You don't have a defense unless you have a great offense to go up against. You want to be the Baltimore Ravens defense of 2000. You kind of want to have your practice offense really push you. That's what Armadin's going to do. We're going to be the all-star team on offense coming at you so you can train your defense with what we're doing.
You built Mandiant, a great success. Why did you decide to get back on the field?
I don't want to sit out the AI shift change when I've done 30 years in security and the whole damn thing's about to change. What AI does in a microsecond would take 70 humans. They can't even do it. It's apples to oranges. This is a tsunami like has never been seen before in security.
The whole let's slow down the models. We don't want cyber risk too late. The open models are already good enough. Armadin, since January of this year, we have found over 90 zero days at customer sites, all in production. This is not like rinky-dink companies. Like these are like Fortune 500 companies.
The differences or similarities between nation-state attacks compared to AI today, and then where you think AI can be in a couple of years.
On the defensive side, we're going to say we're being attacked by these models, but we're not sure who's behind them. Is it a nation? Is it a human? Is it...
Kevin, thanks for being here.
Okay, so you built Mandiant.
Obviously a great success. Many different chapters. You know, it ended up, you know, inside of Google ultimately. Why did you decide to get back on the field?
It's a good question, and you know, I don't know if I decided it, and that'll sound weird. But I met with David Slater and with Travis Lam, the other founders, and Evan Pena. I knew, you know, I could say they started this company. They are the founders. You know, I met them. They had the idea. They pitched me on what they wanted to do, and I saw the talent in them. Like Travis is a generational talent. David Slater's, and I mean this in a positive way, a freak of nature. You know, like these guys are really, really good. Evan Pena is exceptional at what he does.
And when you meet that team and you talk to them, the whole time I was listening to what they were doing, I was thinking, I want to be a part of this. You know, I don't want to sit out the AI shift change when I've done 30 years in security and the whole damn thing's about to change. You know, that's great. Everything I did is dead and everything else is new. But meeting that team and they were starting the company and me realizing I think I'm a real good fit with these guys to accelerate the need. Like what Armadin is building, every company needs now. And I was like, this team that can build it, and I think I can answer the now. Let's, you know, 30 years in security, you meet a few people. Let's go to those people and say we've built what you need. Yeah. You know, so I almost felt compelled to do it. I know that sounds weird, but I would not have founded a company again in my, you know, mid-50s, and I was doing venture.
It wasn't like, oh, I'm an entrepreneur and I love starting companies. That's not it.
And it wasn't, I'm not a VC. I'm just an operational guy. That's not it. I met the team and went, we have to do this. Yeah. I mean, that's really it.
Yeah. And this whole AI shift change was happening. Like that's the catalyst, right?
So yeah, tell us about what Armadin does.
So, Armadin leverages frontier models and AI on offense to test do you have exploitable risk, and that's what we do today. We call it Armadin Red. But when we started the company, Travis and David Slater and Evan all knew the future of cybersecurity is going to be the good guys have to build the offensive cyber cannon and shoot it at networks to make sure those networks can withstand these attacks because they're the ones that are coming. But we also knew it's going to be AI on offense built by the good guys working and training with AI on defense built by the good guys. And you have to have both. So our act one was we got to be the best in the world at finding exploitable risk. If we're five minutes ahead of the bad actor, whether it be a nation-state, criminal, nuisance, if we're five minutes ahead of them, we also recognized our act two, Armadin Blue. We got to stop it. Compensating control tourniquet.
And so that's what Armadin does. We're building the force field you will need in the AI age to defend yourself from AI attacks.
Yeah. Tell us about the nature of the capabilities of AI attacks today, and then where you think it goes.
Well, great. So the nature of them is, first off, we're getting a weird window in time where we're seeing them, but not at the same level you'd expect. Like I've seen nothing like what Armadin's already built in the wild, which is there's 25,000 agents all in concert, all working together, doing really, really smart things without going on bizarre fishing trips. Because when you respond to an AI attack, you can tell it's AI very quickly. At least I can because I've done, you know, I've thought about a lot of offense. I've responded to a lot of attacks in the past that were led by humans, right? And a human goes to point A, then to point B, then to point C through their intrusion. AI does little things like four or five differences, but one would be it'll break into point A, then laterally move to point B. Next thing you know, it's trying to break into point A again.
It's like, I get the drone swarm, but you could probably coordinate and think a little bit better. And that's where it's at today. It'll get better and cleaner. But the differences are, first and foremost, the scale of what AI can do dwarfs humans, like in ways humans don't even get right.
So you have a scaling problem in that humans could always find only one path into a network.
Yeah. They had to be selective because they had to devote their limited resources to one direct path. Right.
Yes. And then so scale is a challenge. Speed, ridiculous.
What AI does in a microsecond would take 70 humans. They can't even do it. It's apples to oranges. And then so what was always lacking is AI creative or effective. But when it comes to what we do, we don't need the fanciest model. We're not trying to speak 400 languages, you know, with our models and all that kind of thing. What Armadin's doing on offense is we're finding vulnerabilities, exploitable risk. That is code. That's a structured language, a structured process. Because it's structured, AI is going to be great at it. Right.
So I really think it's already here today. Like the whole let's slow down the models. We don't want cyber risk too late. The open models are already good enough, and these things are common now. It's just a matter of the minute you have anonymous availability of GPUs, you'll see far more criminal attacks.
Yeah. You know what I mean? But until you can attack anonymously, and you know, it's hard to do crime when people know your name. It's better to, if you can commit a crime anonymously, here's my tip for criminals. If you can commit a crime anonymously, that's a lot smarter than doing it with your jersey on, with your name on it. And so anyway, the difference in attacks and what we're seeing now, we are at the precipice, first inning still, of AI attacks coming. And I think that's just because of the cost and availability of the models is not as readily available to the criminal element as it will be in the future.
Yes. Exactly.
Okay. So your experience in working in the security industry for 30 years, you probably saw a fair amount of nation-state attacks, right?
Every day. So talk about the differences or similarities between nation-state attacks, and I use that just to say the most sophisticated, most, you know, most whatever, most successful, if you will, types of attacks compared to AI today, and then where you think AI can be in a couple of years.
So everything's going to change rapidly, right? And but I can tell you, nations on offense have never, in my opinion, they've never really been, when you're hacking for espionage and for security reasons, you hack with what I would call kind of a sniper round. You're not spraying and praying. For the most part, modern nations on offense restrict their targeting and they go deep at very specific things, like 30 defense contractors or military, you know, and they go hard at that kind of thing. Think of it as, you know, that sniper round. With AI, I think it becomes more like a drone swarm. You know, it becomes a little bit different in the cyber domain. And I think even modern nations are thinking, what will our protocol be if we want to attack this company? Do we swarm it and just burn tokens on it? Because AI is going to do a lot of things humans just wouldn't, right? You know, so it's a little sloppier, a little louder, but it's more effective, but it's more comprehensive.
That's the problem. You got it. It's more effective probably because if the...
And so there's going to be so many things a nation's got to think through right now, and their whole doctrine will shift as the AI shift change comes. Like how does AI change what our mission is? Do we maybe use the cyber domain differently? Do we drone swarm sometimes, sniper round other times? How do we balance the two? Does it depend on risk, target, how surreptitious we want to be? Because right now AI is not a surreptitious action on offense. Yeah.
Unless you've done a ton of post-training. You got to maybe a human in the loop really looking at are we doing smart things? Because if you just go, hey, here's a prompt, hack, you know, abc.com. AI is not going to do it in a surreptitious smart way. And I think even if you ask it to, it's still not going to till it's been really trained and really had some human influence on it. So, but more generally, what you're going to see is less capable attackers, less technical, less successful are going to appear way more successful. It's the equalizer, right? Because when you start using models over time, what it's going to be is on the defensive side, we're going to say we're being attacked by these models, but we're not sure who's behind them. Those attacks, is it a nation? Is it a human? Is it... And we'll have some clue, but attribution will get a little difficult. So that's a long-winded answer saying in the AI age, it does democratize far greater expertise for attacking victim networks.
Yeah. So then that is a good segue back to Armadin. So you have talked about the defense needs to be a great offense, right? Like best train defense with something.
Yeah, of course you got to train your defense with something, and then it needs to be continuous. Right.
Right. So how does the product work, and then how do you get a level of sophistication such that you can identify and remediate these vulnerabilities, like what you're describing, that are more sophisticated than a basic prompt?
Okay. Lot there. I could talk for 45 minutes on it, but first I can tell you this. You don't have a defense unless you have a great offense to go up against. You know what I mean? Like, so even think in sports terms, if you want to be the Baltimore Ravens defense of 2000, you kind of want to have your practice offense really push you. You know what I mean? So that you know how good you are. And that's what Armadin's going to do. We're going to be, you know, the all-star team on offense coming at you so you can train your defense with what we're doing. And that's going to be important. And you can't really have a human in the loop in the AI age for tactical autonomous defense. Like you got to do something fast. You know, you got to tourniquet the wounds as fast as you can. So thinking back to our, like you want to be able to do it continuously, and that's the complexity. So we do a thing called a hyperattack.
And David, that's just a fancy word for we throw a drone swarm of agents at you and we map your network. Every service, every route, every system, all assets. We may end up with terabytes of metadata on your network from this hyperattack done super fast. Just it lights you up. So that way we can now, it's almost like a metadata twin of what we can see. If we're on the inside, do the same thing. Let's just map everything. This is the attacker's view of your network. But with that metadata, we now just pull you almost like a heartbeat. What's changed? What's changed? That's continually looking for did an app change? Did a route change? Did a service get updated? Did a new machine get presented onto the, you know, into the target area so that we can pull cheaply for change and then attack the change. Yep.
What you really want in the future in the AI age is that you want the constant pressure of models attacking you, but you can't do it all the time because a, it's not, it's cost prohibitive, but b, it's unnecessary. You do it when either the threat changes, hey, new models come out, new intelligence is available, or b, your network changes, so you want to test whether that happens. And then c, you just probably just want to test. We have a board meeting tomorrow. Let's see how we do. You know what I mean? Let's audit ourselves and see where we're at. And that's why we had over the weekend there was a zero day in a popular product. And immediately we've already got the heartbeat. We just pulled the problem.
Yeah. And our goal at Armadin is to go from, you know, common vulnerability or CVE to a, we can find if it's exploitable or not before bad guys can, right? You know, and not all bugs allow for human access to your system in a stable way. So not all bugs are created equal, right? And so we want to make sure, hey, this one's one you really need to worry about, or which ones don't give remote command execution. So, long story made short, that hyperattack, that metadata that we get allows us to kind of pull for change and attack you when your network changes. And that's the best you can do for continual, and we'll get better and better at it. And the cost for the polling will go down. You know, it's on small networks doesn't cost much. But on a network that changes all the time and is very large, you'd be pulling it quite a bit to make sure you don't have an exposure window.
Yeah. Of course. So that is actually a very good explanation for why this continuous approach matters, right? It's so fun. Like I, you know, you and I share...
Well, you're already up against it. Somewhere out there, the criminal element will always have that random scanning, and they probably aren't even using AI for it. They've got one exploit that they think works, and they're just kind of scanning the world for it and then coming at the exploitable risk, you know, and so you're already getting some pressure on your network from an unseen force that's not well-intentioned. You know what I mean? So you might as well have a better force built by the good guys constantly putting pressure on you.
Yeah, it's interesting. So, you would kind of, Armadin, I don't know, a year ago, would probably be placed in the category of pentesting, and you and I share history and relationship with George at CrowdStrike, right? And so they famously redefined the category from AV to EDR, and of course they did incredible things, but the category redefinition was on the back of major infrastructure changes and product changes, you know, and allowed them to create a product category that was far greater and bigger than AV. Talk about pentesting. What is the historical view of pentesting, and why that's not what the future is?
Yeah, a couple of things. I mean, you had to do it right. It was kind of like first-gen AV. You have to buy AV. And I think when you look at Armadin, we will be as ubiquitous as AV because you have to have that AI force field of AI on offense, training AI on defense. You have to do it, and you can do it. So why wouldn't you? And so you look at that, and pentesting to me is always just scanning for what's already known, and it doesn't prove whether you're really exploitable or not. So it's always created a larger list of vulns that don't matter, right? And so the way we wanted to do it at Armadin was we actually can carry the exploit out. We verify so there's no false positives. We can get remote code execution or get data off of that machine. And a lot of pentests are nothing but hit your infrastructure, not with a thinking, learning technology that memorizes and knows your infrastructure like an AI agent can. So it's not going to do custom apps. It's going to, at least the old versions of pentesting, you know, the Tenable, the Rapid7, the Qualys was more a hygiene sort of thing. You know, what do I have out there, and what services are exposed, and are there CVEs available against those services, or known exploitable vulns against them. When you have an AI-based attack, it'll find logic flaws rather than code flaws in custom applications. It'll exhaust all routes all the time. And it's like all I can tell you is Armadin, since January of this year in 2026, we have found over 90 zero days at customer sites, all in production.
And by the way, your customer base is like...
They're happy we found them before, and they're like Fortune. This is not like, you know, rinky-dink companies. Like these are like Fortune 500 companies.
And I don't mean that as fear, uncertainty, and doubt. But the difference is that we've trained our models, we've post-trained all our models with real red teamers, real folks that actually can develop exploits. And that's important. And so when we're scanning networks, we don't have source code to review. We're not finding these zero days with source code. We're not finding these zero days because we can log into an app and now we have access and we can get to other things. We are black-box coming from the internet, over 90 zero days in major software companies, and they're thankful. And so everybody's like, wow, Mythos came out and you can scan source code and find vulnerabilities, and you find thousands of them. That's noise.
We're coming from the outside, and then we're calling a CISO, you know, usually within 48 hours. Hey, we've got remote code execution in your DMZ. And usually from there, we're getting in, and they agree with us. And the nice thing is we're going through, you know, the fix side's a little bit harder, takes a little bit longer, but those companies go right into incident mode. They respond as if it's an incident. And that's not a pentest. That is like a real adversary coming at you. And the difference between red teaming and pentesting is pentest to me is a hygiene step. And I think over time everybody would have red-teamed everything all the time if they could, right? It was cost prohibitive and people prohibitive. With AI and an agent doing it, or in our case we have lots of different types of agents doing different things, you can now do that. So I think it'll replace pentesting over time. That's just, that's like a small portion of what a red team coming at you would do.
Yeah. So you talked, you mentioned earlier, you know, obviously that's Armadin Red. Yeah. You mentioned Armadin Blue. Talk about Armadin Blue.
The Armadin Blue is like we can't just show up and say, hey, you know, you're vulnerable. See you later, you know. And hey, the true north for every CISO should be effective autonomous response. We got to build that. And we knew all along you can't just say, hey, we want to be the best in the world at finding exploitable risk. That's goal number one. But then goal number two, and be the best in the world at doing something about it. And that means Armadin Blue. And Armadin Blue will be take the information about exploitable risk and work with the defense plane, you know, whether it be endpoint EDR or firewalls, and create compensating controls at speed. Yes. So that if we find an attack five minutes before someone else using a model finds an attack, you're already safeguarded. And these safeguards are going to be rudimentary potentially out of the gates right over the next few months. A year from now, they're just going to be there. Because the whole cyber domain is progressing at a speed where you're going to have to defend autonomously for better or for worse. You know, I'd rather have a bad patch stopping a bad guy from getting in than have an intrusion. You know what I mean? So you got to take your lesser of two things, and one's much more manageable. You never want an unknown person with arbitrary access on your network.
And so you want to prevent that anyway you can. And I would say the first generation is we're working with CrowdStrike on it, and they know it has to exist. We're working with Palo on it. They know that it has to exist. They want to all, you know, shift into the AI age with autonomous defense as well. And so we need to inform those defense platforms, you know, the Fortinets and everybody else. Here's what you can do about it. And I likened it to, you know, kind of field dressing in war. Someone gets shot, you patch it up, but that's not the hospital, you know, that's a, hey, we kind of stop the bleeding. And but then you got to maybe do something else with more time and humans potentially, or even, you know, agentic approach to it down the road. So you're going to see it happen even if you're a CISO, you're going to see autonomous defense happen even if you don't ask for it, right?
Because of the defensive platforms you've already invested in.
You mentioned earlier, you know, some of the blurring of the lines of different categories within cyber. And I think you joked that your old days, your 30 years of experience is out the window or relevant or something like that. What is the future of the SOC, and then how do the categories within cyber blend together or change?
You know, if I'm a CISO, I do believe my true north is effective autonomous security. You want to keep your best people engaged. You want to automate the processes that work for your organization, but you are absolutely saying what survives in the AI age and what doesn't, right? And I think we're still working through that process. I think there's whole processes in the SOC that will just go away, and for whatever reason, we're automating right now. Yeah. You know, over time, I can tell you this, if you have humans in the detect and respond loop, you're going to be too slow. Yes, you know what I mean? It's just not going to work well. So you have prevent, detect, respond. Prevent's going to be governed by AI, and detect and respond is going to be done by AI. And the goal in cybersecurity has always been if you have, you know, you want to prevent, you know, you don't want to detect and respond. So I just see the constant narrowing of the window of every phase to the point where, you know, we're really not doing a lot of detection and response because the window to do it is it happens. You got it. It's a little bit too fast. So, but you still got to have that onion peel to some extent of systems backing up systems and assuming failure somewhere, right? You know, like even Armadin creating the force field, sooner or later somebody's going to get around it. Someone's going to create an exploit before we find it somehow, someway on a platform or an app that we just haven't assessed yet. It hasn't been in production at a customer's site, and so we haven't looked at it, and someone else finds it. And when they do that, you will want to have a trap behind saying we've got unauthorized access or unlawful access to a system. Those traps are that you just can't have a human there. Yeah.
I mean, it's just going to, because we've already done it at Armadin. And when we break in and have an agentic-aware internal command and control, it proliferates at a speed that is shocking. You know, like I remember as a human, you're like typing on your keyboard, I want to go laterally move with this passphrase from here to here, and you're so slow, and you're doing one thing at a time. This thing just does a thousand things at once. It's just everywhere, and you're like, whoa, okay, done. Got the...
