do is they do a, a check. Right? They take the credentials and try to impersonate someone sent connected to the account, using some con, uh, they call it an SMTP checker, it's a, as in to keep the protocol for sending email. And so they check the credential and it works, they know it's valid. If it's not valid, they get rid of it.Peter Anaman:And then, once it's valid, we have seen like literally in minutes, it can lead to what we call BEC and our [inaudible 00:10:51]. So that's credential phishing essentially. But boldly the three differently areas we're seeing these credentials being used, we see them being sold on the dark web for very little. Because then other people can use it to send spam for example, or unsolicited commercial emails. They could use it to look at the person's account and steal confidential information, or business email compromise. So, that's how credentials are used typically.Peter Anaman:We then move to BEC and CEO fraud. There it's uh, I think most of the time, some people like to use BEC to include phishing but it's really a different type of activity. And the reason they use business email and compromise, is that this activity is targ;eting companies. And the reason is, it's another way of stealing money from the bank, right so to speak. And what I mean by that is that they've realized, the criminals have realized that companies have processes in place. Right? So for example I wanna b, I wanna pay for a service. Well it goes to procurement, and it goes to accounts payable, and they make a, a payment. Peter Anaman:Well, understanding this kind of almost a supply chain, right? The criminals have realized that, s, Peter Anaman:If they can monitor for wire transfers or transactions, they can like take over that conversation and redirect the payment to a different account. And this is how it could work based on what we've seen. So, as I mentioned, you have credential, they then have access to your account. When they have access to your account, in most cases we see two things happen. One, they add a forwarding rule. So they add an inbox forward- forwarding rule which says if you receive an email and in the subject or the body, you see accounts payable, invoice, USD, EUR, so different keywords that are related to a transaction, forward it to this email account. In other cases, what they do is they say forward it to an RSS folder. So a folder in your account and so then they will access your account and that specific folder to get the email messages which makes it harder to identify who they are, right? Because if they have an email or someone accesses that email. Peter Anaman:So once they add the forwarding rule and messages are sent and they find an email about the payment due, what they do is they look at who are the parties and depending on who, who is the person receiving the money, they'll get rid of them on the chain and create a homoglyph domain name. A homoglyph, it's like the Egyptian times, right? Something that is made to look like. It impersonates another domain name. For example, an I becomes a one. Right, or O for Oscar becomes a zero. So it's a slight change. And what they do then is that they have to use the same name as the person who they've removed and they continue the conversation. And at some point they say, hey, my account has changed. Updated PDF, this is our new bank account.Peter Anaman:Well because the people on the chain have been part of the chain, they think is legitimate. And so they make changes to the payee, to the instructions. And then the money is moved to a different account. It's just terrible when you see how much money has been lost. And if you read all the reports, you know, it's in the billions of dollars that have been lost this way. And that's why BEC has become very, very important to tackle as a type of crime. Peter Anaman:Now the third category, we said was a combination. And the reason is that in BEC, the second category, there are cases where it's almost like a stakeout, right? They see a company because they go to a website like, uh, the city has to make public, all the RFPs, you know, orders that they have to do 'cause they have to be public. So they see who may be bidding for a contract. And then they'll impersonate that person and try and get access to the payments for that government contract as an example. So that doesn't use credential phishing, right? It's, they're just looking for public information in order to understand what relationships are and to take over a transaction. Fascinating stuff, you know. Someone could make a movie out of how these people operate.Nic Fillingham:And is BEC the sort of end goal for the phishes? So for example, is phishing in the consumer space, the harvesting of, of credentials then being used to launch and mount, uh, BEC attacks in order to actually make some money?Peter Anaman:So I think there is a way we can distinguish between consumer and enterprise phishing. So the difference between sort of a, a spray concept, which is for consumers, just try and get as many accounts compared to the enterprise, the business email compromise, where it's more targeted. And the difference is that when you create a new Hotmail or Outlook or Gmail account, the systems know it's new, right? When I say it's new, is that if you were to send me an email from outlook.com, right, I would know it was created yesterday. But if it started to send emails to like a lot of, 200 people is highly suspect. But if you were able to get a person who's had the account, like let's say for 10 years, right? Well maybe that's not a anomaly because the person has lots of friends. They have lots of contacts, right. The, it looks like a real person. And so it's more likely to go under the radar when it comes to detection. And those could be some of the benefits of using compromised consumer email accounts. Just one example, there are many others.Peter Anaman:On the enterprise side, what we've seen for example in some of the attacks, is that the people who are being targeted typically within the category, right? We see a lot of executives, for example, in the C-suite that'd be being targeted. We see a lot of people in the accounts department, which have been targeted. We see directors being targeted because these are people who can authorize payments. They're not looking to send an email to a person who cannot help them, unless maybe it's an executive assistant who then can give them access to the inbox of the C-suite. Peter Anaman:Now in my presentation, I've spoken at times of dark web and I think I'll just put a sentence behind that. You know, dark web is a word that is used often, but in this context, I'm just speaking about places where people sell, conduct activities associated with criminal activity. The web is divided into four categories from my lens. One is the surface web, which is indexed like through search engines. The second is called the deep web. Those are websites that are either password protected like an online forum, where you have to register an account before you get in or a dynamically created website. So for example, a new site where the content changes, changes on a regular basis. So that's a deep web, it's not index. One of the biggest parts. Peter Anaman:Then the dark web is really tall, right? That's where you need a specialized search engine, you have to use, go to dot onion websites and that's a different category, dark web. Then you have the vetted web. The vetted web are websites where in for you to get access you need to be vouched. Which means that another criminal has to say you're a bad guy, and or girl. And so then you will be able to access it. And it's a way for them to try and trust each other. But in my context-Nic Fillingham:It's the, it's the Twitter blue tick of, of the bad guys.Peter Anaman:Yes, they're trying, they're trying, they're trying. Uh, but [inaudible 00:18:17] all of them. So, you know, for, for what that matters.Natalia Godyla:One other section of the Microsoft Digital Defense Report that you had covered was the section on COVID-19 themed phishing learners. So can you talk a little bit about how these techniques for phishing and Business Email Compromise were leveraged during the time of the pandemic and are continuing to be levered?Peter Anaman:So one of the, one of the patterns or trends we've noticed is that often the criminals change their attack mechanisms or the way they send messages based on lures which are relevant to a group of people in a specific time. As an example, we saw the same with you see it with, uh, elections or sport games or something to do with a celebrity. In this case with COVID-19 at the beginning of the year, we started to see a change and he came from a specific and came in different people were doing it, but we saw it more naturally with one group. Where we were tracking them for mid-December on the activities they were conducting, phishing activities they were conducting. They were using for example, financial statements, or they were using bonuses or different lures about finance and then all of a sudden they changed and they started to use COVID-19 bonus as a lure where they would say, "Hey, click this link to find out about your club COVID-19 bonus."Peter Anaman:And so when people click the link, it was sent to an Office 365 login page, and they submitted their credentials. A lot of people submitted their credentials from the logs we've analyzed because they believe that it was something that was relevant for them at that time. And that was part of the lure. And after a few months they changed, we were able to technically counter what they were doing and they moved to a different method of attack. It's just using, using the time.Peter Anaman:We just recently saw it with elections, for example, the same thing, the US elections. And we saw there were, there were some groups who had modified how they presented the email to people in order to encourage them to click the link and lead them to a phishing page. So the COVID-19 lures are something that we've noticed. It's part of a broader theme related to, uh, societal events, which are criminal's trying to take advantage of to increase the possibility of people clicking a link, right? It has to be believable. And it has to be a sense of urgency.Natalia Godyla:Do you ever think we'll preempt the societal moments? So if there's some big moment happening, we can assume that a cyber crime would leverage that societal moment as a lure and so we could plan ahead?Peter Anaman:One thing which would be difficult is as a company, we have a wide array of customers and we want all our customers to show up the way they want to show up, you know, without having to try and be someone else and not authentic. And with that in mind, it really, and even a step further, these people, right? They work for different organizations and in different organizations, they have different cultures that they have different ways of working. If you look at, for example, a manufacturing company where maybe IT may not be at the forefront, what the way they interact with IT will be very different to if you went to a startup, a tech startup, where that's what they do most of the time, not manufacturing, right? And so when we have such a wide array of customers and we've got governments, right, we got governments from different countries, some like each other, some don't. We have banks, we've got, we have different types of customers and Microsoft, all of a sudden becomes the protector, right? Because criminals are targeting banks, but they're our customer. So they rely on our security as well.Peter Anaman:So when we go back and speak about lures and things, these are things that we have to as cyber-crime enforces, we have to understand it happens. And so as we build technical measures, we have to implement technical measures that are adjustable and can, can change based on patterns it's observing. So I think the way to attack it is always to have this kind of different measures that are working together and leverage artificial intelligence and machine learning models in order to help us distinguish between different types of criminal activity and protect our customers. If that makes sense.Natalia Godyla:And what is our guidance to customers on what they can be doing to help prevent against these attacks?Peter Anaman:One is always to have good policies in place within the company, right? So that all employees are aware about how to make sure the devices are up to date. Don't pick up a USB on the street and put it in, you know, uh, make sure internally there are policies on backups, make sure you've got an online and offline backup, right? So you have to have policies in place that help protect the organization. The second part is to work hand in hand with their technology providers, right? So for example, if you work with Office 365, make sure that we have something called a Secure Store, a Secure Score. that's Secure Score is based on experience. We can say, hey, maybe if you have, to have a better score put MFA, Multi-factor authentication. Some of your users allow forwarding, block it. [inaudible 00:23:40] make sure it's admin can only authorize forwarding, right? Or off. 2.0, make sure that, uh, consent has to be from the admin. So there's a secure store that it helped them really implement in a much more secure environment, which will be frictionless. Number three is to have regular tests Peter Anaman:... with any organization. So that, I mean, that could be part of the policy, but typically is not always. Where you have fishing simulations, which are taking place, right? So that you can start to e-, keep the education at the forefront because we're all very busy and sometimes we forget. And I think four is that we have to work, we have to look always to use technology to advance the way you work forward. And what I mean by that is that companies need to think about the digitalization of their work processes. And what I mean is, uh, I mean, this may be a little bit off, but investigating some ransomware cases.Peter Anaman:For example, recently we saw that part of the problem is that some customers have old infrastructure on-prem, for example. And so that is what is being attacked. And once they get into that, then they can pivot and move laterally elsewhere into the organization. So I think digital transformation is by looking at your processes overall, by saying, "Are there ways we can modernize in a way that creates a better security landscape?"Nic Fillingham:Well, thank you for your time today. Again, we were, we were talking about the Microsoft Digital Defense Report, which is available to download for free. We'll put the link in the show notes. Peter Anaman or Pierre Anaman, thank you so much for your time.Peter Anaman:Okay, thank you very much. Be safe.Natalia Godyla:And now let's meet an expert from the Microsoft Security team, to learn more about the diverse backgrounds and experiences of the humans creating AI and tech at Microsoft. Hello, everyone, and welcome back to another episode of Security Unlocked. Today, we are joined by Scott Christiansen, who is a Senior Security Program Manager at Microsoft, as well as a Professor at Bellevue University. Thank you for joining us, Scott.Scott Christiansen:Well, thanks for having me. I appreciate it.Natalia Godyla:I'm really looking forward to this conversation. So, so let's kick it off by just giving a little bit more context behind those two roles. Can you tell us what your day and, and night look like as a program manager and professor? What do you do? What does your team look like? What do you teach?Scott Christiansen:Yeah, absolutely. So let's start with Microsoft, that's the thing that takes the majority of my time. So (laughs) I work in our customer security and trust group. And, specifically within that, our security engineering group within customer security trust. And then, more specifically, I work in our data analytics and insights team. And our group, as a whole, our security engineering team, is responsible for ensuring the company meets the software development life cycle, operational security assurance, policies and requirements that we have. As for any shipping software that we have to ensure that what we're shipping out meets our own internal, um, security standards and our internal security rigor.Scott Christiansen:Which then is tied to plenty of different external security compliance objectives and things like that. So that's kind of a mouthful, but we help ensure that the company's delivering secure code is kind of the nutshell. Or as we like to say, we're kind of the security conscious for the company. We have security teams throughout the products and then throughout the organization. And we're the conscience that comes through and says, "Is everybody doing everything they can be doing? And are there areas where we could be doing better and, you know, how can we help in that space?"Scott Christiansen:And so what we started doing is we started pulling in all the bugs across the company. So we've got like 700 different Azure DevOps repositories where engineers are storing work items and working with. And they generate roughly about probably 50 to 60,000, uh, new work items every single month. And so we suck in all that data to one gigantic data warehouse and we perform kind of analytics on that. That's really branched out to kind of work streams that I very specifically work on. One, I've spoken a little bit externally about this, where there's a blog up on the Microsoft blog site. I've spoken at RSA this past year and it's kind of their machine learning work that we've done with security bug classification.Scott Christiansen:So we pulled in all of the security bugs to this one spot. We said... and some of them are labeled as security, some of them aren't. And we took a look at that and we said, "Well, are there any that aren't labeled as security that should be labeled as security?" So about four years ago, probably, we started a little hackathon project trying to answer that question. And, uh, it's been a small project kind of throughout time with that. But, ultimately, it turned into a product that we've put together where we built a machine learning system, uh, that accurately classifies, uh, these bugs and says, "Hey, this pool of bugs is security and this pool of bugs is non-security."Scott Christiansen:And then for the, the pool of bugs that it says it is security, it will, um, say, "Hey, yeah, these particular subset of those bugs are critical security bugs. These are important security bugs, or these are some other particular severity with that." And we've had just unbelievable accuracy with that. So that's one of the things that I work on. Yeah, so we've got that model built and we're in the process of really, uh, we've got it built. We've classified all this data that we have within the company, and now we're in the process of making that more operational, so the engineering teams can take advantage of it. And then, in turn, finding a way to take that and spend it externally, probably through GitHub.Scott Christiansen:Uh, that's kind of the target that we're looking at, but so external customers and just the security industry as a whole can kind of take advantage of this auto classification piece. I spend a portion of my day doing that. The other portion of my day is kind of around this, this compliance report and GitHub bot. A really incredible code analysis tool. Used to be called [inaudible 00:29:11]. And it does just a phenomenal job at finding software vulnerabilities. And it's our team's job to kind of get that deployed within the company. And right now with getting static analysis stuff rolled out i- is the biggest priority. So that's pretty much what I spend my day on.Scott Christiansen:And the evenings, like you had mentioned, I'm a master's level cybersecurity professor at Bellevue University, uh, specifically, in their online cybersecurity program. And there I teach a few different classes, but most specifically I teach their masters in, um, architecture and design.Nic Fillingham:Thanks for that intro, Scott, uh, oh gosh, I've, I've written down like four questions coming back to, I think, one of the first things you just talked about in your day job, if we can call it that, your Microsoft role, how do you use machine learning to classify whether a bug is security related or not?Scott Christiansen:It started as this, as this summer hackathon project, and it was just a few of us, myself, uh, one of my colleagues, Alok Kumar and one of our other colleagues, Naveen [Nurenja 00:30:09] sat down and said, "Hey, are we missing anything in this space?" And none of the three of us were, were data scientists by any means. Alok had a little bit more an understanding experience with some of the machine learning work. And so we sat down and we go, "Who are the big hot tents in July?" And I started chewing through this problem and I was an expert in the security space. And so I said, "Well, well, those guys were going through and they were looking to see if they could find a machine learning model that might kind of work to help us solve this problem."Scott Christiansen:I went through and I did manual sampling of the bugs to determine if there was actually an issue there or not. So we went through and took a couple thousand bucks that were taken as security and looked to see if we had any misclassified or misidentified bugs there. And then we took a bucket of the bugs that were not classified as security, like another 2000, 3000 random sampling of bugs. And said, "Are there any security bugs in that space that we're missing?" And so we found discrepancies in, in both spaces. And so clearly the things that aren't showing up on the security radar are potentially a problem. The, the good thing is there's a good side to this whole story is that engineers fix bugs regardless if they're security bugs or not.Scott Christiansen:So the stuff that we found that didn't necessarily show up as a security bug was still getting fixed and it was getting fixed within a, a good SLA. So that was good, the right thing was happening, but it wasn't necessarily maybe showing up on everybody's radar. And, more importantly, it wasn't necessarily showing up on a radar where a security assurance person can come say, "Hey, I see you doing some security work over here. Maybe I can give you a hand and I can help you out with that.2 And the, the same was true for the space where we saw all of these security bugs or things that were tagged as security bugs, but they weren't necessarily security related.Scott Christiansen:You know, engineers are wasting kind of these trimmed down SLA fixed times for these, you know, supposed security bugs that aren't there. And so we're spinning up all this excitement around, "Hey, oh, here's the, the security bugs that come in and you have to fix these things." But they're not actual security bugs, and so you're just kind of spinning your wheels on that and, and wasting available engineering effort. So we started building our own machine learning algorithm kind of around this. And we started kind of doing this manual assessment and said, "Okay, out of these bugs that are security, can we find clusters of bugs that are misclassified?"Scott Christiansen:And so, eventually, we did that and it took us a while, it took us a good probably year and a half to come up with, what we would say, was a really kind of gold standard training dataset. We had this big block of bugs, uh, roughly about 300,000 bugs that were classified as security and ahead with the right security severity. And we were confident in those classification numbers. And so that's what we used to then train the model. So as we're going through this, and we got about to that point, we said, "We really need data science expertise." We hired, uh, Mayana Pereira and she's our data scientist for the project. And she's absolutely fantastic.Scott Christiansen:She found error rates associated with the data and how flexible we could be as error information potentially got introduced to our training dataset. She's shifted the algorithms that we've used a couple of different times, and we are light years beyond where we were thanks to kind of her joining the team, uh, and joining the project. And so, yeah, it's been about a four year journey, probably.Nic Fillingham:So just to clarify this, so the machine learning model is simply looking at the title of the bug. It's not looking at like Reaper steps or any other data. It's just, what is the title of the bug?Scott Christiansen:Yup, yup, that's correct.Natalia Godyla:So the courses that you're teaching are around infrastructure and the work that you do and Microsoft is around software development. So how did you get into security? What have you done within the security space? What brought you to these particular domains within security?Scott Christiansen:So I used to actually live in Omaha. I'm not from there, originally from North Dakota, part of the small cluster of people that, that, in this world, that are from North Dakota. But I met my wife up there and we moved down to Omaha. I restarted kind of, kind of my education once I went to Omaha into computer science. I went to school there, I got a job, and eventually, I started working at an architecture engineering company. I say it's a small company, it was a 1200 person company, but it was, at the time, it was the fourth largest architecture engineering company in the, in the US. So it was decent sized.Scott Christiansen:Being a small company, you get hands-on with a lot of different things. And so I'm going to school, I'm working, I'm starting to run all the infrastructure components that, that we have within the company. And we've got like 13 different offices in the US. We started to expand internationally, so I got a lot of exposure in that space. As I'm going to school, I'm trying to figure out exactly what kind of discipline of IT I want to do. At that time, it wasn't necessarily development. I like the Microsoft products, I like server products, I like Linux products. It was really the, the infrastructure stuff. And so I started getting into networking, and then I kinda got bored with that.Scott Christiansen:And so then I kind of went to systems administration of Windows stuff. You know, that one was where I was thinking my focus was going to go. And then I kind of got bored of that. One of the unique things about Omaha is it has a really large, uh, department of defense presence down in Bellevue, Nebraska. They've got an air force space and they have strategic command that's down there too. And one of my professors happened to be a security person that worked at StratCom down at the base.Scott Christiansen:And he was really into security and he kind of taught us some security stuff. And I was like, "Whoa, this is kind of like the Jedi, Sith type of cool, you know, dark hacking. This was before like hacking was like super cool like it, like it is now. It was just kind of this thing, but it's was like, "Hey, you can get software to do things that the software developer didn't expect to do." I'm like, "This is kind of interesting. It's got like the prankster type of thing, right?" And you get this creative mind going and you start going, "I want to do security." So I'm working at the architecture business and I said, "Hey, I'd really like to shift my role into security."Scott Christiansen:So I started doing some security stuff for them, but it's not really necessarily a high target type of business when they said, "Hey, you know, if you're ever looking for something, we're looking for a lead in our incident response group." And, and so shortly thereafter, I moved over and I was the lead for the incident response team for, uh, TD Ameritrade for a number of years. And TD Ameritrade absolutely has targets, they have, not, uh, not only normal criminal targets, they've got nation Scott Christiansen:... state attackers and anybody that's looking to try and steal money an- and hack into large financial enterprises, so that was a really exciting job and we did a lot of really exciting, cool things there, and some neat stuff happened. And then one day, I, I got a call from our, uh, sort of VP of security engineering at the time and he said, "Hey, we really need some help over in the software assurance space." And so I moved over onto that team and wrapped up my dev and my code view chops, and started doing kind of code review and code analysis.Scott Christiansen:And, specifically around that time, we were getting into the mobile app space, and so that's where I really focused my effort, was the kind of mobile applications and ensuring we had security coding practices with that. And then, and then, eventually expanded to kind of, to, to the rest of the enterprise. So, I was working at TD Ameritrade during the day, and I was teaching the one location at night, and then teaching online in between that. Scott Christiansen:And then, I was writing some, uh, the local, um, security groups, too, like the OWASP Omaha, I was president of that for a little while. I was the president of Nebraska InfraGard for a little bit. So pretty active in there, and, uh, Microsoft reached out to, out to me, and said, "Hey, look. We've got this opportunity, and we'd like to talk to you about it." And it's Microsoft, right? So I'm not gonna say no. It's like, you know, some of the smartest people in the world working on these kind of world-changing problems. Scott Christiansen:And I came out, and I will say it took the third different position at Microsoft before I finally actually moved out to Redmond and started working for Microsoft full time. I had two different opportunities tha- that didn't work out. So anybody who's ever interested in working for Microsoft, don't give up. There's enough people here and enough opportunities, I'm sure the right opportunity exists out here for you. And, and clearly it was, because this was ... Eventually when I came out here to do this work, this was absolutely the right fit for my skillset, for the company, and it was this kind of perfect blend, and I, I wouldn't think of anything different beyond that. Scott Christiansen:I absolutely love what I do, and I'm now in a role where I have an opportunity to ... You know, I'm not just securing an enterprise or securing a company. I'm part of, uh, really changing a- around the world as a whole. So it's this really, kind of wonderful opportunity and wonderful role that, that I get to do and these kind of global changing types of things that we ... problem solving, I guess, that we get to work on within the company.Natalia Godyla:I love the context and I can absolutely vouch for your statement about Microsoft. I came to Microsoft after the second roll, um, so going inside Microsoft or having the inside out perspective, I now understand the sheer size of Microsoft and the fact that you just keep trying. If the right fit is there, it'll happen. But your story seems to really have started with a professor who highlighted security as an opportunity. So is there any connection between that professor and your desire to go into teaching? How did the professorship start?Scott Christiansen:Very good question. I was pretty active in the local Omaha security community with the different groups, and there was a guy named Ron Warner, and Ron's a good friend of mine, still is a good friend of mine, and he was very active in the community as a whole. And, around the time that Bellevue University was standing up their cybersecurity program, Ron was there, and he called me up, uh, he was standing up the program. He was the director of the program at the time. Scott Christiansen:And he said, "Hey, look. We're standing this thing up, and I know you've had some experience teaching at ITT Tech." And I started teaching at ITT Tech, 'cause I graduated with my master's degree. I was still, um, friends with some of the professors there, and they said, "Hey, you should come teach for us." And, interestingly enough, I decided to teach for one very specific reason. I wasn't a very cohesive public speaker, and it was a skillset that I really wanted to grow and develop, and I thought. "Wow. A, there's no way for me to be a better public speaker than to go up day and day in front of a group of people and try to deliver a message, and I'm not just talking about something at that point in time. I'm teaching them something, so they have to come away with knowledge after that."Scott Christiansen:So it was really like a self-growth thing in a space that I felt like I had some level of expertise. Over the course of time, I really started to, to, to develop kind of a rapport, and almost a character, like y- y- you'd put a hat on say, "Okay, this is, this is my teaching hat. This is what I'm gonna go do," and you deliver something that's interesting and engaging. And there was a personal growth component with that, because I'm this old guy by this time. I'm married and I've got kids. I don't have a lot of extracurricular time on my hands, but I have all of these students. Scott Christiansen:It was, uh, it was a scattering of, of male and female students. So I could start to take new ideas and present them as seeds to the students. So like, "Hey, I wonder if you did this," or, "There is an interesting security tool. Do you think you could do this with it?" And I could pique their interest and they go out, and the next week they came back and they're like, "Hey, look at this thing that I did." And so then we all got to learn together with them. That was really, really personally rewarding to be able to do that, to help people learn, but also to see the feedback and me, individually, grow from the knowledge that they were presenting back to myself and back to the class, too. So it was really incredible.Scott Christiansen:And security is hard. It's not an easy discipline. It's not an easy space. It covers the gamut of everything. If you think about security kinda holistically that, you have all these engineers building all of this technology to do thing, security is trying to understand what they did and figure out where they went wrong. So, I don't have to get a lot of people excited about security anymore. They're already excited, 'cause they've started the program. There's definitely some level setting that you have to do, and let them understand kind of what the space looks like, versus what they think it's gonna look like. Scott Christiansen:Everybody think they're gonna come in and they're gonna be a pin tester and they're gonna make millions of dollars and find all these vulnerabilities, and that might be the case for some people. I mean, there's bug bounty programs out there, where people are making significant amounts of money. But there's a space than that, and that's a very specific subset of everything that you can do in security. There's a lotta opportunities for lots of other people to do lots of different things. So I'd like to help do that, too. Scott Christiansen:But more importantly, I'd like to help the students understand how to properly secure things. There's a lot of misinformation kind of in that space, or people have misguided expectations on how to secure specific things. There's a definitely a right way to r- to do things and a wrong way to do things, and so that's one of the things that I feel I probably contribute the most is saying, "Here's a right way to do this." But sometimes, if you have some knowledge or, or you have that background already, i- the online experience can be very successful for you, or if you're just really good at ... you don't mind asking questions.Nic Fillingham:I love that you said if you find yourself not succeeding in an in-person environment, go check out online and see if that's the right thing for you, and, and the inverse. That's fantastic advice. Well, Scott, is there anything you wanted to plug or, uh, point people to before we let you go? Any sort of resources, blogs, communities you like?Scott Christiansen:Besides assessing that the machine learning model is the right tool, or the machine learning that we built right now is the right tool for external customers, we're doing a lot of our own, individual assessment. You know, Microsoft has gone down this awesome path of responsible AI and ethical AI. So, wh- We're no different to that process. In addition to seeing how well the model does within this outside Microsoft, we're also running it through the gamut. Scott Christiansen:So we've taken it through, um, our legal resources to say, "Here's our model." You know, "If we were to release this thing tomorrow externally, would you be okay with it? Here's the data that we used. Here's the data owners that own the data that we're using. Do you think it's okay with them that we've built this model and it does these things?" We've got security teams now within the company that do, uh, this responsible AI and security AI work, and we've talked to them through the risks associated potentially with our model and, and what the model could do. Scott Christiansen:That whole security AI space is really new, so it's interesting for a security team to come out with this security classification model and then kind of go through all those reviews. We're in the process of starting to work with some security AI pen testers now within the company, so people that in their specific skillset is attacking these AI and, and ML models and finding vulnerabilities and flaws kind of associated with that. So we're engaging with them, uh, to do that.Scott Christiansen:So we're doing a lot of different work kind of with that. And, again, that's all because we've trained this model on a non-public data set. So, if we expose the model externally, we wanna make sure that it's not gonna expose any of this non-public information to the rest of the world. If all this turns out and it fails, so far, it looks like it's not, but if it does, then, you know, being a responsible engineer in this space, we have to go get public data to do this.Scott Christiansen:And if we trained it with public data, that would be fine, but it's taken us three years to kind of get to this particular point to build up this kind of reference data set. It's gonna take that long externally. And so what we wanna do is try and see if what we have is, is good enough to put out there, but, uh, do it in absolutely the most responsible way for Microsoft and our engineers and our customers that we possibly can. So if there's any plug, i- it is that plug and that responsible AI is super, super important, and we're doing our best to kind of adhere to those goals.Nic Fillingham:Well, Scott Christiansen, thank you so much for being on Security Unlocked.Scott Christiansen:Yeah, absolutely. Thank you so much for having me. I ... Uh, it was really rewarding. I really appreciate it.Natalia Godyla:Well, we had a great time unlocking insights into security from research to artificial intelligence. Keep an eye out for our next episode.Nic Fillingham:And don't forget to tweet us at MSFTsecurity or email us at securityunlocked at Microsoft.com with topics you'd like to hear on a future episode. Until then, stay safe.Natalia Godyla:Stay secure.
All Your Pa$$w0rd Are Belong to Us
Special Edition!We’ve been told for years how important passwords are, taught how to make them stronger and longer and better, and we frantically tear up our home or office when we can’t find that sticky note where we wrote them down. Life feels like it comes to a screeching halt when we’ve lost our passwords, but… what would life be like if we didn’t need them? Can your passwords truly become a thing of the past? Sounds a bit unnerving, but we can promise you, it’s always security first here at Microsoft.On this special edition episode of the Security Unlocked podcast, hosts Nic Fillingham and Natalia Godyla explore the journey of becoming passwordless with Alex Weinert, Director of Identity Security at Microsoft, as he explains why your passwords don’t matter and how going passwordless can protect you from attackers.In This Episode, You Will Learn: • The risks that are being mitigated through passwordless authentication• Where the challenges lie within using passwordless authentication• The functions of Windows Hello, Microsoft Authenticator and FIDO tokens• How ML is used in these technologiesSome Questions We Ask: • What does passwordless mean?• What are some common misconceptions or risks?• Where are customers on their journey to going passwordless?•What is the end goal for passwordless authentication?Resources:Alex’s Blog Posthttps://techcommunity.microsoft.com/t5/azure-active-directory-identity/your-pa-word-doesn-t-matter/ba-p/731984Alex’s LinkedInhttps://www.linkedin.com/in/alexweinert/Nic’s LinkedInhttps://www.linkedin.com/in/nicfill/Natalia’s LinkedInhttps://www.linkedin.com/in/nataliagodyla/Microsoft Security Blog:https://www.microsoft.com/security/blog/Transcript(Full transcript can be found athttps://aka.ms/SecurityUnlockedEp12)Nic Fillingham:Hello, and welcome to Security Unlocked, a new podcast from Microsoft, where we unlock insights from the latest in news and research from across Microsoft security engineering and operations teams. I am Nic Fillingham.Natalia Godyla:And I am Natalia Godyla. In each episode, we'll discuss the latest stories from Microsoft Security, deep dive into the newest threat intel, research and data science.Nic Fillingham:And profile some of the fascinating people working on artificial intelligence in Microsoft Security. If you enjoy the podcast, have a request for a topic you'd like covered or have some feedback on how we can make the podcast better ...Natalia Godyla:Please contact us at email@example.com or via Microsoft Security on Twitter. We'd love to hear from you. Hi Nic, how's it going? Welcome to Episode 12 and welcome to three months of podcasting.Nic Fillingham:Yeah. Thanks Italia. This episode marks the, us passing the, the three-month mark, which is pretty cool, of Natalia and I being professional podcasters. I've actually put that on my LinkedIn profile now. So I think that makes it, uh, that makes it official. And I see you, we're obviously an audio only podcast, but as part of the recording, we have our cameras on. I can see Natalia that you appear to have embraced outward, which we, we talked about in the last episode. And you now appear to be in a small cave-like environment.Natalia Godyla:It does feel like a-Nic Fillingham:(laughs).Natalia Godyla:... cave-like environment. I can tell you that. I did transform my closet into my podcast studio. So it was a whole project this weekend. It's swanky, but I can tell you, there are some drawbacks. It is about 3,000 degrees in here.Nic Fillingham:(laughs).Natalia Godyla:I did not plan for that this podcast episode. So I'm, I'm dying a bit.Nic Fillingham:You're in the right place, though, if you decide like, "I'm not appropriately dressed for the temperature." You, you're actually in the perfect place to make that-Natalia Godyla:Yes, I, I mean-Nic Fillingham:... make that change.Natalia Godyla:... theoretically, yes. The other hazard of my current setup is getting locked in the closet, which has happened already. I did have to email for help.Nic Fillingham:(laughs). Who did you email?Natalia Godyla:So I emailed my partner who proceeded to Instagram, a picture of my email. It's just me in all capital letters asking him to get me out of the closet. So I'm glad that posting a picture to Instagram was of high priority in that circumstance.Nic Fillingham:Your partner was like literally feet away, right? Just, just drywall and framing away from you.Natalia Godyla:Yes, but I, I did an amazing job with my podcast studio. These blankets are intense.Nic Fillingham:Yeah. So like, were you banging on the window and the door and all that stuff? And he just couldn't hear you because the, the soundproofing was so phenomenal?Natalia Godyla:There was no knocking. Immediately, emails.Nic Fillingham:You were not, not even gonna to try, not even gonna try and knock. 'Cause I know, I know that I've done such a great job of deadening all sound. The only thing I can do is send a, an all caps email (laughing) subject.Natalia Godyla:The only option. This is all for our audience.Nic Fillingham:You know what? We had to, because our guests were coming on with better and better microphones, including the person you're gonna, you're gonna hear from today, Alex Weinert, who has a recording studio in his home basement. And he and I geeked out on bass guitars. But that, that wasn't the, the goal of the conversation. The goal of the conversation, um, was to talk about passwords.Nic Fillingham:And in fact, this conversation with Alex was so, was so awesome that we couldn't really edit it down. We've decided to do a special episode, which we haven't, we haven't done this before. Natalia, you're grieving away. Is there music coming through your headphones? What's going on?Natalia Godyla:No. I'm that interested in what you're saying, Nic.Nic Fillingham:(laughs).Natalia Godyla:I'm just grooving along with it.Nic Fillingham:L-, Natalia is literally like bopping away. I c-, I, she's bopping away to invisible music. Well, you, you take it from here. Tell us about the, uh-Natalia Godyla:(laughs).Nic Fillingham:You're obviously very excited. Tell us about the conversation we (laughing) had with Weinert.Natalia Godyla:Yeah. So we had a special episode with Alex, as you were saying. We talked about the future of passwords or perhaps the lack of future for passwords. So the inherent risks in continuing to use passwords is ... And some of the risks also with, uh, SMS, which I found really fascinating, the, the concept of it being out of bound, out-of-band and potentially then being intercepted.Natalia Godyla:Um, and then we just really dove into the reality of passwordless. What is the science behind building some of these password technologies? How real is it? How many customers are using it? So it was great to s-, get that substantive approach to passwordless, something that we keep hearing as a buzz term.Nic Fillingham:Yeah. This is a great episode to listen to after you, uh, get through Episode 8, which was with, uh, Maria Maria Puertas Calvo from the Identity team who talked about how that group utilizes artificial intelligence and machine learning. And then after we spoke with Maria, I think we might have been, we might have stopped recording at that point.Nic Fillingham:That Maria recommended that we then sort of move that conversation forward by getting on the phone or, or Teams as it is, uh, and chat with Alex to talk about passwords and the future, the history, the past, the, the good, the bad, the ugly of passwords. So it's a great conversation. We hope you enjoy it. On with the pod?Natalia Godyla:On with the pod.Nic Fillingham:Welcome to the Security Unlocked Podcast, Alex Weinert.Alex Weinert:Hey, how are you? Nice to be here.Nic Fillingham:Thank you so much for joining us, Alex, um, from your, uh, from your home recording studio, which we might, might touch on a little bit later. It looks, it looks pretty awesome. Alex, we normally ask people to first of all, sort of introduced themselves, and, and talk about their role. We will get to that, but I think I just want to sort of set the stage here. You are probably best known to our audience.Nic Fillingham:So let me know if you think it's fair to say you're best known to our, our audience as the, the author of the, All Your Passwords Belong to Us. Did I get that right? Or Your Passwords Don't Matter. You have some great blog posts, which really talk about the fact that passwords are bad. Don't use password. Is, is, is-Alex Weinert:Yeah, Your Password Doesn't Matter as a blog, that kind of took off. And then in my, in my, my non-blogging time, I'm the director of Identity Security for Microsoft.Nic Fillingham:Got it. And what does that look like? Like what, what does your team do? Sort of, what does, what does the day-to-day sort of look like for you, Alex? If there is-Alex Weinert:(laughs).Nic Fillingham:... if there is a, a standard day.Alex Weinert:Day-to-day. Um, I often joke that, um, I have a calendar that tells me what I'm, you know, I think I'm going to do on a given day. And then we have-Natalia Godyla:(laughs).Alex Weinert:... you know, various actors that, uh, change that agenda rapidly, uh, at times. First of all, you know, I think you, you spoke to Maria Puertas earlier. She's on the team. She's, uh, an amazing part of that group. And, and basically there are a set of functions that we do. We do internal security. So this is kind of thinking about, you know, how do we do secrets, um, management?Alex Weinert:And how do we set up our environment for dev ops, you know, security and, you know, pipeline security and operational security and all that kind of thing? And just making sure that the core of our identity system stays safe. And then, uh, we have an incident response team, which is sort of ... It would be nice to say the pointy end of the spear, but it's more like the windshield that catches the bugs, right?Alex Weinert:Like they, they deal with all the nasties that come in and, and try to hurt our customers or hurt Microsoft, uh, or customers via Microsoft. So that's another major function. And then what's cool is that this is where the sort of a flywheel starts, which is the things we learn from those investigations and those incidents go into Maria's team, right? And then Maria's team develops the refined, like data science that tells us, how prevalent is the pattern?Alex Weinert:How do we, you know, build detections into the product? How do we intercept those attacks and apply it in the product, so that we can keep them from ever hurting our customers? And then there's a set of teams that are kind of oriented around that signal that, that Maria's team produces. There's a signals intelligence team, which essentially packages that, so that customers can see it.Alex Weinert:There's the prevention team, which is basically about stopping fraud in the system and doing things in an automated way. So like one thing not a lot of people know is that we block, uh, something like 80 million attacks a day that customers never even know about, but we're able to see them. And, and so defending the system and defending customers from fraud, from account takeover attempts, that sort of thing.Alex Weinert:It's something that we do in an automated way on that team. So, um, the configuration by admins as to what credentials are allowed in the organization, and then the combination of that information with usage information and security information to decide, what's the right challenge sequence to show to a customer at a given time? That's, that's another team.Alex Weinert:And then finally, we have a team that is all about empowering end users. So we sort of jokingly call it the, like the karate school, right? Like it's, how do I teach my end users to defend themselves in a world where there's a lot of hostile activities? So the authenticator, which has the password manager feature.Alex Weinert:So that, that feature is part of that team, as well as things like self-service password reset and other, you know, the, the sign-ins logs that you can go look at and tell us whether you think the recent sign-in was fraudulent. And then all of that actually goes back into Maria's team and feeds that information to tune the algorithm.Alex Weinert:So when people, either administrators or users tell that they see something that we didn't notice, or that we got it wrong, that actually goes back in to make us more accurate. So that's kind of the flywheel, right? We go from incidents of bad things happening through data science and then ultimately out to the customer and to the end user and then right back into data science. And then, you know, by, by doing this, we're able to continuously train our systems.Nic Fillingham:Just for sort of scale, number of, of customers or, or number of sort of identities? I do-, I'm not sure what the right metric is here, but sort of we're talking in the hundreds of millions or are we in the billions category?Alex Weinert:Oh no. (laughs). No, like 40 billion log-in events a day, 170-Nic Fillingham:Wow.Alex Weinert:... terabytes of data, data generated per day. Yeah.Nic Fillingham:Wow, and, and, and the number of humans on the planet that are utilizing this, how's, ha-, how do we, how do we measure that? We measure that in the hundreds of millions as well?Alex Weinert:Mmm, billions.Nic Fillingham:In the billions.Alex Weinert:Yeah.Nic Fillingham:Wow. Okay. So these are bi-, pretty big numbers.Alex Weinert:Yeah.Natalia Godyla:(laughs).Alex Weinert:Yeah. (laughing). Relatively large numbers. Yeah.Nic Fillingham:Awesome. Thank you for that context there. So the, the, the, the topic that we sort of really wanted to start with here was, was passwordless. And, and we'll jump into that in just a sec, but I actually want to start with the fundamental of, you know, there's a lot of ... You know passwordless is, is, is sort of a newish term. It's sort of a buzz term. It's, it's being thrown around.Nic Fillingham:Can you define for us ... It may sound like a very simple question, but what is passwordless? What da-, what does it mean and what does it mean to us?Alex Weinert:Yeah. I mean conceptually, it is exactly what it sounds like, which is passwordless is when you authenticate yourself into a system without ever typing a password. The blog you mentioned earlier, you know, Your Password Doesn't Matter, it kind of goes into all the ways that, you know, short of using a password manager, it's basically impossible to have a, uh, a password that isn't in some way crackable.Alex Weinert:Um, so multi-factor authentication becomes a mandate, right? Like you have to have a second. If you're using a password basis, and you have to have something else. But the thing about it is that given how easy passwords are to crack, multi-factor auth reverts back to single factor auth pretty quickly in a world where your password gets guessed, right?Alex Weinert:So if your password gets guessed and you don't notice it, or you don't do anything about it, then you're now relying on a single factor, because the original factor is compromised, right? So the challenge we said is, you know, how do we get into a multi-factor authentication system where no password is present and actually try to not make that, you know, more challenging, but actually lower the usability bar? Like make it easier to use, right?Alex Weinert:And so what we looked at, uh, sort of in the initial way was Windows Hello, right? So in Windows Hello, you know, once you set up a device as your own, you can like literally just look at the camera and sign in, or you can touch the fingerprint reader and sign in. And the reason for that is that you have a biometric, right? Plus the device possession, and the device possession is hard mound.Alex Weinert:And so, you know, that model, like you think about that as FIDO is the same thing, except for it just takes ... It, it gives you more portability of the device you're using. So, you know, your, your FIDO tokens are, uh, you know, like on a USB form factor or in your phone PhoneFactor.Alex Weinert:And that allows you to then go from computer to computer and have that same, very strong authenticated experience on devices you haven't been on. And then the last one is the phone app, right? And the, the authenticator app is a way of doing passwordless, because we hard-bind into your phone. And then, again, there's some sort of, uh, secret. In the case of the phones, mostly it's Device Unlock.Alex Weinert:So it's, there's a, either pin or biometric unlock, right? So you're still doing two factors, but you're never having to interact with a password. So you don't forget your password. You don't write your password down. You don't pick a stupid password that ... Oh, I'm sorry. I, you don't pick a easily guessable password.Nic Fillingham:(laughs).Alex Weinert:Um, but I mean, seriously, password 1, 2, 3, come on. And by the way, the most common passwords in use are still things like 1, 2, 3, 4, 5, 6 and "I love you," and like, uh, things that are, you know, QWERTY I, uh, UIP, which is just about running your finger along the keyboard. It's like, so clearly people want less effort to go into their authentication rituals, right?Alex Weinert:So we're trying to figure out how to lower that effort bans, at the same time, make it stronger. The thing that is kind of unique, I think, in ... When we say passwordless right now in, in our authentication systems, we're talking about the authenticator application, Windows Hello and FIDO tokens. But I think we can extend that over time. FIDO gives us a nice framework, nice standards-based framework for extending that over time.Alex Weinert:There's an underlying thing that happens, which is really important. And I wrote about this in All Your Creds Are Belong To Us, which if you're old, like me, and you play old video games, you recognize the reference. Um, and, uh, and in All Your Credits Belo-, Are Belong To Us, we talked about something called verifier impersonation resistant. And that's sort of a heady technical term maybe.Alex Weinert:But what it basically means is that you can't put a machine in the middle of the ritual and trick the user, right? So one of the big problems we have with like tools like Modlishka is that Modlishka, um, does a pretty good job of exactly replicating the UI that the user's expecting to see. So the only thing that's protecting them in that case is that they ignore the ... If they ignore the cert warning, right?Alex Weinert:If they're not paying close attention to the URL they're going to, and that's really ... Unfortunately, most users aren't gonna to either get it, or they'll just literally bypass the warnings. So, um-Nic Fillingham:S-, sorry. What is, what is Modlishka? That's, uh, identity [crosstalk 00:14:07]?Alex Weinert:So Modlishka is a, is a red team ... It's like a pen testing tool.Nic Fillingham:All right, yes.Alex Weinert:And, and you can download it from GitHub, right? Like you can go search for it and download it. And what it does is it effectively, you point it at the server you're trying to intercept, request for. You're, so you're trying to machine in the middle, the request between the client and the, the legitimate server. And so this is actually ... We'll, we'll go super geeky for just a second.Alex Weinert:'Cause this is actually really an important aspect of passwordless that I think most people don't quite get. So basically what happens is when we have a, a situation where like you type in a password, and then you get, uh, an OTP code on your phone. The problem with that is that the communication is out-of-band, which means that the server is gonna say ...Alex Weinert:You know, they're gonna send or transmit a message to your phone and saying, "Hey, please approve this." Or, "Please," you know, "re-key this number." And then the user needs to key that number back in. If the user is tricked to going to, into a machine that is impersonating the identity provider, so if it's impersonating like Azure AD, that impersonalization is facilitated by a tool called Modlishka or other tools like it, that actually scrape all the UI code off of the original server and then replay it on their local server.Alex Weinert:So that's what Modlishka is doing is it's like replaying everything forward. So from a user perspective, this isn't like a hacky, lousy old version of the UI that doesn't look right. It's, it's going to look exactly right. It's going to behave in exactly the same way as the, as the code on the original server. So for a user interacting with that, they're like, "Well, this must be the real thing."Alex Weinert:The server will notice the anomaly. Like our server will notice the anomalies saying, "Hey, I don't think I've seen you on that machine before. So I'll challenge you for MFA." The problem is now the request for the MFA challenge is played forward to the user. And if we have an out-of-band authentication mechanism like SMS, the challenge now goes directly to that user's phone.Alex Weinert:Well, the user thinks they're interacting with us. So then they just key in the code that they got on their phone, right into the, the machine in the middle. The machine in the middle turns around and plays it back to us. We see that as an authentication pass, and then we would issue a token to that machine in the middle. And so that's how it's called OTP phishing. This is how like MFA bypass OTP phishing happens.Alex Weinert:So it's a slightly more sophisticated attack. The difference between that and password is that, uh, a pass should only attack is that if I have your password and there's no other protections, I can go anywhere I want and get new sessions. Whereas in this world, I have to trick you into giving me a session on one machine. And I've only got that session for as long as that token lasts, right?Alex Weinert:So it's a somewhat more limited attack, but it's still a very serious attack. And it's, it's a way to bypass e-, existing multifactor auth methods. So one of the really important things that's built into things like Windows Flow and, you know, FIDO and, and our passwordless methods is that we are looking at the, at the point where you issue the credential, at the point where we say, "Hey, that FIDO token can be used to sign into Azure Active Directory," for example, right?Alex Weinert:The credential is actually looking at the certificate of the machine that it's, it's taking a credential for. And built into the FIDO standard is this, this idea that you would never give the user an option to sign in to something that they haven't signed into before. So it won't ... The token itself will never even present the UI to the user to offer that token, because it'll say, "Nope, this is not a server that I've ever interacted with legitimately before. So I'm just not willing to give you a cred for it."Alex Weinert:So it defeats the machine in the middle of the attack, which is a really important and cool thing that it does. So that thing where you look at the credentials of the service that's asking for the credentials, that's called verifier impersonalization resistance. So that was super nerdy, but it's a really important aspect of this thing, which is that we have a cryptographic relationship between the token that's being used to sign in and the service that it's being used to sign into.Alex Weinert:That's two-way. The trust is both ways. So the, the token has to trust the service too. So if you try to impersonate that service as a machine in the middle, your host, like you're not going to ... It's not going to work. And that's a really cool thing about passwordless. So not only is it, you know, you're not going to write down the password, you're not going to choose to use the guest password, all the other issues with passwords.Alex Weinert:It also bypasses many of the vulnerabilities of existing multifactor auth that is out-of-band in nature.Natalia Godyla:So you've outlined a number of risks that we're trying to mitigate through passwordless. Uh, just thinking about it from the other side, wh-, what are the risks that are still inherent and passwordless? What are, what are some common misconceptions on what it can solve? What should people be continuously aware of even after they've implemented passwordless, other identity technologies that need to be paired with it?Alex Weinert:That's a great question. Um, I think that for those of us who've been around the identity industry and the security side for a long time, uh, the, the thing that we probably worry the most about is, uh, what happened around smart cards, right? And so smart cards ended up being a very secure mechanism that was very niche-y in nature. And the reason for that was that there were serious usability issues and, and manageability issues at the, at the organizational level.Alex Weinert:So for example, if you lose a smart card, you know, you leave your smart card at home, you come to work without it, how do you go to that person, authenticate for the day? And it turns out you need a way to manufacture a new smart card. And that is, uh, an expensive process. And you need to physically get somebody down to a desk and, and issue and all that sort of thing.Alex Weinert:So the form factor, specifically the fact that we had to embed credentials using specialized hardware was kind of a big deal in, in those days. And so, as we went into the new generation of passwordless technologies, we wanted to get the security benefits of, of the, sort of the old PIV and smart card model. But we wanted to do it in a way that we could get great usability as well.Alex Weinert:And so the major things that I think we worry about are actually on that usability spectrum. Like if I have a really strong credential ... Le-, let's, let's first back up. Let's talk about passwords. How many places will give you a password reset based on knowing your mother's maiden name or your last address?Natalia Godyla:(laughs).Alex Weinert:Right? Why would we have-Natalia Godyla:Sounds familiar.Alex Weinert:... such a weak mechanism to, to recover a password? And the answer is because passwords are so intrinsically weak that a weak mechanism in some senses is like a rational response. But when we get to a place where we have like a FIDO token, which is a cryptographically, you know, like ha-, hardware-based cryptography, and it's awesome, right? Do we still want to use your mother's maiden name as a way to recover the credential?Alex Weinert:And so recovery becomes one of the brass ring things that we need to go make sure we get right. So issuance recovery, all the things that are about getting you started. Now, for organizations that can use phones, like this is a great way to go for a lot of organizations, if you're allowed to use your mobile phone in the organization. So you can use the authenticator app.Alex Weinert:We've done a ton of work to have essentially the ability to generate a temporary credential issuance code as a help desk, and then have somebody simply point their phone to the screen and get their new credential. And so some of that, we've like massively lowered the cost and the effort involved for an organization to manage these things.Alex Weinert:But then there's organizations where you're not allowed to use a phone, right? They're either, because you're in a secure environment where phones aren't allowed, you're on a retail floor, or there are union or governmental regulations that prevent requiring, or allowing a customer ... Um, I'm sorry, a user to use their personal devices. Right?Alex Weinert:So then you have this whole issue around, okay, so now you've got hardware. And, so what happens if somebody has a two-hour commute to work, gets there and realizes that they left their, you know, FIDO token on their other key chain, right? Like what happens if, you know, you're borrowing the car or your car is in the shop, whatever?Alex Weinert:So the thing that is of concern when you go into these really strong credentials is that you have to have a pair-wise, really strong, you know, lost, forgot recovery and issuance flow. Like we've had the basic login to windows with a FIDO token working for, I think, a couple of years now, right? Like that's not where the energy is going right now. The energy is going in the usability piece.Alex Weinert:Like how do I get to a place where you can go order a FIDO token from your favorite online retailer, have it show up in your house, you know, via Speed Delivery? Right? So one of the scenarios we talk about is if I'm traveling and I get robbed, right? Like, and I need to get into my machine, what do I do? Right? So I can order one of these things, retail off the shelf.Alex Weinert:I can interact remotely with my help desk. And then I can actually reprovision the strong credential from right there on my, my laptop, you know, in my hotel room, right? Like that ... And I realize this is, you know, the pre-COVID version of this, but it's in fact more relevant now. I've hired, I think, you know, something like 10 people onto my team since March. Not one of those people has had physical contact with anyone from the corporation, and they're all doing strong credentialing. Right?Alex Weinert:And so that, that bootstrapping process is really important to get right, especially now. That's where the real challenges are. I don't think that there's a significant argument to be made for, for the security side of this at all. Like the security here is as good as it gets, short of ... I mean, we're certainly just as good as it gets, right?Alex Weinert:You, you could add other rituals, like manager approvals and that sort of thing. Well, you can do that now. From a credentialing perspective, you don't get much better than a cryptographically strong device where the crypto's being done in hardware and you're validating everything all the way down the chain. The people that worked on FIDO2 did a good job, right? They, they nailed the security promise.Alex Weinert:What we're trying to nail now as the usability promise. And even that on the mainstream line isn't that hard, but when you get into the, "Oops, I," you know, "I washed my FIDO token in the laundry today," right? Like that becomes more of a problem. And so how do you reestablish trust? That's a place where we're putting a lot of investment. And I think that that will be the make or break for, for strong credentials.Alex Weinert:The thing about passwords that, as much as I would like to see them eradicated from usage, the thing about them is, you know, there's essentially an infinite key space. They're super easy to reissue. The user can self-reissue. Like there's a bunch of ease of use stuff around passwords, until you forget that, and that's a whole different problem.Alex Weinert:When you, once you get to a really strong credential, you have to kind of match up the ease of use piece. And that's a big investment.Natalia Godyla:So where are customers on their journey to passwordless? We're at a point where we're improving what we already have. And so, like you said, we're focusing on usability. Are our customers actively using these methodologies? Is there one that is preferred over others? What does that look like for people?Alex Weinert:In broad strokes, adoption of Windows Hello is terrific. Like we have many, many, many customers that their primary sign-in mechanism every single day, as you open your laptop and you get to work. And there's a cryptographically strong handshake happening there, but you don't as a user, think very much about it. You can use a pin, face print, thumbprint. I use a pin ...Alex Weinert:Confession time, uh, because I'm on this crazy deck here, and my, all my scanner, all my actual computing hardware is way over on the side. So the pin is an easy way to do it from the keyboard. But if you were using a, a, like a face scanner, which is built into most laptops, the camera will work in same way that you would look at your phone to unlock it. Then you're just signed in and you don't think about it. And that's a really great user experience.Alex Weinert:And that's actually the experience you're used to on your mobile devices. It's the experience customers are used to on their, on their Windows devices. Then the next place that we see really good traction in, you know, here, it's tens of millions is in the authenticator app, right? So the authenticator app is a very popular option for people to use. It's on the phone. So you want to sign in.Alex Weinert:You gotta, you know ... Thing flashes on your phone, it says, "Please approve." And then you push the number, you know, that matches the screen. And that I think has driven a lot of adoption of the authenticator app. So the authenticator app is the second most popular. And then with FIDO, I'd say people are dipping their toes in the water. Like organizations are getting serious.Alex Weinert:people that wear a lot of tinfoil hats like me, you know, the overall Net/Wall or mission full hats, right? Um, are, are deep into the FIDO experience. And so I sign in every day, uh, using FIDO because I, I know the, you know, the security promise behind it is just outstanding. So m-, my personal accounts, I don't have passwords that I know on any of my personal accounts. I intentionally put random, random strings into all of my password fields as-, and then destroy the strings, so I don't have a copy. All of my sign-ins every single day are passwordless.Natalia Godyla:So you mentioned that, uh, the scenario in which you find out that there has been something suspicious in your account and you respond to the request. But ultimately there's something in the technology identifying something as suspicious. How does that work? Are we using machine learning for that use case? Uh, uh, how do we use it across all of the technologies that you've described?Alex Weinert:Yeah. So back in the beginning of my journey with this team in, I guess it was 2013, we were struggling with the fact that we would, um, go through this process where we would figure out a new attacker signal and we would update our algorithms. And that would take a certain amount of time. And then we would test and we would package and we would deploy to servers all over the world and the fix would go live and the attackers would be disrupted for about a day.Alex Weinert:And then they would adopt to our new algorithms and we had to start over. So we were on like a sort of six-week cycle, you know, to get changes made. And then they were on a sort of a two-day cycle to respond to the changes. And so we were on, you know, what, I think a lot of people who have a long background in defender technology know, which is that it can feel like a treadmill.Alex Weinert:Like you, you take a step, that you take a step and then you're right back where you started. And so we made a bet on adaptive defenses, on adaptive technology for defenses. And that was a really hard bet. I mean, it diverted a bunch of resources and stressed a lot of people out and it went on ... You know, we had a lot of false starts. We've talked to other f-, friends in the industry who, you know, started and abandoned their efforts in this area, because it, it can be frustrating.Alex Weinert:But we got to a place where we could beat our static heuristic algorithms with our machine learning algorithms. And at the time, we looked at like 30 different features. A feature is just an aspect of a log-in, right? Like some ... It could be your IP address. It could be your browser, you know, your agent string, whatever, but we'd look at these things.Alex Weinert:And we looked at like 30 and we would say, "All right, given this combination of factors, what's the probability that this thing is going to be a good log-in or a bad log-in?" When you get into data science, you, you're working with two things. There's precision, which is the number of times, if I say it's bad, how often is it r-, is it really bad? And precision is really important, because it's, it gets into how many times do you artificially challenge a user?Alex Weinert:And that results in user friction and like bad experiences and help desk calls and costs. And people will turn off security technology that gets in their way. And this is an unfortunate truth, right? Like if you put technology in front of your users, that frustrates them. Even though it's the, doing the right thing from a security perspective, the organization will turn it off, because productivity is the higher order bread for every organization.Alex Weinert:And so every CSO knows this and has to live with a sort of balance, right? So one of the things that we have to do as security professionals is we have to put experiences in front of people that actually enhance their experience to the extent possible, or at least minimally disruptive. So precision is the thing that we look at for that when we match the precision of our then best algorithm, which was at around 17%.Alex Weinert:Which means that eight out of 10, roughly eight out of 10 challenges that went to users were unnecessary, right? We were, you're throwing MFA challenges that users are blocking them incorrectly, eight out of 10 times. When we match that with our la-, machine learning stuff, when the machine learning got as smart as our current static algorithms, we started blending the two together and then the machine kept on getting better and better and better.Alex Weinert:And over the close of about four or five years, it got up to, north of 85% precision. On the enterprise side, you're given some flexibility. You can say, essentially, "Hey, I'm more risk sensitive," or "I'm less risk sensitive." And so you can tune that precision. But the other side of the equation that moves is recall. Right? And so recall is how much of the bad traffic are you actually catching? Right?Alex Weinert:So I can get precision to a hundred percent if I simply never challenge, right? If I basically never ever challenge, then I will never bother a good user. And I can say, "Yeah, yeah, yeah, I have nothing wrong," but the problem is I'm also catching no attackers. And in that world, um, I want the best possible recall. Or I could simply challenge everyone, and I can get a hundred percent recall, right? I can bother every good user and everybody. I'll get all the bad users.Alex Weinert:So you, the, the thing that's super tricky in this space is turning that dial to the right place. And so machine learning has done huge amounts for us in that space. So we just recently had an algorithm that was static. And when I say static, I mean that is not machine learning, right? Is traditional heuristic algorithm, that detected a, a, an attack called password spray.Alex Weinert:And our password spray algorithm was about 98% precise, which means that, like, if we said it was a bad user, it was a bad user, you know. 98% probability. We were able to double the recall of that by applying machine learning to it. Like we took the supervised machine learning technology and applied it. And after a brief training period, we released it and we hit, doubled the recall without moving precision at all. Right?Alex Weinert:So that's fantastic. Right? Our precision stayed high and we doubled the amount of bad actors we're, we're catching. And one of the things about recalls, you never know the, the total number, right? 'Cause you don't know what you don't know, unless you're in, in like a thing where you can ...Alex Weinert:There are machine learning environments that you'll see if you go to like conferences, which are all like, "Okay, I had temperatures of cats and temperatures of dogs. And my machine learning algorithm is training." And in a world where you're like in a constrained dataset fine, but attacker's whole job is to be invisible. Their whole job is to, to defeat the machine learning system.Alex Weinert:So when we look at a r-, like doubling of recall, that's a significant step to do that without moving precision at all. And, uh, the team was able to do that. That particular system looks at over 200 aspects of every log-in. And then you're, it uses the machine learning algorithms to, to figure that out. But the most important thing about it is that it will, without our investment, without significant investment, continue to get better.Alex Weinert:And of all the things machine learning did for the team and for the defenses of customers, I think the most important is that it freed up innovation cycles. Like the humans were able to go back to really innovating on, how do we find new attacks? How do we defeat these attackers, w-, while the system continues to do the things that we used to do manually? Which is, "Oh, look, a new parameter. Let's tweak the parameter and propagate it." That's now happening for us automatically. So we can go off and invest in innovation.Nic Fillingham:I just want to maybe get some clarity on, on one little piece there. So I use the authenticator app myself. Obviously, you know, I'm a Microsoft employee, so I, I have to use that for my, my job, but I also use it personally for, for personal services. Every now and then, I do get a ping on the authenticator app that doesn't appear to be from something that I've initiated. It's rare, but it does happen.Nic Fillingham:Can you ... This is a slight digression here, but like what's, what's happening there? Is it always a sort of a malicious act happening on the other side of the, of the coin and the fact that I'm ignoring them, obviously, because I don't initiate it? Is that good? Am I doing the right thing? And is that actually helping the model get better? What, w-, what, what happens in those sort of, I guess, false positives? Is that what it's called?Alex Weinert:Yeah. Well, so that's not necessarily a false positive. I mean, I'm not sure I would call it a false positive. So let me tell you about the, the things that will cause that. The two things that will cause that are an attacker has tried to log in. If you're getting a, you know, the, the three codes presented thing, and, and you have a account that's set up for passwordless, and they might've just typed in your username and they're trying to sign in, obviously you should never hit approve on a request that you don't know where it came from. Right?Nic Fillingham:Right, yes.Alex Weinert:I'd like to be very clear. The other possibility is that you have legacy software that is like, you've, you've left a client running somewhere. And this was the cause for a lot of, um, multifactor authentication and things that don't get answered. Because we have blocks in the system, like you have to complete your phone number entry or whatever, that, that require that before you take that next step.Alex Weinert:But if you have software that is like, "I'm gonna try to log in," and that trips a, a multi-factor authentication challenge, then that can be the other thing that happens sometimes. That's pro-, the primary two. Um, we're, we're doing a bunch of work right now and I, I won't get super specific, but I'll say we're doing a bunch of work to make it hard or nearly impossible to approve a malicious attempt at logging in.Alex Weinert:And so, you know, we have ... The wonderful thing about the authenticator app is in some sense, like our systems, we can adopt it very rapidly, and we can adapt the UX for it very rapidly. So the team's putting a bunch of energy right now into this question of, how do we tune the authenticator, so that users don't do accidental approvals and they don't, you know, respond to those, those kinds of challenges?Alex Weinert:But yeah, the majority of those will be caused by either an attacker who has your username and password, and is tripping the, you know, the last step of the authentication or, uh, an old application that doesn't know that it's triggering MFA.Nic Fillingham:Got it. And so me, me ignoring that, though, am I actually helping? Is there some other step that I should take to say like, "Oh, I don't think I actually requested this?" Like, how do I actually help the machine learning models get better to reduce the times that, that I would see those challenges when I don't request them?Alex Weinert:You can review in, uh, My Sign-ins. You can review that either on the web or on your phone. And then you can indicate that a given log-in request was, or wasn't. You know, they can also help you understand whether your, uh, password is compromised. So for example, if you see someone who got through the password challenge, but got stopped at your MFA challenge and it's coming from a country you've never been to and on a device you would never use, right?Alex Weinert:You click, "This wasn't me," and then we will actually step you step by step, how to re-secure your account. And so this is an important part of our security apparatuses to, you know, get the user involved, and we can walk them through re securing their accounts at that point. So that's kind of the best thing to do. If you're getting challenges, you're not expecting, go look at your sign-in logs and, and then react, you know, if you see something out of, out of whack.Nic Fillingham:That's great advice. Thank you. And I want to touch on one, one other thing that you said. So is the end goal for passwordless that there are no passwords anywhere, or is it simply that a password may exist, but the end user basically never enters it? Is that, is the end goal that on my, my identity, my account, my user entity-Alex Weinert:No.Nic Fillingham:... there is no actual password in any shape or form associated with that, and instead it is things like a FIDO key or some other authentication mechanism? Or is it simply that the password does exist, the user just never, never has to enter it?Alex Weinert:Yeah. Well, so we should be clear with that. I think th-, there are, you know, there are systems that still run FORTRAN. There are systems that still run COBOL. Like-Nic Fillingham:(laughs).Alex Weinert:... VAX assembly systems are still out there. Like you're going to have, you're going to have a long tail of technology that is highly coupled to passwords for a very long time. And, and so some passwords will still exist in the environment. Our, our goal is, uh, as we get users into their sort of daily ritual, that that does not involve a password.Alex Weinert:If you have a password you don't know that is also cryptographically strong, so it's, you know, it's completely, what's called entropic, which means that it's a string that doesn't have any patterns in it at all and it's totally random, then that, and not having a password at all are about the same thing. Right? Which is why I've essentially rendered my accounts passwordless without actually like having a system underneath it that deletes that thing from the environment.Alex Weinert:So yes, the goal, I think long-term ... And I, um, say two things here. First of all, the goal here long-term is absolutely the eradication of what is the weakest possible link in s-, in cybersecurity. And we have moved on from the world where I might want to do the, you know, Tom Hanks, Meg Ryan, you know. You've got mail thing. Like that, that's one bar. And now we're talking about like national infrastructure and like global economies and healthcare, and, you know, like lives on the line who are behind these passwords. Right?Alex Weinert:So we, we have to realize that we've kind of shifted our, our security mandate in a pretty substantial way when we're betting the world's infrastructure on the integrity of logins. And so to say it's okay to have like QWERTY I, uh, UIOP as your password, if your password is guarding something like whether the trains run in Europe or whether, you know, lights come on in Minnesota in the winter, right?Alex Weinert:Whether the heaters can come on, like, these are bigger deals than somebody like intercepting a personal mail from the days of bulletin boards. Right? So I think we have to, we have to say, we, we have a mandate to get past the password. So I believe very strongly that yes, our goal here is to find ways that are, that, that are in line with our expectations, for security, for the kinds of systems we're securing now.Alex Weinert:The second thing I will say is that, okay, so it's a long tail. The mitigation for passwords is MFA, right? The mitigation is multifactor auth. And as much as I would say your best bet for multi-factor auth today is probably the, the ma-, the authenticator app where you're doing cryptographic communications and, you know, you have all sorts of other hardening, any multi-factor auth at all of any kind dramatically reduces your risk of compromise, like really dramatically, like more than 99.9%.Alex Weinert:So when we go look at the body of compromised logins that we have, we'd say, "All right, here's all log-ins that we definitively said these were bad, right? These were cases where an attacker got in," only one in 10,000 of those will be a non or will be an MFA'd account. Okay? So that, that's how like radical this is. So if I go look at all my compromised accounts, all the compromise that happens in the system, only one in 10,000 of those will have MFA.Nic Fillingham:And therefore, if you have MFA-enabled, you are protecting yourself from ...Alex Weinert:Vastly, vastly. Right? Like, and even targeted accounts, targeted attacks very often are defeated by conventional MFA. Because as much as we would rather ... Like when we, if you look at something like the radio intercept stuff I write about in the Hang Up The Phone blog, we should be clear that like that radio intercept stuff is, um, it requires proximity in most cases. SS7 doesn't, but the other ones do.Alex Weinert:So if I want to intercept your cell communications, I need to get close enough to you to do it. So I have to get, you know, physically close. Well, a lot of attacks are taking place from around the world. Right? And so it's, it's hard to get close to somebody. So once I have MFA, that requires proximity, I'm going to like, "Meh, I'll give it up." You know? So as long as you're, you're not blind approving things, um, and your phone provider isn't giving away your account, right? Which is an issue. You are probably okay, you know.Alex Weinert:And you were certainly a whole lot better off in not using MFA at all. So I think we have to think of this as tiers. Like password-only is the worst. Password p-, plus MFA is, with, with phones is the next. It's much, much, much better. Right? And then we would say password plus MFA with non-phone mechanisms is the one after that. And then we would go from there to say, "Okay, let's go passwordless with, you know, pho-, with the phone authenticator.Alex Weinert:And to be clear, I'm talking about an application, not the, not SMS, right? Or Windows Hello or FIDO. Like now you're into the brass ring neighborhood. You're like, you're doing as good as you can possibly do.Natalia Godyla:Understandably, Alex, we still have a lot of work with securing the institutions and enterprises. As you said, uh, organizations like utilities still need to adopt passwordless, but what's next after passwordless? Let's say everyone goes passwordless. What is the remit for your team? What are you going to focus on?Alex Weinert:On my tie, uh-Natalia Godyla:(laughs).Alex Weinert:(laughs).Nic Fillingham:More, more bass guitars. More, uh, more music recording?Alex Weinert:Yeah. More bass guitars in a warmer climate. Yeah. The, um ... No, I think ... So there are a couple of inevitable places that attackers will be forced to move, um, once, once we get to secure authentication for users. So if everyone was using ... Let's be very clear. If everyone was using MFA, we would see a big surge in, uh, MFA phishing. Right? We'd see more, uh, Modlishka style attacks, like I talked about before.Alex Weinert:Um, if we get everybody to FIDO and we say, "Okay, now it's impossible to forge a token," then what we have to look at is token theft, which is where an attacker is trying to get into your box as a system, as system memory, lift the token out and take it somewhere else. Um, so for that reason, we're investing very heavily in proof of possession token binding, and, uh, trying to make that an impossible thing to do.Alex Weinert:So I think that the key things here, as we, as we think forward become things that are less user-centric in nature. Like we ha-, once we get users using the right kind of credentials, then we shift into the underlying systems to really harden against, you know, malware attacks, token theft attacks, um, and other things that are very nuanced and, and require a conversation between all the components to get right.Natalia Godyla:Thank you. Thank you for that look-ahead and for joining us on the podcast today, Alex.Alex Weinert:Thanks a lot. It was really fun.Nic Fillingham:I'm gonna go change my password from QWERTYUIOP on my Hotmail account. That's probably out of date now.Alex Weinert:Right. And add MFA while you're on it. Well, your, your Hotmail account has MFA, but (laughs).Nic Fillingham:Perfect. Thanks Alex. We'd love to see you again on a future episode of Security Unlocked.Alex Weinert:All right. And we'll have to talk bases again some other time.Nic Fillingham:Definitely. Thank you.Alex Weinert:(laughing), all right, see you.Natalia Godyla:Well, we had a great time unlocking insights into security from research to artificial intelligence. Keep an eye out for our next episode.Nic Fillingham:And don't forget to tweet us, @msftsecurity, or email us at firstname.lastname@example.org with topics you'd like to hear on a future episode. Until then, stay safe ...Natalia Godyla:Stay secure.
Under the Hood: Ensuring Firmware Integrity
Tracking Nation State Actors
Watchdogs in tow,hostsNic Fillingham andNatalia Godylaarejoined by guest RandyTreit, Principal Security Leader at Microsoft,toexaminethe process ofidentifyingthe source of athreatand stopping the spreadbyprotecting“patient zero.”Randyhas a fewkeytricks up his sleeve as a defender, butyoucan decideifthey’remoreimpressivethan theantics he and his identical twinhave pulled while working at Microsoft.In the second segment,Jeremy Dallman,Principal Program Manager at Microsoft,discusses why some bad actors are known in the security world under some of the most seemingly harmless codenames, such as “Fancy Bear” and “Charming Kitten”, and highlights the techniques his team is using to protect Microsoft’s customers from Nation-State actors.In This Episode, You Will Learn: • How Microsoft is defending and protecting patient zero• The history of Defender andantimalware • The processoffinding gaps inprotections • The importance of protecting customers from Nation-State actors • How and why security vendors use codenames to refer to threat activitygroupsSome Questions We Ask:• What is different about focusing on patient zero than other aspects ofsecurity?• How does Microsoft measure the false positive rate in protecting patient zero?• What tools are being used on a day-to-day basis in defender security?• Why does Microsoft partner with the industry to identify Nation-State actors?• How many groups are utilizing AI and MLto enhance their ability to become a threat?ResourcesMicrosoft Digital Defense Report:https://www.microsoft.com/en-us/security/business/security-intelligence-reportRandy’s LinkedInhttps://www.linkedin.com/in/rtreit/Jeremy’s LinkedInhttps://www.linkedin.com/in/jeremydallman/Nic’s LinkedInhttps://www.linkedin.com/in/nicfill/Natalia’s LinkedInhttps://www.linkedin.com/in/nataliagodyla/Microsoft Security Blog:https://www.microsoft.com/security/blog/Transcript(Full transcript can be found at https://aka.ms/SecurityUnlockedEp10)Nic Fillingham: Hello, and welcome to Security Unlocked, a new podcast from Microsoft, where we unlock insights from the latest in news and research from across Microsoft security engineering and operations teams. I'm Nic Fillingham. Natalia Godyla: And I'm Natalia Godyla. In each episode, we'll discuss the latest stories from Microsoft security, deep dive into the newest threat intel, research and data science. Nic Fillingham: And profile some of the fascinating people working on artificial intelligence in Microsoft security. If you enjoy the podcast, have a request for a topic you'd like covered or have some feedback on how we can make the podcast better. Natalia Godyla: Please contact us at securityunlockedatmicrosoft.com or via Microsoft Security on Twitter. We'd love to hear from you. Hey Nic, how's it going? Nic Fillingham: Hello, Natalia. It's going well, thank you. Welcome to episode 10 double digits. It feels like a milestone. That's a milestone, right? Natalia Godyla: Heck, yes. I think we were proud of ourselves after episode two. So I feel like this feels a little bit more legitimate, a good start to 2021. Nic Fillingham: Great start to 2021. But we were talking, just before we started recording and there is some sad news. Natalia Godyla: Okay. So to listeners that had heard and loved our story about the Somerville Turkey, of course. The Somerville Turkey is no longer, so the Somerville residents had fed the turkey and the turkey became aggressive as a result. And it is no longer a hallmark of our city. Nic Fillingham: The problem was they fed the turkey pure creatin, that was the issue and Red Bull. Natalia Godyla: They didn't publish that in the news story, they're trying to keep that hash, hash. Nic Fillingham: That's why it got aggressive. But no, if you have no idea what we're talking about on our Thanksgiving episode, Natalia told us about a famous turkey in Boston that has a name and it's got an Instagram page or something like that, but unfortunately it's no more, it's pretty sad. Natalia Godyla: Now that the turkey is no longer, maybe we should memorialize it. Nic Fillingham: Ooh, so you're thinking we could potentially adopt the Somerville Turkey as our Security Unlocked mascot. Maybe we could create some kind of small statues, some kind of plush toy, is that where you're going? Natalia Godyla: For some reason, my immediate image was a butter sculpting contest, in which we sculpted butter sculptures of the turkey. Nic Fillingham: Hang on, what? So, I had said as a mascot and something, I think I said the word swag, at least it was in my brain. So something we could send to listeners, and so I just immediately jumped to the logistics of how do you send butter through the US Postal Service in an intricate shape, like that of a turkey? Natalia Godyla: Yeah. I don't think you should be taking my suggestions quite so realistically, I mean- Nic Fillingham: If we had to choose though, between memorializing the Somerville Turkey and our previous plan which was the mighty alpaca as our animal mascot, where are you leaning? Natalia Godyla: Alpaca. Nic Fillingham: Can we justify that from a security perspective? Is there any security link whatsoever from either a turkey, Somerville Turkey or an alpaca? What are you looking up? You're looking up something right now. Natalia Godyla: I'm looking up facts about alpacas because I have to be honest, this is purely on level of cuteness for me. Nic Fillingham: Okay. So our Executive Producer, Bruce Bracken has just chimed in saying that god llamas and god alpacas are a thing. So it says here that a god llama, alpaca or hybrid can be used in farming to protect sheep, goats, hens, or other livestock from coyotes, dogs, foxes, and other predators. Ladies and gentlemen, we have a winner. We now have a solid link from the alpaca to security. Well done everybody, congratulations, mission accomplished, we can go home now. All right, beautiful. Natalia Godyla: On a minimum, we can talk about our next episode. Nic Fillingham: Absolutely. All right, so let's table that. We've decided it is going to be the alpaca because the alpaca can be employed as a rudimentary guardian of livestock. But speaking of the podcast, on today's episode, first up we have Jeremy Dallman joining us from the MSTIC Group. I'm not going to explain what MSTIC stands for because Jeremy will talk about it. And it's a great start to the conversation. Jeremy is coming on to talk to us about the nation-state section or chapter in the Microsoft Digital Defense Report, the MDDR, this is the third of five conversations that we're going to be having on Security Unlocked, where we deep dive into some of the topics covered in that report. Nic Fillingham: This is also I think, the first time that the MSTIC team have compiled a lot of their nation-state tracking activity over a sort of 12 month period into a single report. So first of all, it's a great read, make sure you download the report, aka.ms/digitaldefense. And then, it's a great conversation with Jeremy who really helps us sort of understand some of the core principles and ideas around sort of why is Microsoft in this space, and then sort of what does Microsoft do with tracking nation-state actors. And then after Jeremy, we talk to- Natalia Godyla: Randy Treit, a Principal Security Researcher at Microsoft, a long time employee at Microsoft who has seen a lot of different groups and brings that expertise to his security team today. So we're talking to him about his path to security and he is another security professional who doesn't have a formal or standard path to security. So he doesn't have a formal education. And I think it's a good testament to the fact that so many security folks are autodidactic and just have a love of technology and find themselves continuously passionate and interested in it, and eventually get to do their passion for a job. Nic Fillingham: On with the pod? Natalia Godyla: On with the pod. Nic Fillingham: Jeremy Dallman, welcome to the Security Unlocked podcast. How are you doing?Jeremy Dallman: I'm doing great guys. Thanks for having me. Nic Fillingham: Thank you so much for coming on the podcast. This is one of several conversations we're going to have with folks that have contributed to the Microsoft Digital Defense Report that was released in September of 2020. Jeremy, thanks for coming on. You're going to talk to us about chapter two, which is the chapter that talks about nation-state threats. This is going to be a fascinating conversation. I'm really, really interested and excited to hear what you've got to tell us. But can we just start a little bit with, who are you? What's your job? What do you do at Microsoft? What does your day-to-day look like?Jeremy Dallman: Sure. So let's see, in Microsoft terms, I'm a Principal Program Manager, in the Microsoft Threat Intelligence Center. We call ourselves MSTIC. So I'll probably use that term off and on throughout the conversation, it's much easier to say it than Microsoft Threat Intelligence Center. As a Program Manager in MSTIC, I am responsible for, let's see, directing a large number of projects that kind of span incubation and driving threat intelligence initiatives, both in MSTIC and across Microsoft.Jeremy Dallman: I do things around building and creating strong collaboration partnerships across the security industry, because malicious actors, like nation-state actors, don't just target Microsoft. I also work on sourcing the best possible tooling for our analyst and managing all of our public facing messaging around MSTIC and the threats that we track. So I guess in general, my role is always looking for ways to improve how MSTIC protects our customers, making sure that the analysts are successful and effective at hunting. And making sure that MSTIC knowledge outside the company is communicated effectively to protect our customers and enable better protections across the ecosystem. Nic Fillingham:I have ask, is MSTIC a backronym? Did you guys get in a room and say, "How can we come up with the coolest acronym in the company, and then make it work for what we do?"Jeremy Dallman: There's actually a couple of others I think, that are cooler, as well though. Nonetheless, no, our GM is notorious for let's just say, obscure acronyms that translate into words. So it took a little bit of effort, it took a little bit of time, but we came up with Microsoft Threat Intelligence Center and M-S-T-I-C pronounced as MSTIC. So we worked through a few other variations, but I think this was the best one that came out and it seems to have stuck. Nic Fillingham: I think there needs to be an offshoot team for analytics and learning at the end. Does anyone get that-Jeremy Dallman: Yes, Nic. Yes, yeah. Nic Fillingham: Okay, good.Jeremy Dallman: I know a couple of people on the analytical side that might actually run with that, I might have to jot a note down. Nic Fillingham: There you go, you can have that one for free, no royalties from me, that's fine. Natalia Godyla: The next one's charged, though. Nic Fillingham: The next one's not free, this first one's free. So Jeremy, you're going to walk us through chapter two, the nation-state threats, it's a pretty lengthy section of the MDDR. It's also, I think, correct me here, this is the first time that we've done sort of an annual wrap-up of what Microsoft has seen on the nation-state space. I think obviously, we've had lots of blog posts and activity over the many years on the activity, that we've seen and sort of how we've contributed to it. But previous sort of security intelligence reports didn't really include a lot of nation-state activity. I mean, correct me if I'm wrong here, but is this sort of the first time that we've done an annual look back at what happened in the nation-state space?Jeremy Dallman: Historically, our team hasn't been very publicly outspoken and we haven't really, historically didn't spend a lot of time talking about what we've done externally. So this is definitely unprecedented and something that's brand new for our team. It's kind of along the lines of what we've been doing over the last couple of years, talking a little bit more publicly about threat actors and such. So I think this is a fantastic roll up in view of what we do. I think it goes along with our expansion of MSTIC as an organization and kind of what we've been trying to do, informing our products and customers more broadly. Natalia Godyla: So Jeremy, why does Microsoft do this work? Why do we partner with the industry to identify nation-state actors?Jeremy Dallman: Sure. I think the short version is that Microsoft customers using our products are often the target of nation-state actors. And those customers expect Microsoft security products and Microsoft to help protect them from those threats. So MSTIC tracks nation-state activities to protect our platforms, to protect our services and protect our customers from those more sophisticated threats. Nic Fillingham: So, Jeremy, I've got the report open here in front of me and for those playing along at home, you can download the report. It's the Microsoft Digital Defense Report @ aka.ms/digitaldefense. And if you scroll down to page 44, there is a really interesting sort of graphic here. It says, "The sample of nation-state actors and their activities." And there's a bunch of what look like sort of chemistry symbols from sort of the periodic table of elements with a lot of chemistry names and symbols. And then there's some sort of other things as well. Can you sort of walk us through, what are we looking at here? Is this actual sort of nation-state actors and sort of how they're referred to? And the names that are being used to refer to them?Jeremy Dallman: Across the security industry, a number of different security vendors use different code names to refer to sets of activity that are tied to certain actors or sets of activity groups. So we use code names because we can't always necessarily tie that to a specific country, or we may want to do attribution. Other security vendors will use kittens and tigers and bears, some use numbers and a variety of different code names. And at Microsoft and in MSTIC, when we were trying to figure out how we were going to do code names, we tried a bunch of different things. I think initially, there was some use of dinosaur names, that got fairly complicated and hard to pronounce fairly quickly. I think we played around with a bunch of other things. At one point, I recall we were looking at flavors on the beer flavor wheel, I'm not sure there was enough of them.Jeremy Dallman:So we played around with this a little bit and we ended up basically at periodic table of elements because there's not really a licensing violation there, so we didn't need to worry about that. And there was plenty of them and they were fairly unique. So we code name our actors by elements in the periodic table. And we will name an actor, an element, once we understand that actor has a unique set of activity. But on that page 44 in the report is a summary of a few of our key activity groups via their element names. And largely focusing on the four regional sets of actors that we, and most threat intelligence teams will focus on, Iran, China, North Korea, Russia. Nic Fillingham: And is there any sort of logic to the particular element that's chosen? I mean, I noticed that there's no hydrogen, there's no oxygen. Well, they seem to be up towards the top end of the periodic table. I've never even heard of-Jeremy Dallman: Yttrium? Nic Fillingham: Yttrium? Did Kanye West come up with that one? What's that?Jeremy Dallman: No, it's kind of funny because we actually have an individual on our team over in our UK office. She's responsible, she's our librarian, is kind of the role that she plays and she is responsible for naming. So I don't think there's any specific logic or pattern to who gets what name. I don't even know if our analysts have a say in picking any of the names, but our librarian is the person who basically gives these names out. And I don't think she has any set structure or method for picking the names. Nic Fillingham: I was really hoping you were going to say there was a periodic table of elements stapled to the wall, and then you had to start with dots. Natalia Godyla: Somehow, I knew I was going to be dots.Jeremy Dallman: You know what? I honestly would not be surprised if that was actually the case, but I can't verify that. Nic Fillingham: All right. Well, that's for another episode of the podcast for us to follow up on. Natalia Godyla: So can you provide a little bit more context on the players? What do we know about them? Their motivations? Infrastructure?Jeremy Dallman: Sure. So a number of these actors are pretty well known. When you talk about kind of the more popular, more widely discussed actors, it's kind of hard to not fairly rapidly, get to Strontium, which others refer to as APT28 or Fancy Bear. And this is an actor set that we believe originates in Russia. Jeremy Dallman: This is someone that we've... an activity set that we've talked about fairly extensively over the years of public discussion around these actors. Whether targeting individuals or campaigns or entities involved with politics. So they're probably the more well known out of Russia. I'll just kind of hit a couple in each one of these here.Jeremy Dallman: Phosphorus, which is an actor set that we believe is originating from Iran, also known as APT 35 and Charming Kitten. They're well known for targeting government defense industrial, especially in the region, in the Middle Eastern region. Especially fond of targeting personal email accounts and going after personal email accounts as a way to gain access to systems that they're targeting or individuals and surveil individuals. A lot of activity there tied to sanctions and research around policy, that sort of thing.Jeremy Dallman: In China, we have actors that more broadly, I would say are more likely to use more sophisticated technical solutions. Trying to bypass or using more sophisticated malware, but technology, supply chain targeting, targeting education and medical research. Actors like Barium known as APT 41. Manganese, which will often target communication infrastructure. They'll even go after things like satellite or defense industry or GPS navigation.Jeremy Dallman: And then North Korea actors like Thallium and Zinc. We'll see them targeting human rights organizations and surveilling human rights organizations that might be involved in their region geographically. But we'll also see them often targeting think tanks and governments that are involved in sanctions or policy decision-making that might be tied to the Korean peninsula. Nic Fillingham: Why is Strontium a nation state actor and not simply just a sort of independent group of baddies?Jeremy Dallman: No, that's a great question. I think the simple definition of a nation state activity group is we defined it as cyber threat activity that originates in a particular country with an intent to further national interests. So because that activity fits that parameter, there's an assumption that it's more well-funded, potentially more sophisticated. And they'll more likely going to be using what we call advanced persistent threats which is an adversary that possesses a sophisticated level of expertise and significant resources that allow it to achieve its objectives using a lot of different attack vectors. It's a combination of expertise and significant resources, adequate funding to achieve specific objectives in a particular country with intent to further the national interests. Natalia Godyla: And what about attack techniques? So you hinted at that in your definition. So what are some commonalities or patterns that you can identify across nation state actors that differentiate them from other threat actors?Jeremy Dallman: So when you think about nation state actors, and I would say in most of our threats even outside of nation state actors, you're going to see most threats start with email. I think there was a blog post we put out not too long ago that said 95% of threats start with email. Start with an email lure. From a nation state actor perspective, that's largely a technique to achieve reconnaissance. To find out or identify who the people are that they need to target to achieve the objective that they're trying to achieve. So they will do things like password spray techniques to attempt to guess log in passwords for a number of accounts tied to a specific organization that they're trying to target. They will do brute force login attempts, trying to guess the passwords and try to brute force their way into an organization. That early reconnaissance technique allows them to establish an initial foothold into an organization and also then harvest credentials.Jeremy Dallman: So if they can start guessing passwords and they can understand what those passwords might be, they can harvest those credentials, store those credentials and then use those in future operations to come back into that network and execute whatever operation or mission they might be trying to achieve. Once they've actually established in there, and often as a way to get a foothold into a network, they'll use malware. Malware is a very common method by nation state actors. And I would say some actors on the nation state side, because of the excessive funding that they have at their disposal, they will go above and beyond in building up particularly sophisticated malware techniques to bypass common detections by security vendors and some networks. So that's constantly a game that we're playing to understand these malware techniques. We'll also see nation state actor using very sophisticated and personalized lures.Jeremy Dallman: They will spend a significant amount of time. And this is something we just blogged about a couple of weeks ago, an actor named Phosphorus, which originates in Iran. We're actually using building rapport and building relationships with individuals that are tied to international policy. And by building that rapport with those people, they were actually able to send them invitations masquerading as the Munich security conference, which is a prominent international policy conference. Masquerading as the conference and trying to lure that person to their fake invitation so that they could steal their credentials. A little bit of social engineering happening there. But a nation state actor is going to have the resources and funding at their disposal to be able to build out those more sophisticated techniques. And then finally, I would say there's a lot of nation state actors that spend a significant amount of time building out capabilities, relying on common weaknesses.Jeremy Dallman: So when a new patch goes out, patching a security flaw within a Microsoft product, for example. A lot of actors will reverse engineer that flaw. Better understand it then use it to weaponize a new exploit. Which is why it's exceptionally important for customers to patch as quickly as they can to avoid that weakness that Microsoft is attempting to patch. That weakness becoming an entry point for a malicious actor because nation state actors will move rapidly to take advantage of that and then attempt to exploit those weaknesses where they can. So that's a couple of techniques that I would say, like I said, we dive a little bit more into in the report. But there's more in there, especially things like web shell based attacks, which we see increasing, but I'll let you go read that into the report. Natalia Godyla: Yes. Nice teaser for our audience. One interesting point made in the nation state section of the MDDR was the downstream effect. So if I understand it correctly, the nation states will pursue these techniques and then eventually other actors will pick them up. So how does that happen if they are these sophisticated groups that are leveraging, like you said, more complicated malware? Is it that the other attackers use simplified versions of it, or as it's in the wild they get more exposure and are educated on that strain of malware and then are able to use it? So what does the process look like from nation state actor using these attack types to another attacker in the wild?Jeremy Dallman: Yeah, I think you nailed it there with the second example you gave. Because that's typically what happens is once this exploit gets out in the wild it's not just Microsoft watching for these more sophisticated threats. All of the other actors out there, whether they're criminal organizations or individual hackers, whoever it might be. There's a whole ecosystem of people out there that are watching for these threats to evolve and looking for new techniques. So when a nation state actor might have a particularly sophisticated attack that goes out, there's any number of people who will pick up and discover that through various security researchers in the ecosystem. And then they will immediately go do exactly what we do, which is reverse engineer that, understand how it works. And then you'll see variants come out. You look at things like the VPN exploits that came out in mid 2019.Jeremy Dallman: Those VPN exploits were picked up and used by an actor that we call Manganese to steal credentials and gain access to victim networks, using VPN infrastructure and holes in unpatched systems on VPN networks. So when you think about a world, the world we live in right now, where everybody's working remote. And global enterprise IT departments are relying on VPNs to improve connectivity and security for their systems. If that VPN infrastructure is not updated in its patching, actors like Manganese were taking advantage of that patch, reverse engineering it, and then going out to find VPN infrastructure that hadn't been patched and then exploiting it to gain access to those networks. Well, what we've seen subsequently is everybody else saw the technique and realized, hey, VPN, everybody's using those right now. And they started taking that and tweaking the same technique. And now those exploits have become, unfortunately become fairly commonplace. Nic Fillingham: Jeremy, you said that one of the characteristics of a nation state group is the sophistication in their techniques. And so I sort of have to ask, do we know if many of these groups, any of these groups are utilizing AI machine learning? If so, how?Jeremy Dallman: We don't have conclusive evidence I don't think. I mean, short of us walking into their infrastructure and taking pictures of systems, which isn't something we do. But I think there's enough- Nic Fillingham: Why not?Jeremy Dallman: ... indicators. Nic Fillingham: That sounds like a great idea. I'd make that a priority.Jeremy Dallman: That would definitely make our jobs a lot more interesting. I would say that we've seen indication of nation state actors starting to take advantage of whether it's machine learning or AI. It's unclear. They're starting to take advantage of more sophisticated techniques in those directions. When you think about a password spray campaign, where you are trying to attempt to guess the passwords for a number of different accounts across one organization, that takes a certain amount of compute, a certain amount of effort and a certain amount of automation that can be enabled. But if you take that and you expand it into something like we blogged about from Strontium in September, for example. We saw Strontium attempting to password spray a number of organizations, and they were spearfishing hundreds of organizations with thousands of password guesses in very short periods of time.Jeremy Dallman: And then on top of that they were using thousands of IP addresses and anonymization platforms to obfuscate their activity. So when you think about the complexity of that operation and the speed at which they were able to execute it, it would make sense that actors like that are starting to take advantage of machine learning or some automation capabilities on the backend to increase the speed, the effectiveness and the scope of their operations. Natalia Godyla: I think all of this is leading up to what is Microsoft doing? So how are we disrupting nation state threats today?Jeremy Dallman: So we do a number of different things. I would say probably the best and most effective way is using Microsoft's voice to raise awareness of these activities. And that comes in a number of different ways. We have the blog posts that we put out. The Microsoft On The Issues blog puts on a lot of interesting content that's derived from MSTIC research. And what that does is it kind of helps drive that broad discussion around what can be done to combat malicious nation state activity against governments, academia, social organizations, individuals. A lot of nation states like to target your personal email accounts, but we still defend those private email accounts because whether it's Outlook or a personal email account, that's something that we also have to protect our customers who might be getting attacked through that type of a vector. I would say probably one of the more interesting ways has been on the legal side.Jeremy Dallman: So one of our unique ways to target nation state actors has been partnering with our colleagues in the Digital Crimes Unit here at Microsoft. And the Digital Crimes Unit is responsible for pulling together a lot of the evidentiary information and understanding the threats for a legal perspective. And then they take that to courts and use litigation to seize domains and other assets that are being used by these nation state actors. And then actually through legal action shutting down those attack vectors. And then from time to time, we'll also, if we have sufficient information to warrant one time action to delete or shut down infrastructure or assets that are associated with the nation state actor. We'll also take those proactive measures against that infrastructure to basically eliminate visibility or capability on an actor and forcing them to go rebuild that infrastructure. They will typically rollover infrastructure and start rebuilding and come back later.Jeremy Dallman: So that's not necessarily a whack-a-mole game we want to get into in a lot of cases, but if it's for the protection of our customers, or if we feel it's particularly effective, that is something that we'll do as well. So that's a variety of a few ways. Obviously the one that I didn't touch on is probably the most obvious one, is leveraging our own technology and using all the knowledge that mystic collects about these threats, these actors, their tactics, their techniques and translating those into detections. Transforming and putting those into blocks and protections that show up in our security products and protect our customers in their environments. And the whole objective there has always been to make sure that we're implementing relevant, accurate and actionable threat intelligence for our customers. Nic Fillingham: Where can folks go apart from reading the MDDR? Where can they go for more information on how to protect themselves against a nation state attacks if they find themselves in one of these targeted industries?Jeremy Dallman: So we don't have a MSTIC page. I would say in the MDDR, Jeremy Dallman:We definitely have a section at the end of the Nation-States Reference called comprehensive protections required and it walks through to defensive positions that you can take, the strategies that you can enable there. And then at the end of the digital defense report, we have what are called actionable learnings. And I would recommend you go there and dive into that section as well. And every time MSTIC puts out a blog post, we will always have something at the bottom that are generalized recommendations also. So if we put out a technical blog posts that walks through the techniques of gadolinium or strontium, we will always have at the bottom the specific techniques for that threat that would help you mitigate or protect yourself from that threat. So always watch for those blog posts and then probably for the digital defense report. Go out and look at the actionable learnings. That's probably the best place to start. Nic Fillingham: Hey, Jeremy. Thank you so much for your time. This has been a fascinating conversation. We've really only scratched the surface of that nation-state threat section of the MDDR report. So if you enjoyed this conversation, would like to learn more head to aka.ms/digitaldefense and download the report, and there's lots more detail and lots more articles linked too, that you can read to learn more about this space. Jeremy Dallman, thank you so much.Jeremy Dallman: This was fun. Thanks for having me guys. Natalia Godyla: And now let's meet an expert in the Microsoft security team to learn more about the diverse backgrounds and experiences of the humans creating AI and tech at Microsoft. Today we are joined by Randy Treit. Thank you, Randy, for being here.Randy Treit:I'm happy to be here. Thanks for having me. Natalia Godyla: Great. Well, let's kick things off by chatting a little bit about what you do. So what's your role at Microsoft? What does your day to day look like?Randy Treit: My title is principal security researcher. I'm on the Defender endpoint team. So focused mainly on detecting new threats that we haven't seen before. Protecting patient zero is a big focus of mine. Recently I've started looking into some new kinds of attacks using OAuth phishing. So that's sort of my current main focus area, but I've done a lot in the cloud protection. I've been on the team forever. So I've worn a lot of hats and done a lot of roles. Natalia Godyla: So what were some of the other roles that you've been at at Microsoft? What was the first one that brought you to Microsoft?Randy Treit: I've been at Microsoft 20 years. I started in the exchange team and worked on some mobility stuff. But pretty quickly... So I started in 2000. In 2003, I joined the antivirus team, which was brand new at Microsoft. Really Microsoft's first foray into trying to get serious about the antivirus space. And I joined as a program manager, actually. So security research is a fairly new role for me, but was basically worked on the backend infrastructure for the antivirus platform in the early days. And that was the days of worms running rampant everywhere you had SQL Slammer, MSBlast, Sasser worm, Code Red, Nimda. All the greatest hits of when security was a very dark, dark time at Microsoft. And that's when I started and then have done a ton of stuff since then. So I worked on the antivirus engine as a PM and from the engineering side. Eventually moved on to do a lot of work with our cloud protection system in the last period. And then, about two years ago, I guess I moved from engineering side into security research. Natalia Godyla: So were you sold on security after being part of the AV team? Was that what did it for you?Randy Treit: Our customers, Microsoft's reputation, friends and family, everybody was just getting hammered by security threats at the time. And I really wanted to do something about that. Working on exchange was fascinating from a technical perspective, but getting into the security space where there was a real opportunity to go to battle against the bad guys and try and really protect. I'm sure we all, back in those days, this is mid-2000s, early 2000s, had friends and family who got hit by a worm or a virus or a scam. And so it was very motivating for me to get into a place where I could do something about that. And that's sort of driven me ever since. And I've done a few other forays into some stuff, like I took a break from security for about two years. Around 2012, went and worked on Xbox for the Xbox One when that was getting released and learned a ton about services. And that was a good break, but I couldn't stay away from the security space. Nic Fillingham: Randy, I'd love to come back to that first gig of yours working in the anti-malware space. So for whatever reason, I actually went down a rabbit hole recently trying to better understand the history of Defender. It sounds like you were there at its sort of inception. My understanding is that the first anti-malware, antivirus client, first of all, it wasn't built into the OS. It was a download. And was it something that we built in-house or was it an acquisition? Was it a combination? Do you know the history? Were you there for that?Randy Treit: Yeah. So I was the third PM hired into the antivirus team and it was right after the decision to acquire RAV from a Romanian company called Gecad. And so I started on a Monday and on Wednesday all of the Romanian developers showed up, many who are still on the team today. Marty Marinescu, who was the lead developer of the engine, is still the lead architect on the antivirus engine. And I remember, it was an interesting cultural experience, because they all came in and the custom in Romania was that you would, every morning, go to everybody's office and shake their hand and greet them in the morning. And so that was- Nic Fillingham: That's awesome!Randy Treit: Yeah, it was great. Unfortunately they, I think, became acclimatized to the not as polite American way of doing things. That sort of died out after a few weeks. But yeah, it was an acquisition and we didn't actually know what we were going to do with it at the time. So there was always a desire bring the protection capability into the operating system, but that's a big rock to lift and eventually we got there with Defender in the interim. It started out as, like you said, a download. So the initial... For years we've had the malicious software removal tool that comes out every patch Tuesday and runs on everybody's machine to clean up the ecosystem of malware.Randy Treit: But before that it was actually the very first release of the same engine that runs in Defender today, was something called Blast Clean. It was a Blaster removal tool to remove the Blaster worm. And we released that in late 2004. I have some stories about testing it out on my home machine and actually infecting it. And my kids not being able to play Magic School Bus the next day, and getting a call at the office. So those were fun times. Nic Fillingham: Can you elaborate on that? Is that the story? Is there more to it?Randy Treit: So what happened was the Blaster worm, there was a particular patch that if you weren't patched, it would infect your computer within a few seconds of being online. And so we had the early builds... This was December, heading into Christmas season in 2004. And I decided, well, I've got my computer at home. I'll just uninstall the patch and let it get infected. And then I will run our removal tool and make sure that it works. It was not the brightest thing to do. Don't do this at home kind of thing. I was younger and more eager to just do crazy stuff that I would probably be a little more careful these days, but I did it. I uninstalled the patch. The machine got infected. Rebooted, which was part of the infection.Randy Treit: And then it came up and I ran our removal tool and it worked great and then I decided to try it again. So for those who may remember the Blaster worm, there was another worm called Nachi that somebody else had written and released, exploiting the same vulnerability. And Nachi tried to remove Blaster and then patch your computer. And so our tool removed both of those. And what happened, in my case, was the machine got infected with Nachi, but it was a copy of the Nachi worm, that had itself been infected with a file infecting virus, which infected all the executables is on my machine and then basically bricked it and made it so it wouldn't boot. Nic Fillingham: I know that I got infected with Blaster worm. I couldn't remember that because I got in big trouble from my dad.Randy Treit: Oh, yeah. Nic Fillingham:But I sort of can't remember what it did. I know that it stopped... No one could use the computer. It just completely... The computer was unusable, but can you just kind of bring us down memory lane? If you were infected by Blaster worm, what actually happened?Randy Treit: It was not a worm that was exfiltrating data off your machine. Now it's all about money and these crime groups trying to exploit the ecosystem with Ransomware and that kind of thing. It was really just designed to spread. So it was purely, as I recall and if I'm remembering correctly, but it would just try and infect... It would infect your machine and your machine should actually be able to run with the infection. Although like in my case, and maybe in yours, if it got infected with a version that was itself infected with something else, it would just brick the machine. Like if there was a file infector, which is what I experienced with the Nachi worm. But essentially it would just try and spread to other machines that were unpatched, randomly spraying IP addresses trying to find another machine that had the vulnerability. Natalia Godyla: So you mentioned that, right now, part of your role is to focus on protecting patient zero. So how is that different than some of the work you've done in the past? And what's different about focusing on patient zero in specific?Randy Treit: The attackers could guarantee that they could release something into the wild that wasn't detected because it wasn't detected by current signatures. So before we had cloud protection, you just had the heuristics and signatures that were on disc in these virus definition updates that computers would download periodically. Typically, a few times a day. So you couldn't really protect patient zero because the attackers would always be able to tweak their malware until they saw from scanning with, say, the virus signatures that you weren't going to be able to detect it. And then they would release it. And then the clock starts ticking at that point. And you have a certain amount of time before, say, a customer reports that to Microsoft, or we discover that a sample from some sort of honeypot, or whatever.Randy Treit: And then now you have, okay, we need to quickly add a signature and ship that out to the customers. So the cloud has been a real game changer because it gives us an opportunity to run all these machine learning models in real time, in milliseconds to make an evaluation of a file that we've never seen before and decide that it's malicious and then block it. That has been a huge game changer in terms of protection capability and really shrinking that time to protection to milliseconds from where it used to take days and hours to get a signature out. Nic Fillingham:And how do you measure the false positive rate? If there is one, in that sort of protecting patient zero. How do you measure and then how do you find that balance between a couple of false positives, which would be, probably, annoying. But do you allow yourself a few of those to slip through in order to genuinely protect patient zero? Or are the models so good now that the false positives are extremely rare?Randy Treit: Oh, well, we're always going to have some false positives. ML is not perfect and human expert rules and human logic is not perfect. So there always will be false positives. We have certain thresholds that we try and keep our rules under, or that are basically lines in the sand that, hey, in order to release a new, say, detection rule in our cloud protection infrastructure, it has to run in an experimental period for a certain amount of time. Typically, even a few weeks while we gather all the data on what it would have blocked on, and then we can evaluate, is it having a nice, low, false, positive rate? So there are certain thresholds that we need to make sure all those rules are running under.Randy Treit: And then we have guard rails to make sure that if all of a sudden a rule or an ML model starts... Something changes under the hood and it starts having too high of a false positive rate, then we have systems to alert and automatically disable things until somebody goes and investigates and that kind of thing. So we're definitely very cognizant of trying to find that balance between blocking the bad stuff, but not causing too many false positives and causing pain and headache for our customers. Nic Fillingham: And does your team monitor those metrics? Is that what your team, as part of looking after patient zero, is that one of the things that you track day to day, or is that another part of the org?Randy Treit: Yeah, it's definitely our team. There are other kind of data science focused people who will do a lot of the infrastructure work to support running those metrics. But our team looks... That's creating the cloud rules and some of that capability. We'll work on writing watchdogs and guardrails and alerts and things like that. Just as part of the end to end pipeline of creating that protection. Nic Fillingham:What are some of those tools that you use day in, day out, Randy? When you start your day, where are you going to? Do have some sort of team dashboard, or are you going into some kind of Azure ML service? Yeah, what's in your toolbox?Randy Treit: So we definitely have our dashboards and tools that are the sort of go-to place for, oh, you want to see the trend of detections over time, and these kinds of things and monitor your rules and whatnot. I tend to go a lot deeper into the actual data. So I'm a big fan of Jupyter notebooks and pandas on Python. I've done a bunch of stuff in R, in the last couple of years. Lately I've been using Databricks notebooks, which are fantastic because it basically lets you do big data. Sorry. I don't know if you're familiar with the notebook type environment, but it's essentially a combination of marked down notes and graphs and visualizations. Nick, I know you've seen some of my heat maps that I like to generate, showing where we're seeing particular attacks happening globally.Randy Treit: That's all done in this notebook environment where you have this data under the hood. You can write Python code or R or Scala, and then, to process the data, and then not the other, it'll spit out a beautiful global heat map or graphs or data. And you can just sort of have instant querying at your fingertips. So typically, my day starts with usually firing up some kind of a notebook, pulling in some data. Randy Treit: I'm often looking for gaps, so where are we not doing well. So what did we see over the last... Let me find files that we're now blocking in the cloud, because our cloud learned that these are malicious, but maybe we miss patient zero and maybe we missed the first 25 encounters. Now, then we started blocking. Oh, let me figure out what happened there. Why didn't we block? How do we close that gap? Randy Treit: My day job, I would say, is really trying to find protection gaps where we're not doing a good job and figure out how we close them. They go actually implement something to close those gaps. I tend to work with Python mostly day-to-day in a Jupyter Notebook or more recently, these Databricks Notebook type environment. I love it. Compared to the old days of you're running just SQL queries against a small set of SQL data, the things you can do with these, I would say, data scientist type tools like Jupyter Notebooks is very freeing. I guess that's how I would put it. Nic Fillingham: Randy, what's flagging those gaps? So, you said you look for gaps. Is that just your experience, your expertise, you know what you're looking at when you see data, when you see dashboards, when you see reports; or are there a combination of processes that are specifically looking for a detection that picks something up and then went backwards in time and realized that "Oh, here are some historical detections that we actually miss"? How do you find gaps? I think that's the question. Randy Treit: It's a combination of manual spelunking on into the data and going off intuition or things I've done before, but we do have automation that will flag certain events. We have watchdogs and other rules that researchers write. In my mail inbox in the morning, often, I will have a list of these potential misses where maybe we missed detection on the first patient 0 through 10, and then we started blocking. So, I might go and look at, "Oh, let me dig into that a little bit and find out what happened there." So, in some cases, it might be that we have a malware probability threshold that we were looking forward to say from an ML model that says, "Oh, block if the probability is 0.95. So, 95% probability that this file is malware." Randy Treit: Going into the data in telemetry, I might see that we didn't block because the probability was 0.93. So, one of the things I would look into then, oh, can we reduce that probability that we're looking forward to block from that 0.95 threshold to 0.93? Maybe code up something to model that or to run for a few days in experimental audit mode and see, "Does that lower threshold still meet our false positive targets?" If that's looking good, we can turn that on live, something like that. Natalia Godyla: This is a bit of a deviation, but it would be great to understand, "What kind of context do you bring to this role from previous jobs? What were you studying in school? What did you intend to do? What were your jobs prior to Microsoft, and how do you use them in your day-to-day?" Randy Treit: Yeah, that's a great question. So, I was actually studying Philosophy in Pacific Lutheran University down in Tacoma. I'm a native Washingtonian. So, Microsoft was right in my backyard. It was basically the height of the dotcom boom and the end of the '90s. I had finished up the Philosophy Program at PLU and was planning to become a philosophy professor but needed to get a job. In the interim, I was married. We had a young child, another one on the way. So, I decided to take a break from school, get a job. I started as a technical writer actually at Microsoft on the Exchange Team. I think you talked to Emily Hacker. I listened to the interview and learned that she was also started as a technical writer. So, that was pretty cool. Randy Treit: And then worked in exchange for a few years before I got asked about joining this newly formed antivirus team. I made the jump there. I actually never finished my four-year degree. So, I made a plan with my advisor. I finished the philosophy program, but still had some general university stuff to finish up. But once I started at Microsoft, I was just off and running and never looked back. So, it's been an interesting journey. Sometimes I definitely suffer from, I would say, imposter syndrome here and there, where I spent a lot of time writing code day-to-day, but I've never been formally trained in computer science. It's all been self-taught or picked up on the job thing. Randy Treit: When I moved from a program management and the engineering side into research, I came without the deep reverse engineering background that a lot of my colleagues had. So, that was something that I felt like, "Oh, this is going to be hard for me to pick up." Sometimes that lack of a formal academic background, I feel like it was a bit of a chip on my shoulder, but I just try and do the best I can and go from there. Nic Fillingham: Talk a bit about philosophy, and then I'd love for you to talk about how and if you use it in your job today. Randy Treit:Yeah. So, I was not a good student in high school. So, I barely graduated high school with a very low GPA. So, when I decided to finally get my act together and go back to school, I started at a community college. I needed to take English 101 just as part of every college requirement. So, the English 101 class I took was a combined English 101 and Philosophy taught by two professors who were husband and wife. Debbie Kuder, the wife taught the English portion, and then her husband, John taught the Philosophy portion. It was basically an amazing class. My identical twin brother, who also works at Microsoft by the way, was in the same class with me. We both just fell in love with philosophy. Randy Treit: I think, I just love the idea of open-ended questions that had no answers. So, philosophy, I think differentiated from the sciences, it's dealing with questions that will never actually be answered, like what is beauty and what is a good argument? There's always going to be different opinions. Just the idea of these big open-ended unsolvable questions, but the people will keep getting closer and closer to the truth hopefully over time, I just fell in love with that. In terms of applying philosophy at work, I think the biggest thing that I got out of studying philosophy in undergraduate school at PLU was the rigorous approach to problem solving. So, even though you have these big open-ended problems, like I said, there probably are never going to get answered. Randy Treit: The approach of philosophical approach is very rigorous and requires incredibly good communication skills to be able to communicate your ideas effectively and, in your arguments, cogently. That, I think, has stood me in extremely good stead in my career. I think that's one of the things that I bring to the table. I think someone like Emily, you mentioned with the journalism background, it's just that ability to communicate. There's so many brilliant people who work in the technical field, but who are unfortunately not great communicators. Often, they need someone to help translate what their brilliant ideas into something that other people can actually understand what they're aiming at. Randy Treit: That's something that I think I've been able to do fairly successfully. Just that ability to really rigorously attack a problem and break it down into small components, which I think comes from some of that training I think has also done a great job or has stood being a good stead with malware analysis and threat analysis and that kind of thing. Natalia Godyla: So, I know Nic is dying for me to ask this, but you said you had an identical twin, you just dropped it in there casually that works at Microsoft. Do you guys pull pranks together. Have you done it as kids? Do you do it at Microsoft? Randy Treit: You have no idea. So, Mike actually worked on the antivirus team at the same time as I did. So, he joined Microsoft before me and has worked on NT 5, which became Windows 2000 and is a brilliant dev, but he was actually one of my devs and I was his PM working on the antivirus. This is probably mid-2000s. For a number of years, we were on the same team. And then he went off to Intune. But I mean, the amount of confusion we caused when people would walk into meetings or even just down the hall, it was quite fun. I'm sure we played some pranks. It's been great. Randy Treit: There was one time very early on, we weren't on the same team at that point, where he was in my office over an exchange. He had come over to grab a coffee. He was across the street. I had gone down to get a refill or use the restroom or something. This guy, David came in and started talking to Mike, like he was me, "Hey, Randy, I've got some questions about this thing." Mike was like, "Oh, I'm not Randy." David looked at him and just shook his head and said, "So, anyway, I've got questions. Do you know about this?" Mike's like, "No, I'm not Randy." He looked at him and he said, "wait, are you serious?" So, we've had those kinds of incidents. Randy Treit: Mike is my go-to person whenever I get stuck on a programming problem, because he's a brilliant programmer. So, I'm constantly sending him my code and saying, "Hey, I'm struggling with this." He usually responds with something like, "What is this monstrosity?", and things like that since I'm not nearly the coder that he is. Natalia Godyla: Subtle. Nic Fillingham: Who's the older twin by a fraction of a second or a minute?Randy Treit: Mike's four minutes older than I am. Nic Fillingham: I love it that your prank was actually a wholesome misunderstanding, an unintentional wholesome misunderstanding. I was typing frantically with Natalia, trying to see if there was some example, where you each went to the other's annual review and just tried to just say ludicrous things to the manager to see when they caught on, but no.Randy Treit: No, I haven't done too much of that at work. Although, I mean, in high school, he would skip class and I would go to his art class, because I had a girlfriend who was in the same class. One day, I got called up to make a presentation, the person they thought I was Mike. I was completely unprepared and I just fumbled my way through it. I learned that, "Oh, that didn't work out the way I was hoping it would." I'll throw this out there. My younger brother also works at Microsoft. He is a producer on Xbox video stuff. So, there's a bunch of us running around. Nic Fillingham: How many other Treits are there?Randy Treit: My sister, Tammy worked on Exchange at the same time I did back in the day. There are six of us Treit siblings. I guess four of us have worked at Microsoft. My younger sister is a doctor in Seattle, and my older sister is a teacher in Germany. Natalia Godyla: Thank you, Randy. We're happy to have you at Microsoft. Happy to have two-thirds of your family at Microsoft here, and we'll definitely love to have you back. Randy Treit: That was a lot of fun. I really enjoyed the conversation. Natalia Godyla:Well, we had a great time unlocking insights into security from research to artificial intelligence. Keep an eye out for our next episode. Nic Fillingham: Don't forget to tweet us, @msftsecurity, or email us at email@example.com with topics you'd like to hear on a future episode. Until then, stay safe. Natalia Godyla: Stay secure.
Unpacking the New ML Threat Matrix
Yeehaw! “Data Cowboy” is in the building. Join us as Nic Fillingham and Natalia Godyla sit down with Ram Shankar Siva Kumar, aka “Data Cowboy” at Microsoft, for an exciting conversation about the release of a new adversarial ML threat matrix created for security analysts. Have no fear, we made sure to find out how Ram acquired the name, “Data Cowboy”, so saddle up and get ready for the ride!Stick around to hear Nic and Natalia explore the urgency of surfacing threats at a faster rate with Justin Carroll, a Threat Analyst at Microsoft, and why it is more important now than ever before.In This Episode, You Will Learn: • How Microsoft is using the new ML threat matrix against cyber attacks• The approach and philosophy for putting the threat matrix on GitHub• ML applications in regard to healthcareand why it is worrisome• What needs to happen in order to be successful in combatingcertainthreats Some Questions We Ask: • What is an adversarial ML threat matrix?• How will the community on GitHub contribute to the evolution of the ML threat matrix?• What resources are available to learn about all things VM?• What techniques are being used to find threats at a faster speed?• How do AI and ML factorintothe role of managing data and collaborating with other teams?ResourcesRam’s Blog:https://www.microsoft.com/security/blog/2020/10/22/cyberattacks-against-machine-learning-systems-are-more-common-than-you-think/Microsoft Security Blog:https://www.microsoft.com/security/blog/Nic’s LinkedInhttps://www.linkedin.com/in/nicfill/Natalia’s LinkedInhttps://www.linkedin.com/in/nataliagodyla/Ram’s LinkedInhttps://www.linkedin.com/in/ram-shankar-siva-kumar-7b04a73a/Justin’s LinkedInhttps://www.linkedin.com/in/justin-carroll-20616574/Transcript(Full transcript can be found at https://aka.ms/SecurityUnlockedEp09)Nic Fillingham:Hello, and welcome to Security Unlocked. A new podcast from Microsoft, where we unlock insights from the latest in news and research from across Microsoft security engineering and operations teams. I'm Nic Fillingham.Natalia Godyla:And I'm Natalia Godyla. In each episode, we'll discuss the latest stories from Microsoft security, deep dive into the newest threat intel, research and data science.Nic Fillingham:And profile some of the fascinating people working on artificial intelligence in Microsoft security. If you enjoy the podcast, have a request for a topic you'd like covered, or have some feedback on how we can make the podcast better.Natalia Godyla:Please contact us at firstname.lastname@example.org or via Microsoft security on Twitter. We'd love to hear from you. Hi Nic. Welcome back. How were your holidays?Nic Fillingham:Yes. Thank you, Natalia. Welcome back to you as well. Mine were great. You know, normally you drive somewhere or you fly somewhere, you go visit people, but this was all the FaceTimes and the Zooms and the Skypes, staycation, but it was still nice to eat too much and drink too much over the holiday period. How about you?Natalia Godyla:Yes, it was... to quote my boss. "It was vegetative." It was definitely just... well actually you know what? I did have a big moment over the holidays. I got engaged. Nic Fillingham:Oh, what! Natalia Godyla:I know.Nic Fillingham:Congratulations. Natalia Godyla:Thanks.Nic Fillingham:That's amazing. Natalia Godyla:I feel like it was absolute relaxation, really high point during the five minute proposal. And then we went back to our natural state and just absolute relaxation, lots of video games.Nic Fillingham:Hang on. So were you both sitting on the couch, playing some switch, eating your 95th packet of Doritos, and then all of a sudden your partner pauses and says, "You want to get hitched?"Natalia Godyla:There was a little bit more pomp and circumstance to it. Though I think that would have been very fitting for us. Nic Fillingham:Wow! Good on you guys. That's awesome. Natalia Godyla:I'm sure that like us, everyone has forgotten what they were doing at work, and I'm sure also what this podcast is doing. So why don't we give everyone a after the holiday refresher?Nic Fillingham:So just before the holidays, we partnered with Petri who run the Petri.com site Thurrott.com. First Ring Daily, a bunch of other great blogs, podcasts, email newsletters, and so welcome to all our new listeners who've come to us from Petri, from Throughout from First Ring Daily. Yeah. So what is security unlocked? Well, first and foremost, Natalia, and all your co-hosts, we are Microsoft employees and we will be interviewing, and we do interview on this podcast, other Microsoft employees, but we talk about security topics that hopefully are relevant to all security professionals and those who are interested in the state of cybersecurity. Nic Fillingham:And what we'll do in each episode is the first half is we'll pick a sort of a recent ish topic and we'll speak to a subject matter expert or an author of a recent blog post and ask them about the thing that they're working on, or that they've announced in the AI and ML space, hopefully try and demystify some new terms or concepts that may be either nascent or sort of difficult to wrap one's head around. And then in the second half...Natalia Godyla:We talk to again, another Microsoft security expert, this time more focused on the individual and their path to cybersecurity. So we'll ask them about what interested them about cyber security, what compelled them to join the industry, what jobs they've had, how they've come to Microsoft or their current role. In addition, we also have a new announcement about the podcast, which is we'll be switching to a weekly cadence. So prior to this, we were bi-weekly, now more goodness coming your way.Nic Fillingham:More pod in your pod app. What is the collective receptacle for pod? What is it? More pods in your cast, more cast in your pod?Natalia Godyla:More beans in your pod.Nic Fillingham:I like that. More beans in your pod. And I think the other thing that's worth reiterating Natalia is if you have a cyber-security topic you would love to learn more about, or a perspective you'd like to hear from, please let us know, we'll go after it for you and try and bring that to a future episode.Natalia Godyla:Yes, absolutely. We're really thankful to everyone who has reached out thus far and just keep it coming.Nic Fillingham:On today's episode in the first segment, which we call our deep dive, we speak with Ram Shankar Siva Kumar, whose title I will not give away in the intro because we talk about it in the conversation. And it's an awesome one. Ram works in the Azure Trustworthy ML team. And he's here to talk to us about a blog post that Ram co-authored with Ann Johnson that announces a new adversarial ML threat matrix that has been built and published up on GitHub as a collaboration between Microsoft, MITRE, IBM, Nvidia, Bosch, a bunch of other organizations as a sort of open source approach to this upcoming sort of nascent threat category in adversarial machine learning. And it was a great conversation. And then after that, we speak with...Natalia Godyla:Justin Carroll of the Microsoft Threat Intelligence Global Engagement and Response team. He started in networking very on the ground and only got his education in cybersecurity later in his career, which I think to anybody out there, who's looking to transition to security, who has a different background in security and is wondering whether they can make it, you can. He also chats a little bit about what inspired him to join cybersecurity. Some of it came from video games, which is a theme we're seeing again and again.Natalia Godyla:So he had a unique spin on vigilantism within video games and ensuring that those who had an unfair advantage by using mods were checked and tried to level the playing field for all the rest of the players of that game. And of course we touch on Ninja Turtles, which is really the highlight of the episode. I think, with that on with the pod.Nic Fillingham:Ram Shankar Siva Kumar, thank you for joining us on Security Unlocked.Ram Shankar Siva Kumar:Hey, thanks for having me, Nick and Natalia. Really appreciate it.Nic Fillingham:So we're going to talk about a blog post that you co-authored with the wonderful Ann Johnson. The title is, it's a great title. I'll get straight to the point. Cyber attacks against machine learning systems are more common than you think. Before we get into that, though, I just have to ask, you list your title as data cowboy, which is fantastic. I would love data cowboy, anything cowboy. I would love that for my title. Could you explain to people, what does a data cowboy do and what is the Azure Trustworthy ML group?Ram Shankar Siva Kumar:Oh, totally. First of all, this is like every kid's dream is to be Woody from Toy Story. It's just like, I realize it in my own way. So when I joined Microsoft in 2013, there really wasn't an ML engineer position. So my boss was like, "You can be whatever you want. You can pick your own title." I was like, "Yes, Toy Story comes to life." So it was like, this is a brown version of this Woody that you kind of get. So basically what the Trustworthy Machine Learning group does is our promise to Microsoft is to essentially ensure we can enable engineers and customers to develop and deploy ML systems securely. So it's kind of a broad promise that we make to Microsoft and our customers.Nic Fillingham:Got it. I would love to come back to just the data cowboy one more time. Tell me what you do. I mean, I have visions of you riding around the office on a hobby horse. Lassoing errant databases. Tell us about your day to day. What does it look like?Ram Shankar Siva Kumar:Yeah. So what really happens is that, like I said, I really wish I can ride it on my office, now I am at my home and my 500 square foot apartment- definitely not recommended. But most of the time we end up doing is this wonderful Hiram Anderson who's part of our team, he's militantly looking at how we can detect attacks on machine learning systems. So really working with him and the rest of the Microsoft community to kind of keep our eyes and ears on the ground, see like what sort of attacks on machine learning systems we are seeing, our various different channels and trying to see how we can detect and respond and remediate those sort of attacks. So that's the first one big one. The second thing is like I get to work with a wonderful Will Pears. So I get to work with him to think about actively attacking red teaming Microsoft's machine learning system. So even before our attackers can look at, exploit the vulnerabilities Will and Hiram go and actively attack Microsoft ML systems.Natalia Godyla:So how does the work you do connect to the different product groups. So as you're identifying these cyber attacks, are you then partnering with our products to build those into the detections?Ram Shankar Siva Kumar:Yeah, that's a great question. So one of the things I really like about Microsoft is that super low slake to meet with somebody from another product team. So the amazing Mira Lane who heads the Azure Cognitive Services, really worked very closely with her. And I believe you ever had a Holly Stewart in your podcast as well, so worked very closely with her team. So it's really a big partnership with working with leaders from across Microsoft and kind of shopping around what we're doing and seeing how we can kind of help them and also learn from them because they also have sensors that necessarily might not have.Nic Fillingham:Let's talk about this blog post. So you and Ann both announced this really interesting sort of consortium of 11 organizations, and you're releasing an adversarial ML threat matrix. It's open source, it's on GitHub. Very exciting. Tell us about it.Ram Shankar Siva Kumar:So the goal of the adversarial ML threat matrix is essentially to empower the security analyst community so that they can start thinking about building detections and updating their response playbooks in the context of protecting ML systems. And one of the things that's kind of like we want to be mindfully different is the attacks that we see to this framework with, all these techniques, we kind of only put the ones that Microsoft and MITRE jointly vetted that were effective to be against production machine learning systems. Ram Shankar Siva Kumar:So first of all, the whole area of attacking machine learning systems goes all the way back to 2004. In fact, you can find Daniel Loud, whose Twitter handle is Dloud on Twitter today. He continues to work on this super cool fields and there's a wonderful timeline by this other researcher called Battista Bisho that he also linked to the blog, but he can basically see that this work has gotten immense academic interests for the last 16 years. And especially in the last four years after a very seminal paper was released in 2014.Ram Shankar Siva Kumar:So when a lot of people think about spiel, they think of as, oh, this is something that is really theoretical. This is something that... Oh, Great, you're working in academic setting, but no, that's not true. There are marquee companies, who've all had their ML systems subverted for fun and profit. So the whole point of this blog post with MITRE and this whole corpus of industry organizations was, this is real. Attacks on machine learning systems is real, you need to start thinking about this.Ram Shankar Siva Kumar:Gartner released a report on 2019 saying, 30% of all cyber attacks in 2022 is going to involve a tax on machine learning systems. So this is not a pie in the sky. Oh, I'll get to it when I get to it. 2022 was a year and a half, it's a year away from now. So we got together in this blog post to really empower our security analysts community and help them orient for this new threats.Natalia Godyla:Can you talk a little bit more about what exactly is the adversarial ML threat matrix and how you envision security analysts using this tool?Ram Shankar Siva Kumar:Yeah, totally. So one of the things that before we even put this matrix together, we kind of conducted a survey of 28 organizations. We spoke to everybody from SMBs to governments to large organizations and we spoke to the security analyst Persona, as well as the MLG person. I asked them, "Hey, how do you think about securing ML systems? This is a big deal. What are you doing about it?" And they were like, "Well, we don't have the tools and processes in place to actually go and fix these problems." So the first thing we realized is that we wanted the security analysts community to be introduced to adversarial ML as a field, try to condense the work that's happening in a framework that they already know. Because the last thing we want to do is to put another framework another toolkit on their head.Ram Shankar Siva Kumar:And they're just going to be like, "Nope, this is not going to work out. This is one more thing for them to learn." So we took the MITRE's attack framework. So this is something that was again, bread and butter for any security analyst today. So we took the attack framework and we kind of said, "Hey, we've been really cool." If you took all the ML attacks and put it in this framework, and that's exactly what we did. So if you look at our track matrix, it's modeled after the MITRE attack framework. Ram Shankar Siva Kumar:So the wonderful folks from MITRE's ML research team and us, we got together and we basically aligned the attacks on machine learning systems, along reconnaissance persistence, model evasion, ex-filtration. So if you look at the top of our matrix, the column headers are essentially tactics and the individual ones are techniques.Ram Shankar Siva Kumar:So let's say that an attacker wants to gain initial access to a machine learning subsystem, let's say that's her goal. So she has a couple of options to kind of execute her goal. She has a couple of techniques in her kit. The first thing is that she can just send a phishing email to an ML engineer. That's very valid. Phishing is not going to go away. The second thing that she can do is she can take a pre-trained ML model available that people generally download and she can backdoor it. So the whole point of this attack matrix is to A, build a common corpus of attack techniques and attack tactics in a framework that a security analyst already has knowledge of.Natalia Godyla:Are you seeing any trends? What's most common to combine.Ram Shankar Siva Kumar:Oh, that's a great question. So before I just step into this, I first want to tell you about this attack called model replication. So the easy way to think about this and Natalia, I will get to this, I promise. Natalia Godyla:I love the excitement. I'm so ready for it.Ram Shankar Siva Kumar:We're going to take a little detour like Virgil and Homer. So essentially the best way to think about model replication is that open AI is a very famous ML start up. And they last year released a model called GPT-2, and they said, "Hey, you know what? We're not going to release the entire model immediately. We're going to release it in a stage process." We're going to just... because we want to do our own verification and before they could release the entire model, these spunky researchers, so I love that. They're still cool. Vania Cohen. And I know this other person's name is Skylion with a O, they replicated GPT-2 it was like 1.5 billion parameter model, and they've leased it on the internet on Twitter. And they call it open GPT-2. And I love their tagline, which is GPT-2 of equal or lower value.Ram Shankar Siva Kumar:So even before the company could release, they replicated the ML model based on the data sets that were available based on the architecture. And they basically at the end of the day, and we also references our case study is that they basically tweaked an existing model to match GPT-2 and they publish that for everybody to use. No, it does not have the same accuracy or the same metrics as the original GPT-2 model. But the fact that an attacker can even replicate a ML model using publicly available data sets and having some insights about the architecture is something for people to think about.Ram Shankar Siva Kumar:So now to come back to your excellent question. So what exactly is a common pattern? So what essentially we see attackers doing is that they go interact with the machine learning system, attackers might send some data. They might get some responses back and they keep doing that enough amount of time. And they now have sufficient data to replicate the ML model. So the first step is that they go and replicate the ML model and from the ML model that they have replicated, they go do an offline attack. Because now they their own ML model, they try to evade this ML model and then they find a way to evade the ML model. And they take the examples of the test points that evade the ML model and now evade the online, the real ML that's out there taking that and then boom, fooling the real online ML model. So that's a common data point, but three case studies in our adversarial ML GitHub page that actually kind of shows this.Nic Fillingham:So the sort of takeaway from that. If your data set is public, don't make your ML architecture public and or vice versa.Ram Shankar Siva Kumar:That's a great question. And I've been thinking about this a lot, first of all, we definitely want to be transparent about the baby builder ML models, right? Marcus Sanovich, Oh gosh, he's such an amazing guy. But for the last so many years in RSA has been like militantly, been talking about how we build our ML models for security purposes, because we want to give insights into our customers about how we actually built ML models. And the data sets are machine learning as a field, it has as norms of opening up our data sets. In fact, one can attribute the entire deep learning revolution to Dr. Fei-Fei Li's image in a dataset which really sparked this whole revolution. So, I really don't want anybody to think that being open with our data sets or being open with our ML platforms is a good idea.Ram Shankar Siva Kumar:Because even if you think of traditional cyber security, right? Security by obscurity is never a good strategy. So the way we want to push people to think about is how are you thinking about detection? How are you thinking about response? How are we thinking about remediation? So really trying to take the assumed breach mindset and feeding it into your ML systems is how we want to push the field towards. So if you take away anything from this is continue to be opening your systems for scrutiny, because that's the right thing to do, that's the norms that we've set. And that's important to advance research in this field and think about detection strategies and think about, and assume breach strategies for building ML systems. Ram Shankar Siva Kumar:We wanted to distinguish between traditional attacks and attacks on ML systems. So the one thing that I want to think about is the threat matrix contains both traditional attacks and attacks on ML systems. Whereas the taxonomy only contains attacks on ML systems. The second difference is that, like I said, the matrix is meant for security analysts. This one is meant for policymakers and engineers. The third that's the more important difference is that in the context of the threat matrix, essentially we are only putting attacks that we have validated against commercial ML systems. It's not a laundry list of attacks. We're not trying to taxonomize. Nic Fillingham:I wonder if you could talk about the approach and the philosophy here for putting this on GitHub and making it open to the community. How do you hope folks will contribute? How would you like them to contribute? Ram Shankar Siva Kumar:Yeah, absolutely. So Miguel Rodriguez, who runs the MITRE, who we collaborated with, wonderful team over there before putting this out on GitHub, there was a little bot of angst, right? Because this is not fully baked product. This is something that 13 organizations found useful, but doesn't mean everybody in the community might find useful. And I think he said something to the effect of-Nic Fillingham:It's almost as if you're a cowboy.Ram Shankar Siva Kumar:Yeah. There you go, herding people. It was like, we're putting this out, acknowledging this is a first cut attempt. This is a living document. This is something that we have found useful as 13 organizations, but we really are hoping to get feedback from the community. So if you're listening to this podcast and you're excited about this, please come and contribute to this matrix. If you think there are attacks that are missing, if you would like to spotlight a case study on a commercial ML system, we are super looking to get feedback on this. Ram Shankar Siva Kumar:And we also kind of realized that we wanted a safe space almost to talk about attacks on ML systems. So we were like, you know what? We're just going to have a little Google groups. And the membership of the Google groups is extremely diverse. You've got philosophers that are interested in adversarial machine learning. We've got people who are looking from various perspectives, joining our Google groups and kind of like giving us feedback and how we can make it better.Natalia Godyla:Yeah. As you mentioned, there are tons of different perspectives coming into play here. So how do you envision the different roles within the community interacting? What do you think needs to happen for us to be successful in combating these threats?Ram Shankar Siva Kumar:Yeah. This is a great question. The one thing that I've learned is that this topic is immensely complex. It's mind boggling to wrap the different personas here. So I'll just give you a rundown, right? So, so far we know that policymakers are interested in securing ML systems because every national AI strategy out there is like, securing ML systems is top priority for them. ML engineers are thinking about this, academic researchers. There were like 2000 papers published in the last, I want to say five or six years on this topic. So they are like a hotbed of research we want to rope into. We've got security analysts from these companies that we're talking to are interested. Csos are also thinking about this because this is a new threat for them. So as a business decision maker, how should they think about this?Ram Shankar Siva Kumar:One thing that I got an opportunity with Frank Nagle, who's a professor at HBS. We wrote up piece at Harvard Business Review talking about, is it time to insure ML systems. ML systems are failing so if you're ML powered like vacuum cleaner burns a home down, what do you do about it? We try and rope in the insurers to come in participate in this. So, Natalia this is such a green field and the only way we're going to like get ahead to really get people excited and try for clarity together as a community.Nic Fillingham:How would an ML powered vacuum cleaner work?Natalia Godyla:I was going to say that sounds like a 2020 headline, ML powered vacuum cleaner burns down house and threat.Ram Shankar Siva Kumar:Oh my gosh. So, okay-Nic Fillingham:Man bites dog. Ram Shankar Siva Kumar:There you go. It's funny because this was not an example that I made up. I wish I did. I know. Yes, Nic. I see, yes.Nic Fillingham:What? Ram Shankar Siva Kumar:Yes. Nic Fillingham:All right.Ram Shankar Siva Kumar:This is a well-documented paper called a concrete problems in AI safety. And they talked to the most it's like Final Fantasy. Everything that needs to go wrong is going wrong. So, they're like robots that are burning down homes, breaking things that they can clean up. So if your machine learning system is not trustworthy, there are going to be problems. And you really need to think about that. Nic Fillingham:I can't even get my kettle to boil.Ram Shankar Siva Kumar:But the thing that really worries me is ML applications used in health care. You keep seeing headlines like machine learning systems being used by radiologists, amidst radiologists when it comes to identifying Mulligan tumors and things like that. There's a fantastic work by Samuel Finlayson from Harvard. He show that if you take an x-ray image, just take it and slightly rotate it and you give it to the ML system. It goes from very confidently thinking that it's malignant to very confidently judging it's benign. And that is really scary.Ram Shankar Siva Kumar:In the beginning of the podcast, we spoke a lot about how an adversary can subvert machine learning systems for fun and profit. Oh boy, there is an entirely separate world of how machine learning systems can fail by themselves. What we call unintentional failure modes. And trust me, you will want to go live in the middle of the North cascades in a cabin after you read that work. It'd be like, I am not getting anything ML powered until they figure this out. But the good news is there're extremely smart people, including Hiram and Will from my team who are looking into this problem. So you can feel a little bit like a shore that they're the true Avengers out there.Natalia Godyla:I love all the head nods from Nic. I feel like it underscores the fact that we only know a percentage of the knowledge on ML. So we just need a community behind this. No one company person can know all of it. Ram Shankar Siva Kumar:Absolutely. Oh my gosh. Yeah. When we open the adversarial ML threat matrix Google group, we now went from zero. We felt like nobody's going to join this Google group. It's going to be like a pity party where I'm going to email Michel from MITRE and he's going to respond back to me. But no, we went from zero to 150 right now over just the last four days.Natalia Godyla:Ram, thank you for giving us all of this context on the adversarial ML threat matrix. So what's Microsoft's continued role. What's next for you in ML?Ram Shankar Siva Kumar:First of all, we are hiring. So, if you'd like to come and join us, we are looking for developers to come and join us in this quest. So please email anybody, even Nic, and he can forward his resume. Nic Fillingham:Do you need to have a cowboy hat? Is a cowboy hat a necessity?Ram Shankar Siva Kumar:Not at all. We will accept you for who you are. Natalia Godyla:Do you provide the cowboy hats?Ram Shankar Siva Kumar:We will provide everything. Anything to make you feel comfortable. So we are growing and we'd love to work with the folks. With the adversarial ML threat matrix, like I said, we really are looking for feedback from the community. We really think that like Natalia very correctly pointed out this is a problem so big that we can only solve it if we all come together. So please go to our GitHub link. I'm sure Nic and Natalia might put the link to it. We'd love to get their feedback.Ram Shankar Siva Kumar:The second thing is if you kind of are... We are especially looking for people to come in at case studies, if you think we're missing a tactic, or if you think that you've seen an attack on a ML system on a commercial Ml system, please reach out to us and we'd be happy to include that in the repository. Nic Fillingham:If your autonomous vacuum cleaner has attempted to undermine democracy, let us know. Ram Shankar Siva Kumar:And the one thing that I want everybody to take away is that when we did our survey, 25 out of 28 organizations did not have tools and processes to kind of secure the ML systems. So if you're listening to this podcast and you're like, "Oh my gosh, I don't have a guidance." Do not feel alarmed. You're tracking with the majority of the industry. In fact, three organizations, all of whom were large in our survey even thought about this problem. So there are tools for you and processes that we put out. So in our docs at Microsoft.com, there's a chat modeling guidance, there's taxonomy, there's a bug bar that you can give to your incident responders so that they can track bugs. And for the security analysts community, there is the adversarial ML chat matrix. So please go read them and please give us feedback because we really want to grow.Natalia Godyla:I love it. Thank you for that. That's a great message to end on.Ram Shankar Siva Kumar:Awesome. Thank you, Nic and Natalia for having me. Really appreciate it. This was really fun.Natalia Godyla:And now let's meet an expert in the Microsoft security team to learn more about the diverse backgrounds and experiences of the humans, creating AI and tech at Microsoft. Today, we're joined by Justin Carroll, threat analyst on the Microsoft threat intelligence, global engagement and response team. Well thank you for joining us, Justin.Justin Carroll:Thanks for having me. Natalia Godyla:Well can we kick things off by you just sharing your role at Microsoft. What does your day to day look like?Justin Carroll:So my role is related to threat hunting across large data sets to find advanced adversaries and understand what they're doing. Look for detection opportunities and communicate out the behaviors of the specific threats that we're finding to partner teams or to our customers to help them understand the threat landscape and kind of staying on top of what attackers are doing.Natalia Godyla:That's super interesting. And can you talk a little bit about any recent patterns that you've identified or interesting findings in your last six, eight months?Justin Carroll:Well, it's been a busy six or eight months, I would say, because everybody's been very busy with COVID. We've been seeing quite a large increase in human-operated ransomware and stuff like that. So I've been working really hard to try and figure out different ways to try and surface their behaviors as early as we can to customers to help them take action before the ransom happens. And we've been seeing quite a few other different really advanced adversaries compromising networks. Justin Carroll:A lot of it's kind of the same old, same old, just more of it, but it's always interesting and there's never a shortage of new findings each day and kind of moments of, "Oh, that looks like this, or they're doing this now." Awesome. Great.Natalia Godyla:You mentioned you're constantly trying to find new ways to identify these faster. What are the techniques that you're trying to use to find the threats quicker?Justin Carroll:There's a whole bunch of different ways that you kind of try and surface the threats quicker. Some of it's research and reading other people's work and blogs and stuff like that. I tend to live in the data most of all, where I'm constantly looking at existing attacks and then trying to find similar related behaviors or payloads or infrastructure and pivoting on those to try and attempt to find the attack, to be ready to find it as early as possible. And what's called the kill chain.Justin Carroll:So from the time that the attacker gets in the network, how quick can we find them before they've had a chance to conduct their next set of actions? So whether if they're stealing credentials or something like that, can we surface them before they've had a chance to do the credential theft and then kind of always trying to move earlier and earlier in the kill chain to understand how they got there. And then what are some of the first things that they did when they did get there and how do we surface those next?Justin Carroll:Because a lot of those are a little bit more difficult to surface because it can kind of tend to blend in with a lot of other legitimate activities. Nic Fillingham:What kind of tools do you use Justin? Are you in network logs and sort of writing queries, is there a big giant futuristic dashboard that you sit in front of and you have virtual reality gloves moving big jumps of numbers left and right. Well, what are the tools of your trade? Justin Carroll:So one of the tools that we use a lot, there is a bunch of data that's stored... Customer facing, it's usually called Azure data Lake. It's these huge databases with large amounts of information where you can construct queries with what's called KQL, I believe it's Kusto query language. So there's a specific tool for kind of deep diving into all of that data across our many different sources. And then using that to basically structure and create different queries or methods of finding interesting data and then kind of pivoting on that data. Justin Carroll:Then in addition, I've built some of my own tools to kind of help improve my efficiency or automate some of the stuff that I have to do all the time and then just to make me faster at hunting for the things that I'm looking for.Nic Fillingham:Is it an AI version of yourself? Is it a virtual Justin?Justin Carroll:No. We work with the ML team to try and share as much knowledge with them as possible. There is no tool for an AI Justin, as of yet.Nic Fillingham:Well, let's back it up a bit. So one of the things we would like to do in these interviews with the security SMEs, I'm not even sure if we've explained what an SME yet. We call it a Subject Matter Expert. That's an acronym. We use a lot here at Microsoft. I think it's pretty broadly known, but if you've heard of SME or SME, that's what it means.Nic Fillingham:Now, you and I, we crossed paths about a year ago for the first time when Jessica Payne, who actually hasn't been on the podcast yet, Jessica introduced me to you and she said, "You have to talk to Justin." And she gave me three sort of very disparate, but intriguing bits of data about you. She said, "Justin used to climb telegraph poles. He is a big Star Wars fan and is in a metal band." And I'm sure I've gotten those three things slightly wrong. Could you kind of talk about your journey into the security space and then sort of how you found yourself working for Microsoft. But first of all, these three things that Jessica told me are any of them true?Justin Carroll:Mostly they are. So some of these will kind of combine for the telephone climbing aspect. I used to work for a wireless internet provider that had leases or specific towers, cell phone towers or other towers on top of mountains, essentially, where we would have wireless radio dishes that would communicate to each other. So I was occasionally tasked with installing and or fixing said towers, which is okay if you are fine with heights, I wasn't at first, but you just kind of get used to it. And you kind of realize once you're above 20 feet, it really doesn't make any difference. If you fall, it's going to hurt, but climbing a tower in the winter and in the wind and where you can barely feel your hands and all that wasn't great. Justin Carroll:I was a pretty big Star Wars fan growing up as a kid, even more of a Ninja Turtle fan. And as for metal, I used to be in a band with some friends and have been playing guitar for 25 or 26 years. And music has been a very huge part of my life and remains to be.Nic Fillingham:I think we'll circle back to Ninja Turtles. I'm not going to let that one go, but so let's talk about your path into security. So was this you're working for the wireless internet provider was this your first job. Was this mid career. Where does that fit in your sort of LinkedIn chronology? And at what point did you use formerly into insecurity?Justin Carroll:So it's been a long and winding road to get here I would say. So the internet provider was what I would guess I'd call my first career job of sorts. I had started there in my early 20s and worked for them for about... sorry my cat is right in front of the microphone. One second. Nic Fillingham:There's a cat there. Justin Carroll:She wanted to say her piece. So I worked for the internet company for just under a decade. I used to do some networking type fun stuff in Halo 2, to kind of maybe garner a little bit of an advantage, I guess I would say, and use those learned skills to land that first job. And I did that for quite a while, but realized I was kind of stuck in this job. It was in a city that I didn't want to live in. And I had kind of maxed out my capabilities there. I had attempted to move to Portland because I wanted to have a bigger city experience. I applied to 254 jobs, got one interview for basically an office tech support role was the only position I got hired, but it wasn't feasible to live in Portland.Justin Carroll:So after quite a bit of soul searching and realizing that basically nobody cared that I had eight years of on the job experience because I didn't have a college degree. There were not any doors open for me for the most part. I then decided to take a pay cut and go get a job at a university that was just a city over and work full-time and go to school for a degree in cybersecurity while working full-time for the university doing kind of technical work for them, helping them understand their... Sorry, my cat is a whole thing right now.Nic Fillingham:Your cat's just trying to interject with like don't. Hey, you glossed over that Halo 2 thing, you better to come back to that.Justin Carroll:Aria, come here. Nic Fillingham:We're leaving all this in, by the way. Natalia Godyla:Yeah. We're very much enjoying it.Justin Carroll:So kind of advising the university on different technologies that they could use for their students. So I did that for about three and a half years while going to school and then graduated top of my class and applied for another 150 some odd jobs and mostly the Seattle area this time and was about to give up because even though I now had a degree and almost 10 years of experience, it still wasn't enough. And everybody that I kept losing to had between 10 and 20 years experience. And it just wasn't an option for folks with less specific cybersecurity experience to kind of enter the field. Justin Carroll:There were a lot of walls that were put up. I had a friend of a friend who worked for cybersecurity at a company somewhere in Arizona, who I'd never met. And he decided to go out of his way, even though I'd never met him and looked for some cybersecurity type jobs in my area that he thought maybe I'd be good for and helped me look at my resume and stuff like this. And that helped me land a vendor role for Microsoft, where I kind of started my path and career towards cybersecurity specific stuff.Justin Carroll:I had basically given up at that point on ever working in cybersecurity and had kind of thought that it just wasn't meant for me. So that was kind of a big break and a guy almost closed the application to apply for the job and then figured what's the worst they can say is no, that is kind of how I finally got to Microsoft and cybersecurity, where I was able to work as a vendor for the team evaluating kind of telemetry. And I was kind of given an opportunity to learn a lot and that eventually transitioned into when a position became available, where I started working full-time as a Microsoft employee and went from there.Natalia Godyla:So what in your soul search brought you to cyber security? Was it your background, the fact that you already had those foundations as a network admin, or was there something in particular in the cybersecurity world that just attracted you?Justin Carroll:I'd always found it fascinating. When I started university, they just launched the cybersecurity program. The quarter that I started there, and one of my friends who was a computer science major, basically called me up immediately and was like, "Hey, they just launched this. You need to do this." And there's the very popular culture aspect of it where everybody thinks it's fascinating and you sure there was a little bit of a grab with that. But I like learning how computers work and I like kind of the constant problem solving nature of everything. And the first class I took on it I was hooked and still remains that day where it's just, it's fascinating and it's really fun to just kind of continually work to see what attackers are doing. But I also, there's a huge aspect of it like I like helping people. I think it's important and having a role where I'm able to help millions or even potentially billions of people through better detections or stopping malware. It feels pretty great.Nic Fillingham:What other aspects Justin, of your path to security, your path to Microsoft, do you feel you're sort of bringing forward? I want to ask about you very briefly mentioned something about Halo 2 and I want to know what that was. And then I wonder if there were other sort of dare I say, sort of maybe unorthodox or non-traditional things that you worked on where you learned a bunch of bunch of tools or tricks of the trade that you're bringing forward to your work right now. Justin Carroll:So Halo 2 was a fun one. Back in those days, there were lots of what were called modders, who would mod their Xbox's to gain an unfair advantage. So I would use my networking know-how basically, and learned a lot of it too, when encountering a modder to kick them out of the game. I think it was possibly a little frowned upon, but I was tired of having cheaters constantly win, so I did a lot of research and I didn't know a whole lot about networking at that point, but I tried to not use it as a competitive advantage, but more to just level the playing field, but it was a great way to learn how firewalls worked and network traffic and building more on my understanding of computers. Justin Carroll:And then, kind of, that set a foundation for me, of understanding, there's always going to be stuff that I don't know and what I have done, but I did it all through college and continued all the way till basically getting full-time employment at Microsoft was I set up a lab environment and I would set up servers and clients and I would attack them and monitor the logs on my own little private lab on my machine and see what worked, what didn't, try and figure out why it worked, what didn't and try and build different tools to see how I could make it more effective or deal with different issues.Justin Carroll:Just kind of both playing attacker and defender at the same time on my network, all by myself, essentially and kind of learning from all of that data was massively important and anybody who's looking to get into security, I highly recommend both learning how to attack, on a safe, your own little lab environment where you're not hurting anybody. And what's it like to try and defend and find those attacks because both sides are-Nic Fillingham:Red Justin versus blue Justin. Justin Carroll:Exactly. Yes.Natalia Godyla:You noted earlier that just the sheer amount of data can be overwhelming, especially as you moved through your career and then came to Microsoft where we have billions of signals. So the same transition happens from Halo to now just the sheer scale and scope of your role and the amount of good that you can do. So, how did you handle that overwhelming amount of information, amount of impact that you can have?Justin Carroll:So when I was first brought on one of the things that made a significant difference was I had somebody that kind of instructed me in a lot of the ways of kind of how to work with the data, but I was also given quite a bit of an area for trial and error. So there was lots of opportunity to fail and to learn from what didn't work and to kind of keep building on that. And then any time that I got stuck or I would kind of just do everything I could to attempt to solve the problem or work with the data. If I kind of hit a wall that I couldn't climb on my own, I could go to him and then we would solve it together. So it was kind of both a mentoring and a guidance thing, but also kind of given that ability to experiment and try and learn. So that was kind of one of the biggest ways of learning to pivot on that data and understand it and consume it.Justin Carroll:And then honestly, collaboration with other folks on my team and other team was massively instrumental to be able to kind of learn what they had already learned or pass on my knowledge to them. And just that constant sharing and understanding because there is so much data, it's quite impossible almost to be an expert at all of it. So having those folks that you can reach out to you that are experts in each basically set of their data. So you can understand what the data is trying to tell you, because that's one of the things that is particularly difficult is to take the data and actually glean understanding from it. The data is trying to tell you something, you just need to make sure you're interpreting the message correctly.Natalia Godyla:How do AI and ML factor into your role into helping you manage this data and collaborating with other teams.Justin Carroll:So I work quite a bit with a lot of different data science folks on a few different teams to either use a lot of the models that they're creating to kind of a source, a lot of the malicious information or a particular attackers or stuff like that. And then also collaborating back in sharing my knowledge and intelligence to them to say, this is what an attack looks like. This is what it should look like in the data and kind of giving them the ideas and signals for what they should be looking in their data to kind of train those models. Justin Carroll:It's really important to have that partnership between security and data science for AI and ML to kind of help them understand the security sphere of it. And then they can kind of take the real math and data prowess that they've got and turn our knowledge into ML or AI to detect and surface a lot of these things. Nic Fillingham:If it's possible, Justin, how would you sort of summarize your guidance to other Justin Carroll's that are out there that are... They want to get into security, they're fascinated by cybersecurity in sort of a macro sense, but they feel either don't have a degree or they're not even sure what they should go study or they're trying to work at, how can they translate their current sort of career experience and sort of skills? Can you summarize that into some guidance of what folks should do to try and break in?Justin Carroll:Sure. One, if you're in school, remember that school is not going to teach you a lot of the stuff that you need to know. It's lots of taking what you're learning and building upon it outside. So if it's cybersecurity, that's an interest, try and experiment and fail. Cyber security is huge. There are so different facets of it. Find out the thing that kind of scratches the itch and piques your interest. For me, that was setting up a lab, right? Where I could play both the attacker, the defender, the person monitoring logs, the person setting up all the configurations to try and stop the attacks and was able to kind of see all different aspects of the industry. Nic Fillingham:So just jumping in, was that literally just a bunch of VMs on your machine or did you have multiple PCs sort of networked together? Just very quickly, what did that look like? How accessible is setting up a lab? I guess I'm what I'm asking. Justin Carroll:It is pretty accessible. So while I was in college, it was actually multiple machines and I had four different machines and I set up a router that you can pick up for 50 bucks and a smart switch that I could mirror the traffic on to understand everything for 100 bucks. So there's a little bit of cost. That was kind of my college setup. And as I was kind of learning where I at that point, it made a little more sense to do it with actual machines and for extra clarity. My college was only a couple of years ago. I did not go to college young. So the next route that I did once I headlined did my vendor role and was kind of like security is for me and I want to keep building on it.Justin Carroll:I did it all with VMs. So I just had a desktop computer that had okay specifications and I configured two clients, the domain controller, server on the device and then a mail server. And then basically you just connect to each client and then network them all together. So at that point you can use VirtualBox, you can use lots of different stuff. So the availability of doing that, it's actually pretty good. There isn't a lot of overhead costs or anything like that. You just have to have a okay computer.Natalia Godyla:What about resources to learn how to do all of that? Are there organizations or sites that someone could turn to, if they're interested in starting to do some of this starting to experiment with what they're interested in?Justin Carroll:Honestly, I would say one of the best resources that I had throughout was YouTube. It was a great place to get walkthroughs for every different thing. So like I wanted to learn how to set up a VM and configure it with networking to another VM. I turned to YouTube. I wanted to learn how to attack the VM using Kali Linux, YouTube. And there's a whole bunch of different channels out there that specifically focus on that. And then the other thing is because it's so much more open for creators to share content. You can find people who are at a similar level or maybe just a few steps ahead of you. So you can really kind of join along with other people. Justin Carroll:There are a few websites for coding, I think one's called hacking the box as far as attacking different things. And that was also kind of fun where a lot of the devices that need to be attacked we're already pre-configured for you. But for me, honestly, a lot of the fun was setting up those devices and then learning what I did that worked and didn't and what allowed it to be attacked and what I could do to stop that.Natalia Godyla:Quick plug Microsoft security also has a YouTube channel in case somebody would like to get any, how to content on our products.Nic Fillingham:Natalia may or may not have been involved in that channel, just full disclosure there.Natalia Godyla:Yeah. I couldn't help myself. But it is also great to hear that you found people to work with in the community as well. That's something that's been noted by a few of our guests, like Michelle Lamb, that as she was entering the space, she found mentors. She found conversations, people readily available to either work on a problem alongside her, or just answer questions. So I'm glad that you've also been able to turn to the community for that. So what's next for you? Is there a new challenge that you'd like to solve?Justin Carroll:Definitely want to work on the toolkit that I'm building and kind of continue that growth. It's been interesting to kind of see the hurdles I run into. And even last week I ran into one that felt insurmountable and was able to chat with one of the devs and solve in a few minutes and learned a whole lot and going forward, now I have that in my pocket. And then both-Nic Fillingham:Hang on. Did you say you went from found a new challenge, thought all this is insurmountable and then a few minutes later you solved it?Justin Carroll:With a little support from people that knew how to solve the problems. So collaborating with like one of the other devs on the team and basically having him kind of explain the part it felt like a giant wall, but really once you kind of have somebody to break it down a little bit for you, it was just like, "Oh, okay. I see what I'm missing here." And then it was just like, "Got it. Okay. Moving forward."Nic Fillingham:Oh, I see. So that that's more an endorsement. Yeah, I got it. Justin Carroll:Yeah. Yeah. It's more an endorsement of others teaching abilities and just kind of those times of being able to reach out to others for when you really get stuck and how much of a difference it can make. I had spent an hour on something and was just like, this is ridiculous. This should work. Why isn't it working? What's wrong with me. I'm not smart. And then just chatting with them a little bit and then figuring it out and then like, "Oh, okay. Oh, okay. That's actually pretty simple." I wasn't thinking about it in the right way and kind of getting that other perspective. Justin Carroll:And then what's next kind of going forward is a kind of continued partnership with a lot of the data science folks to, I think we've only scratched the surface in many ways as an industry on how data science and cybersecurity can work together. So I am very excited to kind of see what kind of stuff we can accomplish, whether it's, you know, surfacing attacks shortly after they happen, very early in the kill chain or understanding related behaviors and trying to understand who the might be, or I think most of all, the intent of the attack or adversary.Justin Carroll:Intent can sometimes be a very difficult to suss out, even for SOCs and their entire center. They have all these folks that are trying to figure out what happened. Why did it happen? What does it actually mean? So if we can have data science that can provide a lot of context on that, through understanding existing attacks and modeling what future ones might look like, I think there's some pretty exciting opportunities there.Nic Fillingham:All right, I'm doing it. We're coming to Teenage Mutant Ninja Turtles. You're a fan. How much of a fan are you, Justin?Justin Carroll:I'd say quite a fan. I do have a couple of figurines and a mint package unopened from '87 I think, something like that. And then have a Ninja Turtles tattoo on my back of Raphael. So that was kind of one of those moments where I was trying to think about what steps I wanted to take forward in life and things like that. And I had kind of thought about what are the things that actually make me happy? Justin Carroll:This was probably my mid 20s quarter life crisis kind of thing. And I was like, "I always liked the Ninja Turtles as a kid." They always brought me great joy. I still get excited about watching them. The movies are definitely a guilty pleasure. I realized they're not great. But now I'm talking about the original movies, not the new ones. We won't talk about the new movies. And it was just one of those like, "Yeah, I identify with this. This is a huge part of my life. It's been around since I was... it was started the year I was born." So I was just like, "All right, let's do it." And haven't regretted it at all.Nic Fillingham:I was going to ask who your favorite turtle was, but you've obviously... If you've inked Rafaelle on your back so that question is moot. I'm a Donatello guy. I've always been a Donatello guy.Justin Carroll:I would think of myself as Raf, but really I'm more of a Donatello. Ralph was kind of the cool guy with a little bit of an attitude, but really I was Donatello. When I was 10 dressed up for Halloween, I was Donatello. I'm definitely Donatello with a little bits Raf thrown in for good measure.Nic Fillingham:Well, this has been a blast. Thank you, Justin, for walking us down, Teenage Mutant Ninja Turtle memory lane, and Halo 2 memory lane and sharing your story with us. It was great. Wonderful to get your perspective. Great to have you as a part of the threat hunter team here at Microsoft and contributing in all the ways that you do. Thanks for joining us. I'm sure we'll talk to you again at some point on the Security Unlocked podcast, but keep doing you Cowabunga, dude.Justin Carroll:Thanks very much for having me. I appreciate it. It was great to talk to you all.Natalia Godyla:Well, we had a great time unlocking insights into security from research to artificial intelligence. Keep an eye out for our next episode.Nic Fillingham:And don't forget to tweet us @msftsecurity or email us at email@example.com with topics you'd like to hear on a future episode. Until then stay safe.Natalia Godyla:Stay secure.