Podcast

• 00:40 – Matt’s duties at OpenAI
• 01:52 – Matt’s accidental journey into cybersecurity
• 05:18 – The intersection of AI and open source
• 06:45 – Matt’s thoughts on how AI can help security professionals
• 08:53 – Details on the AI Cyber Challenge (AIxCC)
• 10:53 – Matt answers Omkhar’s rapid-fire questions
• 12:29 – Advice Matt would give to aspiring security professionals
• 13:00 – Matt’s call-to-cation for listeners

• Matt Knight’s Linkedin page
• GNU Radio
• AIxCC Challenge
• OpenAI Cybersecurity Grant Program

Matt Knight soundbite (00:01)
AI has the potential to help cybersecurity practitioners where they’re constrained. That’s important because cybersecurity engineers face a lot of constraints. Every security team is constrained by capabilities, is always up against pressure to be faster and is always up against pressure to access greater scale. 

Omkhar Arasaratnam (00:18)
Welcome to What’s in the SOSS? I am your host Omkhar Arasaratnam. I am also the general manager of the OpenSSF. Today we have a good friend of mine Matt Knight Matt. Why don’t you tell us what you do?

Matt Knight (00:31)
Hey, my name is Matt Knight. I’m the head of security at OpenAI.

Omkhar Arasaratnam (00:34)
I feel like you’re burying the lead here. What does the head of security at OpenAI do? I mean, it doesn’t sound like a boring job.

Matt Knight (00:40)
Yeah, it keeps me on my toes. So I joined OpenAI back in 2020 and have been building the security, privacy and IT programs since then. Before OpenAI, I spent most of my career protecting companies and institutions that had comparable high-value research and technology. I also co-founded a company called Agitator that focused on security research. And if you go far enough back, I started my career as an electrical engineer before getting into security.

But these days I spend most of my time focused on security engineering and building the systems for developing and deploying advanced AI. My teams and I also collaborate on security research with teams across OpenAI and with the broader security research community to explore the frontier of this technology, understand its impacts and also maximize its benefits, specifically as far as I’m concerned, on the cybersecurity domain. 

And internally this involves using large language models wherever we can to enable our security program. And yes, even doing some open source work of our own, too. So it’s great to be here and I look forward to a great discussion.

Omkhar Arasaratnam (01:46)
Wonderful. Thanks, Matt. Sounds like you’ve had quite a journey in terms of security. Why don’t we start at the beginning? How’d you get into security?

Matt Knight (01:52)
To put the bottom line up front: accidentally. So I started my career as an electrical engineer, as I mentioned, I studied EE in college and EE is a pretty big field. You can be sort of on one end of the spectrum, you can be doing analog electronics on the other end, you can do digital, coupled with software engineering.

And I was always more on the digital side. So my first job out of college, I was working as an embedded software engineer, writing software for wireless networking stacks. And it was pretty interesting work, but I got to a point in my work where I found that I needed a spectrum analyzer to debug a system I was working on. And if you’ve ever had to buy lab equipment, you know that it’s really expensive. 

But right around that time, there was this open source project called GNU Radio that was getting a lot of buzz. And GNU Radio was really cool because it was this powerful open source signal processing toolkit that enabled basically like using software to implement all these different radio engineering and signal processing tools.

And between GNU Radio and some low-cost commodity hardware, I was able to get my hands on, I was able to basically build my own spectrum analyzer to help me do my work in developing and debugging these wireless systems. So I had this toolkit for monitoring the spectrum and it was pretty useful for that, but I kind of kept playing with it and found that you could use it not only to, you know, capture and analyze signals, you could also use it to replace signals, to generate your own signals. 

And, you know, realized that, you know, when you, if you captured a signal and replayed it, a lot of devices would just accept it and would, would, you know, treat that as valid. And that really freaked me out. Also got me, you know, was sort of my first contact with how, you know, vulnerable much of that ecosystem was. And I kind of couldn’t look away from it. 

So, I started doing security research on my own nights and weekends, wound up having the opportunity to make a career out of it. And wound up doing a lot of work in that, you know, open source or in that, that wireless security space, a lot of which was supported by this really vibrant open source community at the time. And I did that for a while and then made the choice a couple of years later to make a career transition into what I’m doing now.

And I’ve been spending roughly the last decade playing defense. I still have a lot of passion for the wireless space, but these days I’m spending my time protecting companies rather than doing wireless research.

Omkhar Arasaratnam (04:16)
You might have come up with the Flipper Zero before the Flipper Zero.

Matt Knight (04:19)
Flipper Zero is pretty cool. No, I was working with other sort of open source and some proprietary bits of hardware, but really underpinning all of it was GNU Radio. GNU Radio is a really, really powerful open source tool. There’s a ton of great academic and commercial work and research being done on it.

They have a great community around it. I’ve spoken to their conference a couple of times. And if you go far enough back, I open sourced at least one GNU Radio module myself based on research that I’ve done. So quick shout out to that community. It’s still going strong. And I’m always impressed with the great folks who work on that toolchain are coming up with.

Omkhar Arasaratnam (04:57)
I’m happy to hear that. So open source, it’s been with you for a really long time. Let’s talk about your day job now. So you’re working on a lot of cutting-edge stuff. As we think about AI, large language models, generative AI, how much of that world is supported by open source? What’s that look like?

Matt Knight (05:18)
Quite a bit of it is derived from open source. And I’d say that most companies are, to some degree, leveraging open source and also building their own. If we look at many of the frameworks that the AI industry leverages, think things like PyTorch and TensorFlow, they started in various ways within companies but now are open source and are sort of robustly supported by broad communities.

And if you go beyond the frameworks, there are of course, myriad dependencies that companies depend on to do their research and also to run their infrastructure. And of course, much of the world’s AI training infrastructure runs on Linux, which is, you know, of itself, of course, open source. So I’d say that by and large, you know, open sources is pretty important to AI research and innovation. 

But beyond AI, you know, much of the tools that the security industry uses too, you know, have open source connections too. So there’s a network security tool called Zeek that most security, well, I shouldn’t say most, but many security teams use in different ways that’s really powerful. And then, you know, in other domains like code scanning, we’ve got some newer tools like Semgrep and CodeQL that are really powerful. 

Omkhar Arasaratnam (06:25)
So we talked about how open source is a lot of foundational components of what we use in terms of AI today and how open source is a foundational component in a lot of the security tools we use. What if we inverted that? How can we use AI to improve the security of open source? Do you have any thoughts on that?

Matt Knight (06:45)
I do. So my teams and I spend a portion of our time studying and analyzing how advances in AI may impact cybersecurity. And we want those benefits to be, of course, as broadly distributed as possible. And what more deserving beneficiary of that than the open source software ecosystem?

And a thesis that I’ve sort of been refining here is that AI has the potential to help cybersecurity practitioners where they’re constrained. And that’s important because cybersecurity engineers face a lot of constraints. Every security team, to some degree, is constrained by capabilities, is always up against pressure to move faster, and is always up against pressure to access greater scale. 

Do you have the expertise to find and fix the security problems wherever they may lie? Can you find and fix the problems fast enough to mitigate issues before they turn into real problems? Can you fix the problems wherever they happen to exist? There’s always more code to analyze, there’s always more logs to analyze, there’s always more that you can do to get leverage. Can you access them efficiently? 

So we are finding that AI is broadly useful to alleviate some of these pressures. And we as a team look to incorporate language models into our own work wherever we can. Now, of course, it is necessary to be aware that these tools are very imperfect on their own. They have things that they’re really good at and they also have a lot of downsides. So we’re looking for places in which we can implement these tools to benefit our work while also managing the drawbacks and downsides. 

Omkhar Arasaratnam (08:30)
Sounds good. So we’re recording this just after the Open Field Competition for AIxCC closed. It closed on April 30th. Can you share with the audience a little bit about the AIxCC, the AI Cyber Challenge, how OpenAI is involved, obviously, OpenSSF is a supporter as well.

Matt Knight (08:53)
I’m happy to and Omkhar, I think we first met at DEF CON last year in connection with the AI Cyber Challenge and I’m glad to be supporting this initiative along with OpenSSF. So the AI Cyber Challenge really has a great mission at its core, which is to find and fix vulnerabilities in the open source software that powers and underpins the critical infrastructure that we all rely on.

And it’s very timely because we’ve seen this great explosion in AI capabilities that’s largely been driven by language models. And while we’ve seen so much capability growth in language models, I believe that static analysis, that is finding and fixing vulnerabilities in source code, is an area where language models have historically underperformed. I think it’s a rich area for research, but because the capabilities are still emergent, I think success in this challenge is gonna involve a lot more than just like clever prompt engineering to get results. 

But the challenge is great because it engages a robust security research community. It brings a whole bunch of folks who wouldn’t necessarily participate in a program like this into the fold. And it’s also gonna happen and play out publicly. I think the semi-finals and finals are slated to be at DEF CON, which will be a great way to get even more of the community involved. And I’m pretty enthusiastic about what it’s gonna produce. If we look at where conventional static analysis tools fall short, AI and language models have the potential to really bring different capabilities to this domain to help, I think, fill in some areas that could really benefit the sort of static analysis tool ecosystem.

Omkhar Arasaratnam (10:36)
I’m really looking forward to seeing what our competitors come up with as well. We’re going to move into the rapid-fire section. So I’m ready when you’re ready. And the right answer for any of these may be one of the answers I provide or no, Omkhar, I actually, I think it’s something else. So are you ready?

Matt Knight (10:55)
Let’s go, hit me.

Omkhar Arasaratnam (10:57)
Spicy or mild food?

Matt Knight (11:00)
Okay, so I have Irish heritage and I grew up in a family and household where salt was an exotic spice. So my answer may surprise you. I am a spicy food guy all the way.

Omkhar Arasaratnam (11:14)
All right, man. Well, we’ve got…we’re going to be grabbing a meal soon. I hope you’re…I may bring some hot sauce with me. Now, the next couple of questions are very engineering-focused. Text editor of choice: VI, VS Code or Emacs?

Matt Knight (11:32)
I am a VI or Vim person all the way. And, I mean, beyond it just being the first thing that I learned, it’s on everything. You know, it’s on your, it’s on your Linux, you know, laptop, it’s on your, you know, all the servers you’re going to jump onto, but it’s also on a lot of embedded systems. You know, you’ve got the small low profile and embedded versions of it that you see in various places. So it’s a pretty useful editor to fall back on.

Omkhar Arasaratnam (11:59)
I’m also a Vim guy, so full support here. Last but not least, tabs or spaces?

Matt Knight (12:05)
Spaces and specifically two of them.

Omkhar Arasaratnam (12:09)
(Laughter) Excellent Thanks so much for for going through that. Now Matt, as we close out the podcast, what advice do you have for somebody entering our field today — somebody that’s either a new grad? Just completed their undergrad in comp sci or somebody that may be switching careers. What advice do you have for somebody entering today?

Matt Knight (12:29)
Love this, love this question. The world is changing beneath our feet very quickly with whether it’s the emergence of AI or just sort of more generally the pace at which the software ecosystem or the security ecosystem moves. So my advice to anyone who’s getting started is really to stay curious. And if you commit to that and a lifetime of learning, just enjoy the ride.

Omkhar Arasaratnam (12:55)
And the last question for you, what’s your call to action for our listeners?

Matt Knight (13:00)
A couple of things here will be exciting to the listeners here. The first is that we at OpenAI are hiring. So if you’re interested in AI or language models or security, please do give us a look. I also want to just briefly mention our cybersecurity grant program. This is something that all your listeners should feel encouraged to participate in. But we’re giving out a million dollars in cash incentives plus API credits to fuel innovation and research in defense of cybersecurity. 

We love open source as part of that. So if you are working on or want to work on some sort of open source innovation to help benefit the ecosystem, we’d love to take a look and fund it. Just some ideas of things that we’re excited about. So, you know, porting code to memory-safe languages. If you want to look at applying AI to that, that would be awesome. We think that confidential computing for GPUs could be a pretty important layer for protecting AI services going forward. And we’d love to fund some work around that, and other ideas too. We’re always looking for research collaborations with the broader community. So we’d love to hear from you. And just lastly, two of my colleagues were at Black Cat Asia, Paul McMillan and Fotios Chantzis. They actually open sourced some of their work coming out of that. Some automation that we built at OpenAI to help enable our work and help our teams move faster. So if that sounds interesting, I encourage you to go check that out.

Omkhar Arasaratnam (14:25)
Thanks so much, Matt. Really appreciate your time. Thank you for joining us on the podcast.

Matt Knight (14:29)
My pleasure, thanks for having me.

Announcer (14:31)
Thank you for listening to What’s in the SOSS? An OpenSSF podcast. Be sure to subscribe to our series of conversations on Spotify, Apple, Amazon or wherever you get your podcasts. And to keep up to date on the Open Source Security Foundation community, join us online at OpenSSF.org/getinvolved. We’ll talk to you next time on What’s in the SOSS?

In this episode, Omkhar talks to Eric Brewer, professor emeritus of computer science at the University of California, Berkeley and vice president of infrastructure at Google. He’s also on the Governing Board of the OpenSSF. His research interests include operating systems and distributed computing. He is known for formulating the CAP theorem about distributed network applications in the late 1990s.

• 01:15 – Eric discusses his background
• 03:14 – Improving security in a corporate vs. open source environment
• 05:58 – Advancements Eric has noticed in open source in recent years
• 07:17 – How to make software repositories more secure
• 08:58 – The next big hurdle in open source security
• 11:12 – Rapid-fire questions: Mild or spicy food? Vim or Emacs? Spaces or tabs?
• 12:42 – Eric’s advice for aspiring security professionals
• 14:45 – The importance of being active in security communities

• Eric Brewer’s LinkedIn profile
• OS3I report

Eric Brewer (soundbite) (00:01)
I do think we need to start tackling build services and automated testing. And the reason these are harder is because they cost money. Even if you’re willing to volunteer time to work on open source, you may not be willing to pay for extensive building and testing. 

Omkhar Arasaratnam (00:18)
Hi everyone. Welcome to What’s in the SOSS, a podcast by the OpenSSF. I’m the OpenSSF General Manager Omkar Arasaratnam. And with us this week, we have Eric Brewer from Google. Eric, can you give us a little bit about your title and what you do at Google?

Eric Brewer (00:38)
Happy to. Nice to be on this podcast. I am a VP and fellow at Google. I’ve been working on cloud-related things for a long time, really since the 90s, before we had a cloud. At Google, I’ve been working on things like Kubernetes and open source security, and that’s what led me to help start the OpenSSF.

Omkhar Arasaratnam (00:58)
And for our listeners, a long time ago, Eric and I both worked together. And in fact, how we got to know each other was through my interest in open source security. And of course, the leadership that you were providing in open source security at Google. Can you talk a little bit about that aspect for our listeners?

Eric Brewer (01:15)
Yes, so through my work in Kubernetes, I came to realize in around 2018 that, you know, this was obviously a successful project, but it was also very complicated. At the time, it had like 1,200 dependencies. So it touched a whole bunch of code and that if you just look around, it wasn’t hard to find things that we depended on that realistically weren’t all that trustworthy.

And people were not very careful at the time about what kinds of things got included or how they would get used. And so that was a bit of a wake-up call for me. Then I started to look at a whole bunch of other things. I’m like, well, this is not just a dependency problem. It’s actually a supply chain problem more broadly. 

I started giving internal talks on supply chain security, which by the way, that term didn’t exist at the time either. We didn’t really call it that. It’s the right term, but how do we build our software? Why do we know it’s built correctly? And especially at the time, lots of times people would include packages directly off the Internet like you don’t even know what’s in there. My friend Kelsey Hightower often said it’s kind of like picking up a USB drive off the street, sticking it in your laptop. It’s like everyone knows not to do that, but we don’t know not to take random packages off the Internet, even though it’s a very apt analogy. 

I started thinking about that in 2018. I started thinking about what Google could do, but at the end of the day, this is not a Google problem. As much impact as Google can have, this is an industry-wide problem and needs an industry-wide solution.

Omkhar Arasaratnam (02:41)
As a grumpy old guy that’s been doing security for about two decades, the very thought of somebody randomly plugging in a USB stick they found in the parking lot sends chills down my spine. And I tota lly get the equivalence in terms of, hey, what’s the software you’re consuming off the internet? 

Now, Eric, you’ve worked in large organizations and you’ve also done a lot of work in open source. Can you speak to the differences in how you would improve security in a corporate environment like when you’re shipping code at Google versus what’s possible in an open source project?

Eric Brewer (03:14)
They are pretty different, which is something I hope to change eventually. And I give lots of talks to Google Cloud customers on this kind of topic for the corporate view, at least, which is roughly, have control of the code you’re using, which often means private copies of things. The private copies give you two advantages. One of them is you’re not taking it directly off the internet, even if it came indirectly from the internet. Second, when you have some kind of problem, you actually know exactly what code you used. Because another problem with pulling stuff off the internet is that code changes and you may not know which version you have or when it was pulled. And so you may not even know exactly what you’re running. 

So there’s some basic things like know the code you’re using. And then of course, the next big one after that is use a build service, right? You’re not allowed to build production code on your laptop because that device is probably in most cases not trustworthy for its supply chain attributes. And so those are kind of two basic examples of things that corporations can easily do and should be expected to do. 

Open source maintainers don’t have it so easy. For example, clearly they’re gonna use dependencies off the internet, they’re not gonna have a proper copy of all the dependencies, that kind of misses the point. And they typically have to build and test some packages at their own expense using whatever means they have. So to ask them to pay for a build service to do that is pretty unreasonable. And in fact, one of the things I’m looking at is how we could maybe build or rebuild packages in a secure signed way for free for open source maintainers. Maybe not all the time, but when you want to do a major release or something like that. So unclear where that will go, but there is plenty we could do to make it easier to be a maintainer for open source package, especially one that’s critical to the rest of the world.

Omkhar Arasaratnam (05:02)”
Absolutely, the notion of these kind of hermetically sealed build environments that are kept absolutely pristine versus some of the horror stories that we can think of — like, you know random laptop mining bitcoin on three of the cores while trying to do a production build of a package — that definitely has some obvious benefits in terms of using the hermetically sealed build environment, of course. 

It does sound like we’ve got quite a few things that we need to be focusing on, but since your involvement, which even predates the creation of the OpenSSF way back in 2017, 2018, I’m now referring to your involvement versus the OpenSSF’s inception in 2020, what are some accomplishments that we’ve had in the field of open source security? I mean, it’s been about, you know five, six years. What have we done so far that you’ve been proud of?

Eric Brewer (05:58)
I think there’s a bunch of things. The biggest one is probably just awareness, right? The US now has an open source strategy, right? There’s a cybersecurity executive order. Both of those things I had some influence on, but I didn’t cause them, right? The importance of these issues caused them. And so that awareness is just symptomatic of broader awareness from all the ecosystems like Python or Rust where they’re now taking their role seriously in how to secure supply chains, how to, in general, improve the hygiene of development in open source and also how to make it easier on maintainers. Those are all good goals. And our best approach is to prove the tooling that maintainers use so they don’t have to do the right thing by some kind of behavioral change. That’s hard to communicate, hard to educate.

If they can use the tools they like and it happens to do the right thing, that would be the best outcome.

Omkhar Arasaratnam (06:55)
That sounds like some great accomplishments that we’ve had and completely agree with you. Let’s move now to talk a little bit about the watering holes of our community, the software repositories, the package repos. Can you talk a little bit about how improving the security around those software repositories can help improve the security of open source software in general?

Eric Brewer (07:17)
Those are critical, critical components. Now, source code for these things is mostly in GitHub, and that does help in the sense that GitHub is at least a group that cares about improving security issues, so I thank them for that. Package managers are more complicated because there’s many of them, and each ecosystem has its kind of own culture and philosophy around these things, and so we’re not gonna have some universal agreement on exactly how to do supply chain security. But I think we can agree on some basic things. 

Like you would like to know for which are your critical projects and which are not. We’re not trying to improve, you know, or maybe raise the security burden on all things open source. Most things open source, frankly, aren’t relevant to national security. But a surprising number are. So I do expect we’ll have some kind of national dichotomy over time, which is those projects that know and actively accept that they’re part of critical infrastructure and take it seriously. And those that really want to just make their own website and create a new programming language do various things that are for their exploration or fun or all the great reasons one might do open source, right? But they’re not committing to say this is a viable thing to use in critical infrastructure.

I’d kind of like to get to the point where most projects know which camp they’re in, right? Because we have a bunch in the middle right now where it’s mostly fun, but oh, by the way, it’s included in very important things, right? Not by their choice, by the way. Being included in something is often not the choice of the maintainer, and that also causes many problems.

Omkhar Arasaratnam (08:49)
Yeah, that dependency graph can be very interesting. Looking ahead, what do you see as the next big hurdle in open source security, and what can we do about it?

Eric Brewer (08:87)
It’s a great question. We’ve done a lot of focus recently on package managers and SBOM generation. There’s still plenty to do there. I do think we need to start tackling build services and automated testing. And the reason these are harder is because they cost money. Even if you’re willing to volunteer time to work on open source, you may not be willing to pay for extensive building and testing. And how that gets paid for is I think one of the great open questions that we need to sort out the next several years. 

The point though is that we can’t really quickly fix security bugs today in part because we don’t know when you make a change to an open source package if it’s gonna break users of that package or not. So there’s some uncertainty about even pure security changes about what impact they might have on the rest of the ecosystem. Now the good news is most of the time these changes are small, most of the time they don’t break the ecosystem. But we don’t really know because we don’t have that many test cases and, in general, we don’t have test cases for all the dependents either. All the things that use Log4j, they may not have test cases that can tell if the new version of Log4j is gonna break them or not. So we have to kind of put forward changes, hope they don’t break stuff and cross our fingers. And that’s not a great place to be. 

I think if we had more automated testing, more test cases, control builds, all those would improve our chance to deploy security patches quickly and effectively when the time came. So that is an important. medium-term agenda, for sure. And this is a place actually where machine learning may be a great benefit because it looks like we’ve had some success already with generating test harnesses for fuzzing, improving test coverage. I think we can generate test cases, or we can probably do more on the front of actually making simple patches easy for a maintainer to accept. So I kept this patch to do a version bump to get the new Log4j. Some of that already, but there’s, these are mundane things and if we can do mundane things automatically, that will save everyone a lot of unfun time.

Omkhar Arasaratnam (11:07)
Absolutely, reduce toil wherever possible, right?

Eric Brewer (11:11)
Absolutely.

Omkhar Arasaratnam (11:12)
So we’re going to shift gears a bit and now we’re going to go into what I hope are a bunch of fun rapid-fire questions for you. So first out the gate, and I’ll provide you two options. The third option of course is, Omkar, it’s neither of those. Here’s my answer. So the first question is, spicy food or mild food?

Eric Brewer (11:33)
Sadly mild.

Omkhar Arasaratnam (11:34)
Oh no. Oh no. Would you like to say more on that?

Eric Brewer (11:38)
Well, I’ve been to lots of countries where there is no mild. Hyderabad in India comes to mind. The mildest they have is near the top of my spice chart. I do have, for better or worse, a very sensitive palate, which is great for wine tasting and a few other things, but it’s not good for eating spicy food.

Omkhar Arasaratnam (11:58)
Okay, well, good to know. Second question for the rapid fire. Vim or Emacs or other?

Eric Brewer (12:06)
Emacs still. Picked it up in grad school in the 90s and know certain keyboard shortcuts that are just deep in my brain.

Omkhar Arasaratnam (12:08)
Oh boy.

Omkhar Arasaratnam (12:16)
Emacs is a great operating system that has an editor attached to it. All right. Number three in the rapid-fire, and the final one for the rapid-fire, Eric. Tabs or spaces?

Eric Brewer (12:26)Spaces.

Omkhar Arasaratnam (12:27)
All right! We’re moving to our closeout now. So you’ve been in the industry for quite a while. You’re very well-regarded and have accomplished a number of things. What advice do you have for somebody that’s entering our field today?

Eric Brewer (12:42)
Well, the good news is I think open source is a great way to boost a career in computer science or tech more broadly. And it’s amazing how often I’ve wanted to hire people because of what I saw them write in open source. And I’m not saying that’s an easy path, but boy, it is a good path because it’s very clear to tell what you care about by what you choose to work on, and I can see the code you write, how you feel about lots of different topics, for example, tabs versus spaces, which is not a criterion I would use for hiring, but I might notice. 

Omkhar Arasaratnam (13:17)
Good to know.

Eric Brewer (13:19)
So there’s that role of open source, which is as a proving ground or a way to increase visibility. And by the way, if you’re helping those projects, that’s a great thing to do, regardless of even if you’re doing it for reasons to get exposure to learn about a project or space.

The second thing I would say is that, you know, it’s worth learning how to interact with many different projects. The easy thing to do is pick a project and work on it, and there’s certainly value in that. But I also feel like I’ve learned more when I’m working on five or ten different things at a time. They have slightly different cultures or different rules about what you do to submit code or readability, things like that. And those choices are worth understanding. And I’m not even saying that they’re good or bad. Point is they are diverse and the communities are diverse, and it’s much more important, I think, to be able to contribute to someone else’s project than to your own project, Most of what the world needs is interconnections of projects and glue. And that is itself a skill that’s worth acquiring.

Omkhar Arasaratnam (14:26)
I completely agree and the old adage I suppose holds up which is we can’t solve tomorrow’s problems using yesterday’s thinking, so encouraging that diversity of thought is certainly paramount, especially in security. Last question for you Eric and thank you for having been so generous with your time. What’s your call to action for our listeners?

Eric Brewer (14:45)
It’s a great question. It depends a little bit on the listeners, but I think I would start with all of the communities typically based around languages like Python or Rust, and what can you do to make your community have better support for security? And that can be all kinds of things. It can be two-factor authentication. It can be helping with automation for SBOMs or for signing things correctly or being able to know for sure which source goes with the built artifact. There’s so many things that communities can do, and kind of need to do, that that’s an area of great need right now, where they aren’t hard things to do. They just need people to think about for their community, how do they want to solv d then go do it. And that would be a huge benefit to the community but also to the world.

Omkhar Arasaratnam (15:35)
Thank you so much, Eric, for your time. That’s it for What’s in the SOSS. Stay tuned for our next episode.

Announcer (15:40)
Thank you for listening to What’s in the SOSS? An OpenSSF podcast. Be sure to subscribe to our series of conversations on Spotify, Apple, Amazon or wherever you get your podcasts. And to keep up to date on the Open Source Security Foundation community, join us online at OpenSSF.org/getinvolved. We’ll talk to you next time on What’s in the SOSS?

In this episode, Omkhar talks to Mark Russinovich, CTO of Microsoft Azure. Mark oversees the technical strategy and architecture of Microsoft’s cloud computing platform. Mark is also on the Governing Board of the OpenSSF. He’s a widely recognized expert in distributed systems, operating system internals, and cybersecurity. Mark’s also the author of the Jeff Aiken cyberthriller novels Zero Day, Trojan Horse and Rogue Code, and co-author of the Microsoft Press Windows Internals books.

• 00:36 – Mark on his role at Azure
• 01:30 – Where AI is headed and its impact on enterprises
• 04:06 – The task of teaching a machine learning model to unlearn Harry Potter
• 06:32 – The good and bad of AI hallucinations
• 10:35 – The promise of more secure open source software via AI
• 13:05 – Mark answers Omkhar’s “rapid-fire” questions: mild or spicy food, Vim, Emacs or VS Code and tabs or spaces
• 15:01 – Why aspiring software engineers should still learn to code

• Mark Russinovich’s LinkedIn page
• Press Release: OpenSSF to Support Darpa on New AI Cyber Challenge (AIxCC)

Mark Russinovich soundbite (00:01)
I think we’re still a ways away from AI completely just taking over coding. Just like, you can have people that might be able to get away with never learning how to code, and just always prompting AI. When things go wrong, knowing what’s going on underneath will make you more effective than the person that doesn’t.

Omkhar Arasaratnam (00:18 )
Hi everyone, and welcome to What’s in the SOSS? I’m your host Omkhar Arasaratnam, the general manager of the OpenSSF. Today we have a good friend of mine, Mr. Mark Russinovich, Azure CTO. What does it mean to be the Azure CTO? Let’s get into that.

Mark Russinovich (00:36)
What I tell people, the short version is, lead technical strategy and architecture for the Azure platform. There’s a lot behind that, though. I work with engineering teams. I do work on architecture. I also, as part of it, focus on security and helped co-found the Open Source Security Foundation as part of looking at how we can improve all of our industry supply chain for open source.

Omkhar Arasaratnam (00:56)
And thank you for that. It is certainly a challenging mission we’re on. Now, you buried the lead a bit. You didn’t talk about the continued work that you’re doing on Sysinternals.

Mark Russinovich (01:04)
(Laughter) Yeah, I’m also known as Mr. Sysinternals. I still do occasional side work on Sysinternals. My favorite tool, by the way, and if you haven’t seen it and your’re Windows user, is Zoomit, which lets you annotate the screen and it’s great for demos and presentations.

Omkhar Arasaratnam (01:21)
And if I recall, for those whose eyesight has suffered over the years as mine, it helps with that too.

Mark Russinovich (01:26)
Yeah, I use it frequently myself for that.

Omkhar Arasaratnam (01:28)
(Laughter) Absolutely. You know, other than the leadership that you’ve provided in security, one of the other areas that you’ve been focusing on in terms of the leading edge of our industry is in AI and machine learning. Generative AI, in particular, holds a lot of promise. Where do you see this heading?

Mark Russinovich (01:48)
First of all, it’s hard to predict where things are heading because the rise of generative AI and the capabilities that we see in it took just about everybody by surprise. And I think that there’s probably more surprises in store for us. So there’s going to be some discontinuities, but generally, the trajectory is that we’re going to have AI assistance that are our personal assistants that help us in all aspects of our life. And then in the enterprise scenarios, we’ll have AI assistants that are automating a lot of the work that today humans are required to do and helping humans make decisions in all aspects of their work across enterprises.

Omkhar Arasaratnam (02:28)
On a personal level, if you don’t mind getting into it, how have you been using AI personally? How has that helped your day? What kind of toilsome tasks has AI been able to automate for you, and where are you seeing the limits? Like, where are we not quite there yet?

Mark Russinovich (02:42)
Well, there’s basically three different ways that I use AI. One of them is if there’s a topic that I’m not that familiar with and I want to know more, rather than going to a web search for it, I just go and ask an AI assistant to teach me about it. And the nice thing is I can tell it, hey, teach me as if I’m a high school student. Teach me as if I’m an expert in this, these other holes that I might have in my knowledge. And it crafts an appropriate response at the right altitude.

The other way is summarization. So looking at lots of papers saying to the AI, summarize this paper for me. And that gives me a high-level view of what’s in it. And then I can go dive into specific sections that I want to learn more about. And then the final way is as programming, both for Sysinternals and the AI programming work that I do on the side, I use GitHub Copilot, and it has transformed the way that I code to change me into an expert at things that I don’t really know much about, like Python and PyTorch, and changed the way that I approach programming and that I really don’t want to have to type any code anymore. I want to just tell AI to type it for me.

Omkhar Arasaratnam (03:51)
Now we were chatting a little while ago. You’d actually taken a sabbatical last year. And while you had a lot of wonderful quality time with the family, you also used some of that time to start picking up on generative AI. What kind of projects do you get into at that time?

Mark Russinovich (04:06)
So I wanted to get my hands dirty during the sabbatical where I had more time on exploring something that was novel and where I’d learn a lot in the process. And so one of the things that I recognized from the early days of me looking at the rise of generative AI and the cost of these large models — where they can cost millions to tens of millions of dollars or more to train — is the issue of training data that is problematic that you discover after you finish the training of the model.

For example, copyrighted information, GDPR, poison data, you want to have a version of the model that reflects not having been trained on that without spending, again, the millions of dollars to retrain it from scratch. And so, I thought unlearning would be a fantastic tool for these kinds of scenarios. And so me and Ronen Eldan, another researcher at Microsoft, decided to see if we could get large language model, specifically Llama 7b from Meta, to forget Harry Potter because these models know Harry Potter really deeply. And so that was the kind of summer project, and we succeeded in getting Llama 7b to forget Harry Potter. So when you ask it to complete a sentence like, “Harry went back to school that fall and saw his friends…” the pre-trained model would say, “Of course, Ron and Hermione,” even though there was no other Hogwarts reference there other than basically indirect reference to school and the name Harry. That’s how deeply they are trained on Harry Potter content. Now the version that we made, where it forgets the Harry Potter universe, will say, “Went back to school to see his friends Sarah and Joe and take a class from their favorite professor,” and with some generic name.

Omkhar Arasaratnam (05:48)
That’s, that’s really cool. That’s incredibly interesting. And I think addresses some of the, at least what I’ve heard of as some concerns, especially adversarial use of improperly trained models and things of that nature. One of the things that I have a personal concern about —and it’s probably just being keenly aware of my own limitations —you’d mentioned one of the use cases that you use AI for today is in quickly coming up to speed on a subject that you’re unaware of.

What do you think about this notion of hallucinations and the possibility that the AI may not give you the most accurate information today? And I recognize it’s a point-in-time statement. How do you get by that?

Mark Russinovich (06:32)
It seems like you might have read my mind or maybe we had a conversation about this that I don’t recall. Hallucination, I think, is actually the biggest challenge for use in high-impact scenarios, which many enterprise scenarios where you’d want to apply AI are high impact, where if the model hallucinates something, you could have a big problem. Let me just also say that hallucination actually has positive attributes to it.

So when you want to be creative, when you want to write a document that actually flows nicely, hallucinations, which is just the model going off of the training distribution a bit, helps it be more creative and easier to read. Now in the kind of enterprise scenario where automating a workflow, a hallucination can cause a problem. And especially when you get into multi-agent systems, that can really pose a problem where agents might have a dozen interactions, and somewhere along the lines one of the agents hallucinates something, and the workflow continues with the others not being aware of what happened and making decisions and continuing orchestration based off of the incorrect assumptions in that hallucination.

And that by the end of the workflow, you’ve got an output that is completely wrong but you can’t tell why it’s wrong or where it went wrong. So that’s an example of where I think taming hallucination is key. And there’s a few approaches to taming hallucination, just leveraging the existing capabilities of the models, like grounding it with RAG content, like meta prompts that tell it to check its work, like having another model or itself go back and review its work with a separate prompt.

But I think we need other techniques, too. Because even while that drives down hallucinations, depending on what scenario, you’ll see hallucination rates between 5% and 20% or 30%, depending on what the model is being asked to do if it’s off its training distribution. So I think that there’s a need for AI models that detect hallucinations, that correct hallucinations, and then even just kind of old fashioned validation of what the model is producing. And code is a great example of this, where you could see the models generating code.

Now, a lot of times it’s going to be correct. A lot of times, though, it’s got bugs in it, like referencing packages that don’t exist, because it’s like, oh, there should be a package named this that does this. And so it’ll put it in. And it actually doesn’t exist. And so your code doesn’t even compile or run. So a simple validation is just compile it or run it. Are there any errors? A more sophisticated validation is don’t just compile and run it, but check to see if it actually produces output.

And the third one, actually, first-level validation is just look at it and see if there’s any problems. Second would be run it and see if it actually runs. And third one would be create unit tests for it and then validate against the unit tests. So I think there’s this need for domain specific knowledge validators with degrees of validation based on how much cost you want to spend on validation, which is relative to the impact of a hallucination.

Omkhar Arasaratnam (09:35)
Yeah, that makes a lot of sense. We’ve, I think we’ve all heard about the Canadian airline a few months ago where their AI BackChat bot had made a particular statement about a ticket that somebody had purchased that had to do with them traveling for bereavement. And it had given them incorrect information, and the Canadian court system ended up finding in favor of the passenger. I mean, it was the airline’s chat bot which they took to be as gospel.

It’s very interesting that you brought up the notion of different regression tests or unit tests that we could take when writing software. Turning the focus of how we may apply AI now to a challenge that you and I both face on a daily basis, what are your thoughts about AI helping to secure open source software, whether it be challenges like the DARPA AI Cyber Challenge that we’re helping out on or maybe in more general?

Mark Russinovich (10:35)
So AI is going to do a tremendous amount over the next few years for open source software. And there’s a few things that you can see right away that it can do, like code reviews. Look for bugs. And already it’s good enough to detect certain kinds of bugs just by that. But we can continue to fine-tune it to learn better how to spot security vulnerabilities in software as just through code reviews. The other one is through this kind of validation that I talked about.

So, and people have already started to explore this, like fuzz testing based on AI-driven fuzzer that is more sophisticated about looking for problems by expecting the code and then deciding the best way to fuzz it. So it’s kind of combining the human type of reasoning with automated fuzzing.

The other one is helping to generate the code like we talked about. But I think one thing that is going to be a great boon and can already be done today, is documenting code. And there’s tremendous amounts of code out there in Linux and elsewhere that have no documentation. The code is the documentation. So somebody that is new to the code comes and says, “I want to contribute to this, but I have no idea what’s going on. It takes me a long time to come up to speed and learn the code.”

When an AI model can inspect the code and generate comments and in the header for the function or in inline comments to describe exactly what’s going on. And while that’s not rocket science, it can save tons of hours probably of work as somebody coming up to speed with the code base. Not just that, but you have an AI chatbot that sees the code, and you can ask it questions about the code to learn how the code is working more quickly. I think that one is a very near here-and-now capability that AI can use to help security and open source contributions.

Omkhar Arasaratnam (12:24)
I think that makes a lot of sense. In fact, as we think about things like self-documenting code where previously the documentation was the code, I think use cases like that, to the point that you made earlier, also provide almost a semi-automatic method, right?

So even if the quality isn’t right there today, and even if there’s a slight hallucination or imagination in terms of the LLM’s inference of what the code’s supposed to do. Presumably, you have enough familiarity with the syntax of the language that you would be able to pick up correctness of that interpretation. But even still the error rate is probably lower than you having to manually grok through all the code yourself. I see that.

I think we’re gonna move into the rapid-fire section now, Mark. And with any of these questions, I’m gonna give you an either-or but the reality is there could be a third answer, which is, “No, Omkhar, I actually, I feel this way.” So I think the first one is quite binary, but spicy or mild food?

Mark Russinovich (13:23)
Spicy.

Omkhar Arasaratnam (13:25 )
All right. You know, some of our other guests have been leaning mild, and we have a dinner coming up and I’m going to find someplace with spicy food for you. I think I know the answer to this, but I’m going to ask it anyway. Vim, Emacs or VS Code?

Mark Russinovich (13:39)
VS Code, but if it is, I think that the true question here, the pure question is Emacs or Vim or VI?

Omkhar Arasaratnam (13:48)
You know, I’d like to say that, but I’ve been messing around with VS Code lately, and it’s not just because you’re on this recording, Mark. I’m starting to dig VS Code.

Mark Russinovich (13:57)
Now, I love VS Code, that’s what I use. But prior to VS Code, and there was very much the Vim camp and the Emacs camp, I was strongly in the Emacs. In fact, I used Emacs until the late 90s, before I started to use Microsoft Visual C, its own editor. Like, I just don’t understand the VI people at all, I’m just baffled.

Omkhar Arasaratnam (14:18)
Well, I’m definitely a VI guy and you know, Emacs is a great operating system that happens to have an editor attached to it. (Laughter) Last one for the rapid –

Mark Russinovich (14:31)
I still have trouble quitting VIs.

Omkhar Arasaratnam (14:33)
(Laughter) I presume you can get Emacs key bindings for VS Code.

Mark Russinovich (14:38)
You know what I grew out of Emacs key bindings? But I mean Emacs key bindings, and by the way, I just don’t know why Emacs key bindings aren’t the default for shells either. The key bindings for shells that come default are just ridiculous.

Omkhar Arasaratnam (14:51)
They are. They are. Tabs or spaces?

Mark Russinovich (14:54)
I don’t really care that much. That’s one where I’m like, whatever, as long as it formats correctly visually.

Omkhar Arasaratnam (15:01)
Makes sense as far as it’s consistent, I guess. So to close us out, Mark, what advice do you have for somebody entering our field today? We’ve both been in the field for quite a while. We’ve seen a lot of stuff. A lot of stuff has changed with that wealth of knowledge. How would you guide somebody that’s entering our field today?

Mark Russinovich (15:18)
Entering our field meaning software engineering. I guess the elephant in the room aspect of that question is should they learn to code or not? Is that what’s going to happen? Do they need to? And I would actually say, yes, go ahead and learn how to code. And I’d say that for a couple of reasons. One, it’s a way to give you critical thinking about an end-to-end process from the high-level objective down to actually how you implement it.

And that translates to other domains as well. And even if AI is going to be doing some of the low-level lifting, you still need to have the high-level, how things fit together and flow that you’re going to get as you learn to code. The other reason is that I think we’re still a ways away from AI completely just taking over coding. And just like you can have people that might be able to get away with never learning how to code and just always prompting AI, when things go wrong, knowing what’s going on underneath will make you ten times more effective than the person that doesn’t. And so just, you know, that reason, but certainly the first one that I mentioned, I would say you’re not wasting your time by learning how to code.

Omkhar Arasaratnam (16:31)
I think that’s great advice for people entering software engineering today. Last question for you. What’s your call to action for our listeners? What would you have them do immediately following this show?

Mark Russinovich (16:41)
Go check out all the learning materials that the Open Source Security Foundation offers and learn how to secure your open source supply chains.

Omkhar Arasaratnam (16:48)
Thanks very much, Mark. And I can’t say, I can’t thank you enough for being a guest on our show. Look forward to catching up with you shortly and thank you for joining What’s in the SOSS?

Mark Russinovich (17:00)
Yeah, thanks for having me. I’m a great conversation.

Announcer (17:02)
Thank you for listening to What’s in the SOSS? An OpenSSF Podcsat. Be sure to subscribe to our series of conversations on Spotify, Apple, Amazon or wherever you get your podcasts. And to keep up to date on the Open Source Security Foundation community, join us online at OpenSSF.org/getinvolved. We’ll talk to you next time on What’s in the SOSS?

In this episode, Omkhar talks to Christoph Kern, Principal Software Engineer in Google’s Information Security Engineering organization. Christoph helps to keep Google’s products secure and users safe. His main focus is on developing scalable, principled approaches to software security.

• 00:42 – Christoph offers a rundown of his duties at Google
• 01:38 – Google’s general approach to security
• 03:02 – What Christoph describes as “stubborn vulnerabilities” and how to stop them
• 06:42 – An overview of Google’s security ecosystem
• 10:00 – Why memory safety is so important
• 12:23 – Solving memory safety problems via languages
• 16:23 – Omkhar’s rapid-fire questions
• 18:28 – Why Christoph thinks this may be a great time for young professionals to enter the cybersecurity industry

• Blog: Tackling Cybersecurity Vulnerabilities Through Secure by Design
• Report: Secure by Design: Google’s Perspective on Memory Safety
• White House Press Release: Future Software Should be Memory Safe
• Blog: OpenSSF Supports White House’s Efforts to Build More Secure and Measurable Software
• Research: Developer Ecosystems for Software Safety: Continuous Assurance at Scale

Christoph Kern soundbite (00:01)
The White House just put out a memo talking about memory safety and formal methods for security. I would have never believed this a couple of years ago, right? It’s becoming a more important table-stakes. It might be actually a very interesting time to get into this space without having to sort of swim upstream the whole time.

Omkhar Arasaratnam (00:17)
Hi everyone, it’s Omkhar Arasaratnam. I am the general manager of the OpenSSF and the host of the What’s in the Sauce? podcast. With us this week, we have Christoph Kern. Christoph, welcome.

Christoph Kern (00:30)
Thank you, Omkhar, for having me. It’s an honor to be here, and I’m looking forward to this conversation.

Omkhar Arasaratnam (00:34)
It’s a pleasure, Christoph. So, background. Tell us a little bit about where you work and what you do.

Christoph Kern (00:42)
I’m a principal engineer at Google. I’ve been there about 20 years and a bit, so quite a long while. I work in our information security engineering team, which is basically product security. So we look after the security posture of all the services and applications that Google offers to our users and customers. And a lot of that time, I focused on essentially trying to figure out scalable ways of providing security posture across hundreds of applications and to a high degree of assurance at that.

Omkhar Arasaratnam (01:13)
Well, I think if memory serves, we spoke a couple of times when I was at Google, a couple of times after Google. I mean, securing Google full stop, no caveat, no asterisk. That’s a lot of stuff. So what are some of the ways that y’all have thought about securing all the things within Google? I presume you just don’t have a fleet of security engineers that descend upon every project.

Christoph Kern (01:38)
Right, exactly. To make this scale, you really have to think about invariance that you want to hold for every application, and also classes of common defects that you want to avoid having in any of these hundreds of applications. And the traditional way of doing this has been to try to educate developers and to use sort of after the fact code reviews and testing and penetration testing and, you know, In our experience, this has not actually worked all that well. And we, over the years, sort of realized that we really need to think about the environments in which these applications are being built. And so usually there’s like many applications that are fairly similar, right? Like we have hundreds of web front ends and they have many aspects of their threat model that are actually the same for all of them, right?

Cross-site scripting, for instance, is an issue for every web app, irrespective of whether it’s a photo editor or a banking app or an online email system. And so we can kind of take advantage of this observation to scale the prevention of these types of problems by actually building that into the application framework and the underlying libraries and the entire developer ecosystem, really, that developers use to build applications. And that has turned out to work really quite well.

Omkhar Arasaratnam (02:53)
Now, in the past, you’ve referred to this class of stubborn vulnerabilities. Can you say a little bit more about stubborn vulnerabilities and what makes them so stubborn and hard to eliminate?

Christoph Kern (03:02)
Yeah, there’s a list of vulnerabilities that the folks who make this common weakness enumeration, the CWE, put out. So they’ve been putting out the, sort of, top 25 most dangerous vulnerabilities list for years. And recently, they started also making a list of the ones that consistently appear near the top of these lists over many years. And those are then, evidently, classes of problems that are in principle well understood.

We know exactly why they happen and what the, sort of, individual root cause is, and yet it turns out to be extremely difficult to actually get rid of them at scale and consistently. And this is then evidenced in the fact that they just keep reappearing, even though there’s been guidance on how to, in principle, in theory, avoid them for years, right? And it’s well understood what you, in principle, need to do. But applying that consistently is very difficult.

Omkhar Arasaratnam (03:52)
Software engineer to software engineer. What’s the right way of fixing these vulnerabilities? I mean we’ve thrown WAFs at them, we’ve taken all kinds of input validation techniques. What would you recommend? Like, how does Google stop those?

Christoph Kern (04:06)
I think the systemic root cause for these vulnerabilities being so prevalent is that there is an underlying API that developers use that puts the burden on developers to use it correctly and safely. Essentially, all of these APIs that are in this class of injection vulnerabilities consume a string, a sequence of characters, that is then interpreted in some language. It could be SQL in the case of SQL APIs. And then leading to SQL injection or JavaScript embedded in HTML in the case of XSS, right?

And the burden is on developers to make sure that when they write code, they assemble strings that are then passed to one of those APIs, that the way they’re assembled is following secure coding guidelines. In this case, questions of how you would escape or sanitize an untrusted string that’s embedded in HTML markup, for instance. And you have to do this hundreds of times over in a large application because there’s lots of code in a typical web app that assembles smaller strings into HTML markup that is then shipped to a browser and rendered. And it’s extremely difficult to not forget in one of those places or apply the wrong rule or apply it inconsistently. And this is just really, really difficult, right? And this is why those vulnerabilities keep appearing.

Now, to get rid of them, what we found, the only thing that actually works, is to really rethink the design of the API and change it. And so we just went ahead effectively and changed the API so it no longer consumes a string, but rather consumes a specific type that is dedicated to that API and essentially holds the type contract, the promise, that its value is actually safe to use in that context. And then we provide libraries of builders and constructors that are written by experts, by security engineers, that actually follow safe coding rules.

And then as an application developer, you really don’t have the opportunity to incorrectly use that API anymore, because the only way to make a value that will be accepted by the API is to use those expert-built libraries, right? And then effectively the type system of the language just glues everything together. It then also makes sure that when a value is constructed in one module, there’s like some module, maybe even in a backend, that makes HTML markup or a snippet of HTML markup that’s shipped to a browser and then embedded into the DOM in the browser, the type system ties those two places that are otherwise very difficult to understand because they’re very far away. They might be written by different teams. The type system ties those two things together and actually makes sure that the underlying coding rules are actually followed consistently and always.

Omkhar Arasaratnam (06:42)
Other than SQL injection and cross-site scripting, can you provide any other practical examples or maybe just to reflect back on how this has shown up in the security properties of Google products? Has this been broadly adopted by Google developers? Has there been some resistance? Can you talk a little bit about that from a developer experience perspective?

Christoph Kern (07:06)
The way Google’s developer ecosystem evolved for different reasons, really for productivity and quality reasons, the design of that ecosystem actually helped us greatly, right? So Google has this single monorepo where all the common infrastructure, including compilers and toolchains and libraries, are provided by central teams to all the application developers. And there’s really no practical way for somebody to build code without using that. It would be just very expensive and outlandish to even think of. And so if we build these things into those centrally-provided components, and we do it in a way that doesn’t cause undue friction, most people just don’t even notice.

They’ll just use a different API to make strings that get sent to a SQL query, and it just works, right? If it doesn’t work, then they’ll read the document and say, “Oh, this API wants a trusted SQL string instead of a string, so I’ll have to figure out how to make that and here’s the docs.” And once they figure this out once, they’re on their way. And so we’ve actually seen fairly little resistance to that. And of course, we’ve designed it so that it’s easy to use, right, otherwise we would see complaints.

One interesting thing we’ve done, I think that actually sort of in hindsight helped a lot is that we’ve chosen ourselves to make the maintainers and developers of these APIs, the security engineers, the first line customer support, so to speak, for developers using them. So we have this internal, sort of,  equivalent of Stack Overflow, where people can ask questions. And our team actually monitors the questions about these APIs. And that inherently requires us to, so we don’t get drowned in questions or problems, to design them and iterate them on an ongoing basis to make them easier to use. So that in almost all use cases, developers can just be on their way by themselves without needing any help. And so that’s really helped to sort of tune these APIs and figure out their corner cases in their usability and make them both easy to use and secure at the same time.

Omkhar Arasaratnam (09:00)
That’s a wonderful overview. And just to summarize, by baking these kind of protections right into the tooling that the developers use, they don’t have to waste mental effort on trying to figure out how to sanitize a string. It’s already there. It’s already present. If you have a new developer coming in from the outside who maybe doesn’t have experience with using these trusted types, the actual API that they would call won’t accept a raw string. So they’re forced into it.

And I guess the counterbalance to ensure that you have a usable API for your tens of thousands of developers within Google is that essentially the people that write this also have to support it. So it’s in their best interest to make it as friction-free as possible for the average developer inside of Google. I think that’s, that’s excellent.

We’re going to switch gears. Google recently published a paper on memory safety of which you were one of the co-authors. So let’s talk about memory safety a little bit. Can you explain to the listeners why it is important?

Christoph Kern (10:00)
Yes, I think memory safety essentially, or the memory safety problem, is essentially an instance of this sort of problem we just talked about, right? It is due to the design in this case of a programming language or programming languages that have language primitives that are inherently unsafe to use, where the burden is on the developer to make sure that the surrounding code ensures the safety precondition for that primitive. So for instance, if you’re dereferencing a pointer and C or C++, it’s your responsibility as a programmer to be sure that anytime execution gets to that point, that pointer still points to validly allocated memory, and it hasn’t been deallocated by some other part of the code previously before you got here, right?

And so if that was the case, it would lead to a temporal safety violation because you have like a use-after-free, for instance, vulnerability. Similarly, when you’re indexing into an array, it’s your responsibility to make sure that the index is in bounds and you’re not reading off the end of the array or previous to the beginning. Otherwise, you have a spatial safety issue.

And I think what makes memory safety particularly stubborn is that the density of uses of potentially unsafe APIs or language features for memory safety is orders of magnitude more than some of these other vulnerability classes. So if you look at SQL injection, in a large program you might maybe have tens of places where the code is making a SQL query versus in a large C program or C++ program, you’ll have you know, thousands or tens-of-thousands of places that dereference pointers, like every other line of code literally is a potential safety violation, right? And so with that density of potential mistakes, there will be mistakes.

There’s absolutely no way around it. And that sort of is borne out by experience in that code that is written in an unsafe language tends to have its vulnerabilities be memory safety vulnerabilities.

Omkhar Arasaratnam (11:50)
Many languages nowadays, be it Python, JavaScript, or for lower level software development, Golang or Rust, all proclaim these memory safety properties and are often referred to with absolutes, as in solving an entire class of problem. I think you and I have been around software engineering for long enough that such bold claims are often met with a bit of cynicism. Can you talk about how these languages are actually solving these entire classes of memory safety problems?

Christoph Kern (12:23)
Yes, I think the key to that is that if you use them to good effect, you can design your overall program to enable modular reasoning about the safety of the whole thing. And in particular, design the small fragments of your code that do need to use unsafe features. So in Rust, it might be that you might need a module. For instance, if you want to implement a linked list, a doubly linked list, you need unsafe, right? Or you need reference counters.

But what you can do is write this one module that uses potentially unsafe features so that it is self-contained and its correctness and safety can be reasoned about without having to think about the rest of the program. So basically when you write this linked list implementation, for instance, in Rust, you will write it in a way such that the assumptions it needs to make about the rest of the program are entirely captured in the type signatures of its API.

And you can then validate by really thinking about it hard, but it’s a small piece of code, and you might get your experts in unsafe Rust to look at it, that module will behave safely for any well-typed program it is embedded in, right? And once you are in that kind of a place, then you will get actually a very high assurance of safety of the whole program. Just out of the fact that it type checks, right?

Because the components that use unsafe features are safe for any well-typed caller, and the rest of it is inherently safe due to the design of the language, there really is very little opportunity for a potential mistake. And that’s, I think, again, borne out of practice in that, like, in Java or JVM-based languages, memory safety really is a very rare problem. We’ve had some buffer overflows in, I don’t know, like, image parsers that use native code and stuff like that.

But it’s otherwise a relatively rare problem compared to the density of this type of bug in code that’s written in a language where unsafety is basically everywhere across the entire code base.

Omkhar Arasaratnam (14:23)
So, I mean, the obvious thing seems to be, OK, let’s wave our magic wands and rewrite everything in a memory-safe language. Obviously, things aren’t that simple. So what are the challenges with simply shifting languages, and how do you address large legacy code bases?

Christoph Kern (14:39)
Unless there is some breakthrough in like ML-based automated rewriting, I think we have to live with the assumption that the vast majority of C++ code that is in existence now will keep running as C++ until it reaches its natural end of life. And so we have to really think about,  as we make this transition to memory safety, probably over a span of like decades, really, where do we put our energy to get the best benefit for our investments in terms of increased security posture?

And so I think there’s a couple of areas where we can look at, right? So for instance, there’s some types of code that are particularly risky, it’s most likely very valuable to focus on those and replace them with a memory-safe implementation. So we might replace an image parser that’s written in C or C++ with one that’s written in Rust, for instance.

And then beyond that, if we have a large C++ code base that we can’t really rewrite feasibly and we can’t just stop using it because we need it, we’ll have to look at incremental ways we can improve its security posture. And there is some interesting approaches for instance, we for instance, I think are somewhat confident that it’s possible to achieve a reasonable assurance for spatial safety in C++ through approaches like safe buffers by basically adding runtime checks.

For temporal safety, it’s much more difficult. There are some ideas, you know, there’s like some work in Chrome for instance, using these wrapper types for pointers called MiraclePtr. There might be some hardware mechanisms like MTE. And there’s a lot of trade-offs between cost and performance impact and achievable security improvement that will really probably take some time to shake out. But you know, we’ll get there at some point.

Omkhar Arasaratnam (16:23)
I’m glad to hear that the problem is at least tractable now. Moving over to the next part of our podcast Christoph we’re gonna go through a series of rapid-fire questions. Some of these will have one or two options, but the last option is always, “No Omkhar. Actually, I think it’s this.” So we’re gonna start off with one that’s quite binary, which is spicy or mild food.

Christoph Kern (16:45)
I don’t think it’s actually that binary. In the winter, when it’s cold out, I tend to gravitate to more like sort of, you know, savory  German type cooking. That’s my cultural background. And then in the summer, I’m more leaning towards the like zesty, more spicy flavors, you know, so it maybe varies throughout the year.

Omkhar Arasaratnam (17:02)
Interesting. For me I tend to gravitate to spicy as a default, but then when the weather gets cooler, I find that spicy is even higher priority for me as it helps me to feel a bit warm. OK, the next one’s a bit controversial one based on some previous guests: VI, VS Code, Emacs?

Christoph Kern (17:22)
For me, it really depends on what I’m working on. I’ll use whatever code editor that’s most well supported for the language. So for like, say Rust it might be VS Code, but then in Google we have our own thing that’s supported by a central team. My muscle memory is definitely VI key bindings, but I actually, at the age of like 45 or something, I decided to finally learn Emacs so I could use org mode, but I do use it with a VI key binding, so.

Omkhar Arasaratnam (17:48)
Excellent. Tabs or spaces?

Christoph Kern (17:51)
You know, I haven’t thought about that in a long time. I think many years ago, the language platform teams at Google basically decided that all code needs to be automatically formatted. And so basically, you do whatever the thing does and what’s built into the editors. And it never really occurs even as a question anymore.

Omkhar Arasaratnam (18:09)
Makes it easier. One less thing to worry about. To close it out, what advice do you have for somebody entering our field today, somebody that’s just graduating with their undergrad in comp sci or maybe just transitioning into an engineering field from another field that’s interested in tackling this problem of security?

Christoph Kern (18:28)
You know, maybe it’s actually a particularly good time to get into this field. I think I’ve been very fortunate to have worked in an organization that really does make security a priority. And so usually when you approach somebody you want to work with on improving security posture of a product, it’s rarely a question of whether or not this should be done at all.

You don’t have to justify your existence, right? It’s really usually questions about the engineering of exactly how to do it. And that’s a very nice place to be, right? You’re not constantly arguing to even be there, right? At the table. And I think maybe I’m a little hopeful that this is now changing for other organizations where that’s not so obvious, right? Like, you hear a lot more talk about security and security design.

I mean, the White House just put out a memo talking about memory safety and formal methods for security. It was like, I would have never believed this if you’d told me this a couple of years ago, right? So I think it’s becoming a more important and sort of obvious table-stakes part of the conversation. And so it might be actually a very interesting time to get into this space without having to sort of swim upstream the whole time.

Omkhar Arasaratnam (19:34)
We’ve talked about stubborn vulnerabilities, safe coding, memory safety. What is your call to action for our listeners, having absorbed all this new information?

Christoph Kern (19:44)
I think it is well past time to no longer put the burden on developers and really view these problems as systemic outcomes of the design of the frameworks and application frameworks and production environments, the entire developer ecosystem. Like in the article we recently published, we kind of put this as t he security posture is an emergent property of this entire developer ecosystem, and you really can’t actually change the outcome by not focusing on that and only blaming developers. It’s not going to work.

Omkhar Arasaratnam (20:18)
Christoph, thank you for joining us, and it was a pleasure to have you. Look forward to speaking to you again soon.

Christoph Kern (20:23)
Thank you, yeah, it was a pleasure to be here.

Announcer (20:25)
Thank you for listening to What’s in the SOSS? An OpenSSF podcast. Be sure to subscribe to our series of conversations on Spotify, Apple, Amazon or wherever you get your podcasts. And to keep up to date on the Open Source Security Foundation community, join us online at OpenSSF.org/getinvolved. We’ll talk to you next time on What’s in the SOSS?

In this episode, Omkhar talks to Vincent Danen, Vice President of Product Security at Red Hat, responsible for security and compliance activities for all Red Hat products and services. He’s also on the Governing Board of the OpenSSF. Vincent has been involved with open source and software security for over 20 years, leading security teams and participating in open source communities and development.

• 00:39 – Vincent shares his background in security and responsibilities at Red Hat
• 03:36 – The importance of maintaining a sense of calm during security incidents
• 05:18 – Omkhar and Vincent discuss their experiences learning about the infamous Heartbleed Bug
• 09:05 – Vincent offers advice on how to address vulnerability management and the importance of trusting your vendors
• 11:34 – Not every threat or vulnerability requires swift and immediate action
• 12:46 – Pitfalls organizations should avoid in vulnerability management
• 15:40 – Vincent answers Omkhar’s “rapid-fire” questions: mild vs. spicy food, text editor or choice and tabs vs. spaces
• 16:32 – Advice Vincent would give to aspiring security professionals and the importance of being open-minded

Vincent Danen soundbite (00:01)
I want somebody to come out and create a bug scanner. Go tell me all the bugs that are in the software that I have. Not the security issues but the bugs. Because that list is gonna be way longer. And I guarantee you that some of those bugs are far more impactful for you as a user than some of these security issues.

Omkhar Arasaratnam (00:17)
Welcome to What’s in the SOSS? I’m your host Omkar Arasaratnam and with me this week we have fellow Canadian Vincent Danen. Vincent, how are you doing my friend?

Vincent Danen (00:28)
Good, Omkhar. How are you?

Omkhar Arasaratnam (00:29)
I’m doing just dandy. So for our audience, I would love to do a quick intro. Why don’t you give them your name, title and what you do?

Vincent Danen (00:39)
Sure, so Vincent Danen, Vice President of Product Security at Red Hat. I just actually celebrated 15 years at Red Hat a month ago.

Omkhar Arasaratnam (00:47)
Congratulations.

Vincent Danen (00:49)
Thank you. Prior to that, I was at Mandriva for those long-time listeners who know the history of Linux. I was doing security work for them for about eight years. So I’ve been knee-deep in open source security for over 20 years now, and it just makes me feel old.

Omkhar Arasaratnam (01:04)
You’re, you’re an O.G. as the kids say, and let me let me drop some street cred: You know, I used to be a Red Hat certified engineer in Red Hat 7.2 And I didn’t say RHEL, I said Red Hat 7.2 because I’m an old guy, too.

Vincent Danen (01:20)
Yeah, well you got some street cred for sure.

Omkhar Arasaratnam (01:23 )
That’s a really cool title. Sounds incredibly important. Can you give our listeners a bit of an overview as to, you know, being the person in charge of product security? What does that mean at Red Hat?

Vincent Danen (01:35)
Yeah, I mean, product security at Red Hat has, I mean, that name kind of gives it away, right? It is about the security of our products. Our remit is effectively all of the proactive/reactive security concerns around our portfolio of products. So if you think about it, that, you’d mentioned RHEL, that’s one. OpenShift, Ansible, Middleware, EAP, a ton of products. And of course, we like to support these things for a very long time. So multiple versions of the same product. So effectively, my team ingresses a number of vulnerability information. So new CVEs are discovered, either they’re reported directly to us, either under embargo or not.

We get information from CVE, other reporters. You’re familiar with the Linux distros mailing list. So we get information that way as well. So we’re kind of ingressing all of these vulnerabilities. We triage them and determine their effectiveness or effectedness to our products. And then we kind of go through the whole process of rating the vulnerability in terms of its severity, how it’s impacted in the products.

And then kind of just follow that through with engineering who are going to fix these things and test them, release them out to our customers. We provide a ton of information about CVEs because customers really like to know, “ What does this thing do and should I be sweating or is this okay?” We also focus a lot on, say, our internal build pipelines, how we curate the open source, how we interact with upstream. We do a lot on the compliance front as well. So it’s like a very robust view of security, kind of from front to end for all of our products.

Omkhar Arasaratnam (03:14)
That sounds like an incredibly broad scope. And at some point, you have to tell the listeners when you have time to sleep It sounds like you’re on all the time, like most of us are in cybersecurity.

Vincent Danen (03:25)
Yes, although I do sleep and actually sleep pretty good. One of the benefits of having a fantastic team to work with. So I don’t have to worry about everything. I have a great team to work with,  and they do a lot of the heavy lifting.

Omkhar Arasaratnam (03:36)
That’s wonderful to hear. And I certainly get that. Back in the day, when I first started in cybersecurity, incident response was one of the things that I had. And an old manager of mine often said, whenever we have to deal with an incident, there should be a sense of urgency, but it shouldn’t be panic. And what I’m hearing from you is you’ve got a team that’s really set up to handle that sense of urgency properly without the panic that could be a negative force.

Vincent Danen (04:03 )
It’s actually interesting that you mentioned that because one of our goals is to, particularly with a lot of these named vulnerabilities, so those have been a phenomenon for at least the last dozen years. Because Heartbleed actually just celebrated a 10-year anniversary, I think it was earlier this week or last week.

Omkhar Arasaratnam (04:19)
Yeah, I didn’t get a cake, but I remember.

Vincent Danen (04:22)
I didn’t get a cake either, but I do remember when it happened. I was hip-deep in that as well. But one of our goals is to maybe quell that sense of panic that our customers or other people in the industry have. So we really try to take a look at these vulnerabilities from the perspective of what does it actually do and do I need to be worried? And then convey that information as clearly and concisely as possible to our customers so that we’re not seeing undue panic.

I mean, there are certain things we should absolutely be panicking about, right? Like, these are things where if we produce a patch, I mean, we want you to apply it as quickly as possible. There is that sense of urgency. But when we’re looking and analyzing these things, I kind of think of it more akin to a firefighter. If you’re in the middle of a blaze trying to put that fire out and you’re panicking, you’re not going to be very effective, right? So we want to be as kind of calm, cool, collected, measured, as clear as possible.

Omkhar Arasaratnam (05:18)
The analog that I use often to describe that same concept: A neighbor of mine is a paramedic, and one of the things he pointed out to me was you’ll notice that paramedics never run at an accident scene. And, It’s not, I mean they certainly move with urgency, but they don’t run because they don’t want to cause more harm through acting in a non-stoic and measured manner by kind of running, running into the proverbial scene. Of course, we see that on TV all the time, but you know, TV is not reality.

I do want to come back to the Heartbleed thing for just a moment. It’s said that when you look back on your life, there are certain key moments that everybody remembers. And for those that were maybe the generation prior to us, it was the JFK assassination. For our generation to betray our age to the viewers — or the listeners — it was probably the Challenger explosion. It was probably, you know, 9/11.

I have that indelible kind of memory of Heartbleed, and the reason I have that indelible memory is I have very poor discipline when it comes to turning off work. And I wish I had better discipline. My wife also wishes I had better discipline. But ten years ago, I had promised my wife and kids were going to go to Hawaii for the first time. We were in Maui, and this was still back in the days when everybody had a Blackberry. I left my Blackberry at home turned off, and we were on the beach in Maui, and I came back in and I turned on the TV. And I was like, “Oh boy, what a day to be disconnected from work.” What was, what was your experience?

Vincent Danen (07:04)
First, I’ll say you were one of the lucky ones to be disconnected from it.

Omkhar Arasaratnam (07:07)
By total coincidence.

Vincent Danen (07:10)
Yeah, yeah. No, the thing that sticks out for me the most, there’s two. One is that our Red Hat Summit was about a month later, and that was all anyone wanted to talk about was Heartbleed. And that’s not what I was there for. Right, so that was interesting and that kind of sticks in my head. The other one was I actually remember my mother phoning me, and she’s completely, sorry Mom if you hear this, completely computer illiterate. Right? I have to go to her house to help her fix the remote because she did something to the TV, and it’s literally one button, right? But she phones me, and she’s like, “Hey, I heard about this computer thing on the radio.”

And I was like, “What are you even talking about?” A, you picked up on this,  and you knew it was somehow relevant to me, which was shocking. And then secondly, it was like, it was on the radio. And to that point, I had never heard, like the local news, I had never heard of a security issue in software ever getting that kind of airplay. This thing was really noisy.

Omkhar Arasaratnam (08:05)
My family non-technical analog is my dad, and again, apologies to my dad if he hears this. Like, my dad wants to send me articles about, you know, the latest scam that’s out there and, you know, don’t get title scammed out of your house and stuff like that and the odd meme and not do much else. But when dad starts sending me stuff that’s like, “Hey, do you know about this?” Yeah, then then it really puts things in perspective as to how this affects society.

So I think the, I mean, the conclusion in all this that I’m drawing to is vulnerability management is hard to do properly. And being able to kind of filter signal and noise and get down to something that’s actually actionable shouldn’t be based on whether Vincent’s mom hears it on the radio or Omkhar’s dad finds it on a news website. What are some key considerations for our listeners? What should they be thinking about when they start thinking about vulnerability management?

Vincent Danen (09:05)
That’s a great question because it’s something I think about a lot. I actually talk about it a lot as well. The caveat here being I work for Red Hat, and so this is my day job, right? And so I deal with a lot of customers who have a lot of questions, particularly about this topic, right? So the first thing that I would say is you have to know your vendor before you pick them. There’s a fundamental trust factor that comes into play with your vendor. And I’m not even talking just from a security perspective, right? Like, you have to be able to trust the software that you’re using or the vendor who puts it out, right? And there’s a couple of reasons for that.

Vendors typically will assess a vulnerability themselves, right? I know we have things like NVD and OSV and, like, other kind of CVE aggregation systems, but a vendor typically rates the severity of a vulnerability in terms of their product. I’ve heard in the past, I haven’t heard it recently, but somebody actually accused me of lowballing a vulnerability because I didn’t want to have to fix it. I was like, well, that’s really weird. You know, like, you trust me to run your workloads, to do all this work that you’re doing, to build value in your business, right? To run your platforms and whatnot. But you’re not going to trust me when I say that this vulnerability doesn’t matter for these particular reasons, right? Which is a little weird. You trust me for one thing, but you don’t trust me for the other.

Omkhar Arasaratnam (10:20)
It is strange.

Vincent Danen (10:22)
So, I mean, there is a trust relationship with your vendor, and I think that extends to when they say something is impactful or not, you have to kind of believe that, right? And it’s really important because I was looking at a, I think, it was a GRUB vulnerability a couple months ago.

Omkhar Arasaratnam (10:39)
The Bootloader?

Vincent Danen (10:41)
Yeah, the Bootloader. And when I was looking at the CVSS ratings for that GRUB vulnerability, we had it rated one way. I think Debian had it rated a different way. SUSE rated it the same. F5 rated it like really low, right? In the context of their environment and how accessible it is in their devices. Right? So I mean, they rated it in the context of the way that they use it and kind of the environment around it. And that’s typically what vendors do. So I wouldn’t sit there and say, “Yeah, go look at, you know, how Debian writes stuff, and that’s exactly how it works for Red Hat.” Because it’s not true.

Omkhar Arasaratnam (11:16)
And presumably there may be some, I mean, it could be mitigations in your build chain that you include. It could be, to your point, is this an appliance? And is this something that’s a materially accessible vulnerability remotely or something of that nature based on your usage?

Vincent Danen (11:34)
A hundred percent. RHEL being an operating system, and you can do whatever you want with it, we don’t know. OpenShift is more of an appliance platform and it’s built a very specific way, and there’s a limited amount that you can do with it, right? In terms of how you’re messing around with the different components. The same component might be present in both. In RHEL, I can use it however I want. I can use it as part of my own application, I can use it on the system, whatever. In OpenShift, that might be one very specific piece of plumbing with one very specific use that’s either the vulnerable code isn’t being used, or there’s literally no way for a user or an attacker to access it. So the fact that the vulnerability is there, I mean, okay, yes, technically it’s there, but in any possible use of OpenShift, it’s not going to be material. You’d have to break OpenShift really, really bad in order to even access it, and then you’ve got bigger problems.

Omkhar Arasaratnam (12:30)
Absolutely. So the notion of reachability or exploitability is obviously key and a huge part of how people should be triaging these vulnerabilities as they do come up. What are some other pitfalls that people should avoid in vulnerability management?

Vincent Danen (12:46)
Well, I think one of them is just the notion that, you know, as we were discussing here, that every vulnerability matters, right? Most of them don’t. So I kind of look at it as like, don’t sweat the fact that your scanner is showing up a bunch of low or medium or moderate vulnerabilities. That’s probably fine, right?

I would worry more about the critical and important or high vulnerabilities that it’s showing because those are the ones that are more likely to be exploited and are more likely to be damaging if they are. Interestingly enough, Red Hat produces a risk report on an annual basis. Last year, out of the, what is it, about 1,600 vulnerabilities that impacted us, only 1.2 % were actually known to be exploited. The prior year was at 0.4%. Now the majority of those are in those critical and important vulnerabilities. And there was like a handful in the moderate levels, like, I think three.

So I think about it like about a thousand moderates and two of them are exported. Like, why are we panicking over the other 998 that are effectively immaterial and not actually being used? Now, a little plug for Red Hat here is when we find out that something is being exploited, that kind of raises it to our level of, “OK, this is actually an issue.” And if we hadn’t fixed it already, we’re going to fix it. So we’ll always proactively do the criticals and the importance because it could be any one of those that could be exploited, cause damage.

But we’re not worrying about all of them because, I mean, frankly, I actually had this thought the other day. Because I hear a lot about these vulnerability scanners, right? And they’re very noisy. Sometimes they’re not very accurate and they show a lot of things. I want somebody to come out and create a bug scanner. Go tell me all the bugs that are in the software that I have. Like not the security issues, but the bugs. Because that list is gonna be way longer. And I guarantee you that some of those bugs are far more impactful for you as a user than some of these security issues, particularly the low vulnerabilities.

Omkhar Arasaratnam (14:44)
Absolutely. I mean security properties of a program are essentially an aspect of quality. And looking at them holistically in terms of all quality issues is an interesting view. One of the ways  I’ve described this in the past is security is like this infinite problem space, and if you don’t have a way of reasoning over what’s actually important, you’re going to be chasing down rabbit holes forever and a day. And some of the work that we’re actually doing in the Security Toolbelt group within the OpenSSF is around doing these kind of threat modeling and risk assessments to really pick up on, “Look, OK, in the fullness of time, we should address all the things, but what do I need to address now? And how do I need to address it?”

Vincent with all that said, I think we’re going to jump into the rapid-fire round. Are you ready?

Vincent Danen (15:39)
Absolutely.

Omkhar Arasaratnam (15:40)
All right. Spicy or mild food?

Vincent Danen (15:44)
Mild. Although my mother likes spicy food, and I think that turned me off as a youngster. I’m starting to get back into handling a little bit of heat.

Omkhar Arasaratnam (15:51)
I’d like to be the Sherpa on your journey.

Vincent Danen (15:54)
Thank you.

Omkhar Arasaratnam (15:55)
Text editor of choice: Vim, VS Code, Emacs or other. That’s an option as well.

Vincent Danen (16:01)
Vim.

Omkhar Arasaratnam (16:03)
Yes! All right. You know, you, you slipped on the spicy food. You redeemed yourself on the text editor. This next one is incredibly influential: tabs or spaces?

Vincent Danen (16:14)
I’m a spaces guy.

Omkhar Arasaratnam (16:15)
Yes! Alright. We, we will continue to be good friends, Vincent

Vincent Danen (16:20)
Awesome!

Omkhar Arasaratnam (16:21)
In closing out, thank you so much for all your great advice, but for somebody that’s entering our field today, what would you tell them? What sage wisdom would you impart?

Vincent Danen (16:32)
Probably two things. One, as you and I are both aware, I’ve been here for a long time. It’s very easy to be burnt out and stressed out and everything else by this work. Not to take anything away from the fantastic firefighters and paramedics and everything else, but it feels a lot like first responder-type work. So I say, take care of yourself first. If you don’t take care of yourself, you’re no good to anybody else. And we’re here to be good to other people, right?

And then the other part I would say that I think is actually really, really important is for people to stay curious. Right? If we think about this XZ Backdoor that we just had recently, it was curiosity that found it. I mean, at the end of the day, that’s what it was. This thing is a little bit weird, and I don’t understand it, so I’m gonna go digging. We have to be curious. I don’t really care how you build it, I wanna know how you break it. Right? And I think that’s a very important mindset for security people, so being curious is super important.

Omkhar Arasaratnam (17:25)
That’s some great advice. Last but not least, what’s your call to action for our audience?

Vincent Danen (17:32)
Be open-minded. Find a good reputable vendor to enable you on your — I hate the term digital transformation — but your digital transformation journey, right? Find a reputable vendor to work with there and then trust them, right? There’s a lot of great software vendors out there, a lot of great open source communities, projects, et cetera, who are desperately doing the right thing for those around them. And I think that that should inspire and has earned trust. And we have to trust the people we work with.

Omkhar Arasaratnam (18:02)
Vincent, thank you so much for being generous with your time. Be safe, and thank you so much for coming on What’s in the SOSS?

Vincent Danen (18:10)
Thanks, Omkhar.

Announcer (18:11)
Thank you for listening to What’s in the SOSS? An OpenSSF podcast. Be sure to subscribe to our series of conversations on Spotify, Apple, Amazon or wherever you get your podcasts. And to keep up to date on the Open Source Security Foundation community, join us online at OpenSSF.org/getinvolved. We’ll talk to you next time on What’s in the SOSS?