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>> You're watching TVN. We are live from Falcon Con here with Jordan Kurtz from CrowdStrike. Welcome to the show. Thank you so much. Always great to be back here with you. >> Always great to have you. Uh, congratulations on everything so far. I'd love for you to start by taking us through the big announcements today.
Well, big announcements, uh, just coming out of my keynote today. First, we started with our >> Falcon Guardian product, which is in the category of AI. So, if we think about the category that CrowdStrike really helped create around endpoint detection response, now this is taking really what we do for a human and a computer and applying it to AI agents.
>> Obviously, AI agents are more sophisticated. They have access to data. They have access to compute, to networking resources. They do bad things. >> Yeah. >> Because they're like a bunch of drunk interns that you put on your network. >> Yeah. And, um, and >> they can do a lot of damage. >> They can do a lot of damage. Right. So, we built this technology. We talked to our customers. We worked with, um, some of our largest customers to really figure out what they wanted, like Amazon. >> Yeah. >> And, uh, we're super excited because the missing link to accelerating security, sorry, AI adoption is security. >> Yep. >> Customers for the first time want to go faster somewhere and they need security to go faster as opposed to a brake pedal. It's actually a gas pedal.
>> Yeah. If you go back throughout your career, I mean, you've been working in security for decades, and I've just been really struggling with the order of operations for the predictions that have come true. Like, we got the Hugging Face attack, and then like three weeks later, someone was able to use ChatGPT to book a haircut. And it's just weird that we're getting capabilities in this very spiky way. Does this match your expectations? How does what you're seeing today go back to your original thesis when you started the company?
Well, it's interesting. When I first started the company, it was really based upon, we called AI, but it was machine learning back then. But again, it was being more predictive and using, um, the algorithms to figure out whether something was good or bad. >> Yeah. >> And now, if you fast forward to generative AI and agents, you know, it's important to leverage all of the data that we've accumulated over the last 15 years to get to a point where we're still doing that. And one of the second announcements we made was really the Super Intelligence Cyber Lab. Yeah. This was very exciting. And we actually partnered with NVIDIA to create really the first, what I would call, the agentic security, um, platform.
>> That is focused on a red, a blue, and a harness that continually learns from each other. Yeah. >> So we based, um, some of our models on Nemotron, >> right? We can probably get to that, but just overall announcement. So if you think about what we're doing, it's really creating a frontier-type model and harness at frontier levels specifically built for just the defenders.
>> Yes. So, uh, with that, uh, cyber, super, super intelligence lab, uh, you're going to have more tailored models, more specification, probably spikes that go beyond what's available with the stock frontier products, I imagine, over time, uh, if not immediately. But I'm interested in the, uh, the benefits of open source, the benefits of, uh, thinking economically, because I imagine that part of the battle between attackers and defenders is starting to become economic. How much, how many megawatts can I put behind this attack? Is that what's happening?
>> Well, the compute, the limitation, you're exactly right. The limitation for these attacks are really going to come down to sort of compute and cost. >> Yeah. >> Because the knowledge, and I talked about this in my keynote, has now been democratized where whether it's an activist, an e-crime actor, a nation state, they're, they're all now equivalent because of agentic technology. Yep. >> And we called it the rise of the agent state. >> Yes. >> Right. >> Yes. >> Meaning that now >> post-nation state. >> Post-nation state. Right. So the apex predator is now >> the, the agent state.
>> Yes. And I think what's really interesting is, and it kind of gets back to your spikes and the, in these models and those sort of things, is that when you go back to Hugging Face, >> it's a fascinating read. You probably have read it, and there's some great papers. We were actually called in >> to, to help OpenAI go through some of it. I'll leave it at that, but the papers are out there. >> And when you look at what these agents were capable of doing, >> and just how sophisticated they were with note-taking and communicating and maybe working as part of the collective, it's incredible.
>> Yeah. But the thing that I really called out in my keynote was that's all groundbreaking, but really what was the aha moment? The aha moment was the same incredible frontier-caliber AI was available for the adversary. In this particular case, that were, you know, it was trying to pass a test, >> but it wasn't available, drunk interns, >> for the defenders. Yeah. And, and these spikes come with the model refusals and all the guardrailing that, that was put in place. So again, our models are specifically trained on our data, which we think is a huge advantage. Harnesses that we built. Yeah. >> And again, we fine-tuned, uh, in the model creation and, and post-training. >> Yeah. >> Uh, in concert with NVIDIA to come out with incredible efficacy at the lowest cost. And this is what you were just getting to because customers want the best outcome at the lowest cost.
>> And I want, and I want probably AI review aid at every endpoint, at every transaction, every API call, every single possible moment. And that can be very expensive if it's running on a really expensive model. Right.
>> Right. Yeah. So, so our aid is going to, again, there are two separate announcements, but you're going to be able to run that from the platform. It's in, it's in, we announced it today, but the, the Red, uh, Tempest, which is the name of that model, >> and the Blue Solano, which is the defensive model, >> are part of the SafeMind system. Okay. So SafeMind, you can think about as the harness, right? >> But those models and harness will be available in the platform >> to make everything smarter and better and faster. Yeah. And then we have a trusted access program for customers in our CrowdWorks program that they would be able to use the models directly. >> Yeah.
>> Okay. So, uh, when you read the agent traces from the Hugging Face, uh, attack, uh, do you see anything in there that feels difficult to detect? Because when I look at those, I'm, I'm like, okay, they're crossing a line. This is odd. This would flag something in me. But we've seen examples like the how many R's are in the word strawberry, where AI just kind of falls flat on its face when you're trying to analyze a particular shape of problem. Do you, how tractable is this problem? How optimistic are you about solving it?
>> Well, it's tractable because when we, when we built our system, it was designed to look at sort of these, we call them indicators of attack. So if you look at the whole attack chain, >> and if you saw the keynote this morning, you know, it's just linking all these together. So irrespective of like what happened, these are, these are kind of unknown attack chains. Sure. Part of the issue was it was sort of flooded with so much information that I think it was just sort of buried. You know, what's going on? Is it real? Is it not real? >> And what is going to really take place is the defenders have to use AI to be able to >> connect the dots on those, which we do. But you also then have to strip out all the noise. So you have to separate the signal from the noise, >> and that's where these sort of models, uh, perform well.
I mean, obviously, there's an incredible amount of attention on AI. What is the role of deterministic threat detection these days? Is there, is there still, is that a useful tool in the tool chest? Is there, are there still advances being made there? Because I imagine that for certain problems, throwing a more deterministic, uh, you know, security, uh, structure around something could actually be beneficial.
>> Well, you have to, and if you look at in the Hugging Face incident, this was more of a forensics, what happened. Sure. >> Right. If you think about deterministic, um, security, it has to be in line, and you have to make a decision. You know, you have to be right the first time, right? First time final, as we call it. So, um, I haven't seen any sort of models, if you will, actually stop a breach in its tracks because >> it's, you know, as it's happening, you're kind of looking at data and those sort of things. It's not in line. >> Sure. >> So a lot of what the models are good at is sort of sorting out what happened, you know, sifting through lots of data and those sort of things, finding vulnerabilities. But, um, you have to have a deterministic system, which is what we built. >> Yeah.
>> And I think what people maybe get confused on, or maybe aren't quite sure, is when they hear things like Mythos. It's like, well, you know, this super powerful model is going to hack the world. >> It really hasn't come up with a new invention of hacking. >> Sure. >> Okay. This is very important. It's come up with, it can find more vulnerabilities. So more of >> and faster. Right. And when you combine those, you have, and you combine and link these things together, you have greater success. But they haven't invented a new way to hack.
>> Yeah, this is very important because I think the, the public may look at this and say, "Well, Jesus, a super weapon that can hack anything." And it, it really is the same techniques. It's just more of it, and it, it can keep track of more things. >> In turn, it's like you're taking a, a 10x hacker and making them a thousand-x hacker. Correct. Potentially.
>> Yeah. It's, it's almost like Iron Man. You put the suit on, >> somebody who's smart is a heck of a lot smarter. Yeah.
>> So, how, how are the threats evolving? I imagine you've been talking about agent states, which makes sense as a new concept, but I imagine that you still have nation states that are deploying their own agent states, >> correct? >> On their behalf. I'm sure the same thing is happening with various, you know, loosely tied hacker groups. But how is the threat evolving? What are you talking with customers about, these sort of new threats?
Well, it's interesting, and it, it is, the agent state is going to help the nation state, the e-crime, and the activists, right? Everybody in between. So, obviously, that's just an umbrella. But I think if you look across those different groups, they all have capabilities. They're all leveraging things like these open-weight models, right? We talked about obliteration, really taking the guardrails off an open-weight model, and you go to Hugging Face now and you can download these obliterated models and you can run them basically on a, on a beefy system, right? It's incredible. And you put a question in, and you're like, there's no way it can answer this, and it builds like, you want a full malware ransomware kit. Boom. It's done. >> Crazy. >> So this is part of the issue. This isn't theoretical. It's here. And what customers are asking for is, we want, we want to give visibility into these agents. Got it. We want to stop these sort of threats, but we also want to know if it's an AI attack. It's actually a very important question that they need answered. Is it an AI attack or is it sort of an adversary with maybe AI-assisted? That's been one of the number one questions because it informs them on what they need to defend against, but it also informs them on how they express this to the rest of the company, the CEO, and the board.
>> Yeah. What's been the biggest, or what do you see as the, the biggest bottleneck for you in terms of actually deploying solutions to customers? They're asking you, do you need more sales reps? Do you need more, uh, just more customers to come to you, just scale up what you already have? What's the shape of the next 12 months for you?
>> Uh, the, the great part of what we built at CrowdStrike is it's a very scalable model. It's a single agent, >> single platform with a single control plane. >> So, you know what people need to do to roll out aid? >> Turn it on. >> You know, sign the PO. I need to turn it on. That's it. Right. It's the same agent that's there. >> And we spend a lot of time, um, making sure that we can instrument, we can find shadow AI. Is it Claude? Is it CEX? Whatever it is, >> we can instrument every action that agent has taken, every action >> with a specific identity, every tool call, every spawn of an agent, >> every network connection, every prompt. We have that visibility. It's incredible.
>> So, it's sort of like the EDR moment when we developed EDR, >> when we first showed people, they were like, I've never seen this before. And when you do this to an agent, they're like, we've never seen this. We've been dying to see this. So I think when you look at our model, we're combining a very scalable platform. Turn it on, same agent. That's a huge win for us and a huge barrier to entry for other competitors. We have the most security agents deployed of any pure-play security company. So that's one. And two, we combine that with a very flexible licensing model. Yep. >> Which is Falcon Flex. So you'll be able to, to use, it's a, it's a token-based system. So the more AI you use, the more you pay, um, because there's, you know, more cost to this. But at the end of the day, you'll be able to use those credits and burn down from your Falcon Flex licensing model.
>> Yeah. And I imagine with Nemotron and just the advances in models, like there's a world where token prices come down over time if, if, you know, you're scaling up and stuff. So there's a lot of flexibility there.
>> Well, and we, we have different models which make it a lot more cost efficient. So the, the goal for us is to really, yeah, is actually to really, it is, it's not just one model, >> of course. Um, so we're, we're really driving down the cost, and I think that's a huge, uh, advantage for our customers, and then providing that sort of trusted access. We've been doing this a long time, and customers want to retain their data and the, the provenance of that data, the sovereignty of that data with us.
>> Yeah. Take me, uh, a couple quarters out, a couple years out, as far as you can, because it feels like we, there was, there were sci-fi stories about cybersecurity incidents related to AI. Then we got the Mythos moment, the Hugging Face moment. Now we have a really solid response, and it feels like there's, you know, the, the never-ending cold war continues. But are, are we, are we in a stable equilibrium here? Are you expecting some big change one way or another in the posture between the two warring groups here, the red team, the blue team?
>> I think it goes back to >> the story as old as time. It's good versus evil. >> It really is. This just plays out now in the modern day with agents at a speed that we can never really contemplate. >> But we can fight. >> But we can fight, and we will. They'll get better. We get better. >> And, you know, part of, part of what we delivered today with the lab is the red-blue training loop. Very important >> is that the blue learns from the red, right? So the defensive model continually learns from the offensive model, and you have a very fast cycle. It's very important. But >> you know, there's going to be all kinds of new technologies, new agents, new systems, things that we haven't even heard of today. Yeah. >> And we have to be able to defend against that. And I think what remains, while there will be a lot of change, what remains constant is security >> parallels the slope of the technology curve. >> Yeah. >> So the technology curve, I mean, >> you know, I started in the early 90s doing this, right? It was like this, and then it, it's like that. So you have to have security that actually parallels that.
>> Um, we don't do everything. You know, what we do, we do really well. We're a big platform company. There's only a few of us. I think that's going to win in this market. Um, but it's a big market. You can see by all the, the companies around here.
>> Yeah. And this is like a, for those of you that are tuning in, this is a, uh, it feels like you set up a town here, like 10,000 people. It's massive.
>> It's unbelievable. Yeah. I mean, you know, maybe you'll see some of this in B-roll or whatever, but >> this is a massive security conference. We have companies coming to this going, "We're not going to any other conference." And it was just an offshoot because we've got the best customers. It's a big audience. But I think what's important to realize is we understand and value the ecosystem. We can't do everything. Like, what we do, we do really well, but it's part of the whole ecosystem and network, which is why, uh, NVIDIA is here, obviously. Jensen Huang this morning, Lip-Bu from Intel, Greg Brockman from OpenAI, all partners, plus all the many that you see here.
>> Yeah. Uh, sorry, Jordi, please. What, uh, what groups or institutions are not paying enough attention to this new technology cycle that, uh, everyone here is like paying attention to this? Obviously, the AI boom, new threats, things like that. But is, is there a set of groups globally that, that need to be, uh, paying more attention to the new set of threats that aren't today?
>> Well, it's a good question, and I think the Mythos moment has really provided, uh, much more visibility from the board all the way down to the CEO level. I mean, my phone was ringing off the hook from Fortune 10 CEOs going, "Hey, what does this mean? How can you help us, etc., right?" So, you know, from a visibility standpoint, that's good. And then you look at a Fortune, we'll call it a Fortune 500 company. For the most part, they have or will find the money to deal with some of this, and it depends on the industry, how much they spend, but generally they have a view, and it's regulated, etc. The have-nots, those are the half. The have-nots are >> I'm thinking like local utilities, hospital systems, >> hospitals, NOS's like utilities, forget it. I mean, they're running such old software.
>> So, it's the have and the have-nots. And I think part of what we want to do, and even working with OpenAI, is how do we help, you know, give a hand up to people >> who, you know, need it because they don't have all of the security people they need. They don't have the money for all of these sort of advanced software and technologies. But we've got to, it's a collective community effort, and that's part of what we're helping to drive in partnership with many others.
>> What does it take to make it a CrowdStrike these days? You're hiring, uh, AI researchers now for the new, uh, super intelligence lab. You have a lab >> with 270 PhDs. >> Wow. Uh, significant. So, uh, what is the shape of the new all-star up-and-comer at CrowdStrike look like? >> Um, the up-and-comer, I mean, it depends on the... >> I guess the question is just like, how much AI are they using? How much are the human skills still hyper-relevant? What is the, what is the balance? How, how familiar do you have to be with these tools? What are the pitfalls? Because I think everyone's sort of realizing as they run large companies that people can get lost in the sauce if they're too reliant on it. How do you think about this in terms of like your own management style?
>> Yeah, I think that's important because, I mean, we, we try to be very deliberate about it. Security is very important to us. So where we use it, how we use it, um, what groups we use it in, you know, we've expanded out obviously, but >> obviously a big part is going to be around coding. >> Sure. >> And you have to make sure that you get the right secure code out of it. >> Yeah. >> You know, it used to be in the early models, I would say a little less so now, but in the early models, it was like the early days of coding when someone would go out to the internet and they would just copy and paste a snippet of code. You would take that vulnerability and it would propagate for everybody that needed, you know, that snippet of code, right? So AI was originally generating some code, and you're, you know, I, I have my own models I built. I, you know, have my own security agents that I built just to play around. >> And it's like, well, the same model that just built my code, then I built an agent to figure out whether it was secure, was the same model that goes, it's not secure. Like, okay, why don't you build it, you know, in the first place? So you have to be aware of that. And, but what I think is important, getting back to your question, is if you don't buy into AI as an enabling technology and you're sort of scared for your job, you're not going to, you're not going to be successful at CrowdStrike. If you want to use AI in the right places at the right time with the right cost, >> we have all the room in the world for you here. >> I love it.
>> And we have these sort of >> AI builders, and we're deploying them into all the different functions. So those are the folks that you go, "Hey, it'd be great if we can do this." And, and you turn around and get some coffee, and they go, "Here, it's done." Yeah, that's what we like.
>> No, I love that too. I love that too. Even in our small organization, we would love for you to sign this helmet. We have a Sharpie here. Uh, would you mind signing right here? We want to get an autograph from you to commemorate the occasion. And we also have a gong with a mallet. We'd love to >> get you to smash this for >> the occasion. Here you go. Give us a gong hit. We'll let you get a backhand on this, right? Where's the, the sweet spot?
>> I think the sweet spot's right here. No, just give it enough force. You'll be good.
>> All right. >> With authority. >> There we go. With authority. >> Well, thank you. >> And I just want to say, I love the, I love the aesthetics of everything here. We got Agents of Chaos back here. It's incredible.
>> It's incredible. Well, congratulations to you, because I know >> you, you had a new baby. >> I did. That's breaking news. >> Okay. >> I had a new baby. No, no, it's great. It's not a secret. >> Did I scoop you? >> You scooped me. Okay. Sorry about that. >> No, no, no. It's great. Great to see you, George. On the track. >> I'm going to leave it. I'm going to leave it, >> but I, yeah, I won't walk away like I normally do. Um, we'll see you at the track. >> Yeah. >> Uh, stay tuned for the race this weekend. >> We're excited. >> Hopefully our men, our men do well, and, uh, we'll go from there. Okay. All right. Yeah. Bye. See you soon. We'll talk to you soon. >> Cheers.
>> Uh, that was fantastic. Of course, the show is >> breaking news >> sponsored by Ramp. Time is money. Save both. Easy-to-use corporate cards, bill pay, accounting, and a whole lot more, all in one place. Thank you, Ramp, for making TBPN possible. We have a bunch more guests coming on from Falcon Con here in Las Vegas. And I believe we have our next guest ready to rock. We have Michael Sentonas, the president of CrowdStrike, here to take us deeper on everything CrowdStrike is doing in cybersecurity in the age of AI. The AI revolution is here. Are you ready? That's what it says outside. A little ominous, but probably accurate.
>> Accurate. >> Good question to be asking. How are you doing, John? Pleasure. Nice to meet you.
>> Welcome to the show. >> Uh, we're going to have you throw this headset on. Uh, we'll get this out of the way, get comfortable, and, uh, we will ask that the microphone just go a little bit close to your mouth because it's noisy in here. You've got a lot of, lot of partners here. It's a huge company, huge conference. Um, did you have anything to do with that? Are you the reason why everybody's here?
>> A little bit of a reason. Okay. Yeah. Yeah. Well, yeah, let's start with your role. Uh, what do you do at CrowdStrike? Little bit of your history, and then there's a whole bunch of hot topics I'd love to go into. Happy to go wherever you want. >> Let's start with, uh, your role, your day-to-day.
>> President of CrowdStrike. So, uh, go-to-market reports into me. Product and engineering team. Uh, researchers, our threat hunters, the >> researchers too. >> Researchers too. >> Researchers and go-to-market. How are those, feel like different groups? What, how, how does that work? Is that, uh, operational? Are you spending more time with one or the other? How does that blend? Um, look, I think, uh, my background, I, I started through the, the product side of the, the organization. >> Uh, I was the CTO of the company for, for quite a while. One of the things that I talk a lot about is you can build the best technology in the industry. >> If you can't sell it, if you can't talk about the value, if people can't deploy it and they can't ultimately keep themselves safe, >> it's kind of irrelevant. So, it's trying to bring together >> uh, the smartest people. Obviously, you had George on before. We worked really closely. He's got a bunch of people that report in to him as well on the engineering and research side. >> It's bringing it all together and then making sure that we keep people safe and secure.
>> Yeah. What are, what are customers in the go-to-market side actually concerned about? Because there's an immense amount of attention on cybersecurity right now. I imagine that makes sales easier, but at the same time, we've all seen token maxing and AI budgets and people, you know, they have to find the money somewhere. So what is the tension that you deal with? How are you thinking about positioning that for customers?
Yeah, look, every organization has huge, uh, requirements, but they've also got a budget. They've got a business to run. The business is not there unless you're a service provider and your business is cyber. You're building cars, you're building houses, you're in medicine. >> Um, and you need to keep yourself safe and secure. So, every CISO, every CIO is trying to basically do the best at what they can. They came into 2026, suddenly everyone's trying to work out, how do I find tokens to pay for all of the things that the business is doing? >> You know, every second organization has token shock. So, at the end of every month, they just realize that they spent 20,000 more than they should have per employee. >> Uh, and, you know, we've got to work with everybody to show them there's a better way. There's a more efficient way. We give them a, a vehicle that they can procure and get CrowdStrike Flex that I think you guys have talked about with George in the past. Yeah. >> And we show them that they get a much better solution. It's just easier to live with day-to-day. So it's not only showing them the cost of buying it, but how do they deploy it and then operationalize it? >> Yeah. >> Uh, because cyber, you've got to live with it. You've got to use it every day.
>> Yeah. Yeah. Okay. So in deployment, uh, let's talk about the balance between attackers and defenders. In terms of AI capabilities, I'm pretty confident that you, OpenAI, Anthropic, the big labs have the advantage on raw power, intelligence, capabilities in terms of defense and probably offense too, but you don't use it for that, you know. Um, but does that map to your reality that, that the >> only, the only difference is like you guys need to be successful every single time and an attacker only needs to be successful one out of it. >> Yeah. Yeah. >> 100,000 times, right? >> Yeah. >> I mean, that's the way it works.
>> Okay. Um, every organization can't get it wrong, and equally they've got additional pressure. Yeah, they've got to get it right 100% of the time, but they also have to not stop business. Yeah, it's easy to get it right 100% of the time if you turn off everything. >> So, you know, it's not going to, it's not going to fly with the CEO of the company, and if every day, you know, the security technology is slowing people from browsing, you can't use the AI that you want. So, there's an added level of complexity.
>> The defender has things like change control. The defender has things like, you know, regulatory, uh, guidelines and process that they need to, you know, follow. Attacker doesn't care about any of that. You know, you go to Europe where everyone in Europe is talking about like AI laws and privacy and regulation. I said at a conference, this is fantastic. You guys are leading the world in all of this regulation, and everyone was proud. The adversary does not care. >> Yeah. >> The adversary. >> Yeah. They're already breaking the law. So why would they not, why would they not follow >> regulations? They love it. They're in there, and, and that's, that's kind of some of the challenges that people face with, and then you have the cost pressures. >> Yeah. >> You can't just pour everything into tokens. >> You can't just pour everything into, you know, IT budget. >> So that's why we spend a lot of time making sure that you get the best that you can. >> And a lot of the time we come in and say, "Okay, here's a product. We're going to try to take two out." >> Yeah. >> It's not one in, one out. It's one in, two out, three out.
>> Sure. Sure. Sure. Um, but so, uh, talk about the pace of AI diffusion, AI adoption in, uh, in cyber, because it feels like even though there's immense go-to-market operations, AI adoption among the bad guys has to be incredibly quick because it's often free. It's, it's, you know, highly motivated. There's no, just download the thing. Um, and so I feel like that's maybe more of the challenge than like raw intelligence. Is that a reasonable frame of mind to think about the, the real shape of the problem is like the slope of adoption, like the, the good guys need to adopt more security AI faster than the, than the, than the attackers?
>> Look, we've talked about this for 20 plus years. If you went to a security conference 20 years ago, everybody talked about this time in the future is going to come. >> Sure. >> Where attackers are finding vulnerabilities and they're weaponizing them at a speed that you're just not going to be able to deal with. >> Sure. We're here now. >> Yeah. And if you think about the technology, I mean, the adversaries get access to everything. And the best thing that's happened to them is the advancement in the open models. They can go and get a Chinese model. They can go and get a model effectively from anywhere that they run inside their, their sort of framework. Uh, they can build it, they can train it, they can tune it. And because they're running it in their environment, they can customize it in a way that you don't know what they're doing. >> Yeah. >> And then the first time they use it is the first time you have to deal with it. And it's cheap for them when they run it internally. They don't have the cost of the tokens and everything else. They need the hardware. They need everything out there.
>> Yeah. Do you, do you feel like the adversaries are compute-constrained right now or are they just able to do a lot with a little?
>> Depends on the adversary. You know, the kid at home is going to be compute-constrained. Uh, if you're dealing with a nation state, if you're, if you're dealing with some of the most, uh, well-funded, well-structured, well-trained adversaries that now have this capability as well, this is the challenge. That's why there was a packed, uh, arena this morning. That's why Jensen came out to talk about what they can do, because if we don't do something and if it's not a community, it's going to be really hard to compete with this technology. It's so good.
>> Yeah. Yeah. What, uh, what kind of conversation are you having with governments these days? Uh, we were just talking about, uh, you know, it's not just enough to secure the Fortune 10, the Fortune 500. You need to secure the local hospital, the local, uh, you know, utilities operation. And it feels like the government, various governments might try and incentivize different rollouts and speed things up there. What are you hearing from talking to people in government?
Generally, >> I think, I think you've nailed the point because the world's business runs on small business. The world's economy, I should say, runs on small business. They don't have the resource, they don't have dedicated people, they don't have the, the dollars. And most often when they have a problem, it's also very hard, where do they go? And they think, you know, I'm not going to be able to get the resource of the largest banks, etc. Uh, we want to spend a lot of time with them, and that, that's super important. But importantly, governments around the world that are also starting to say, hey, we need to make sure that our economy keeps working. We need to make sure that critical infrastructure, you know, the power is on, water is flowing, um, you know, rubbish trucks arrive. Um, otherwise, we're going to have, have chaos. And, you know, we've seen examples of critical infrastructure taken out. We can't have banks get compromised with ransomware. We can't have, uh, you know, just pure, uh, chaos out there. And I think there's an opportunity now to work more collaboratively.
>> And every, every, coming, coming back to your question, every government wants to talk about AI, you know, what do we have to worry about? How do we use it? How do we embrace it? But what do we have to be worried about when other people that have malicious intent? >> Yeah. >> Uh, what could they do to us? You know, if they start using all of these open-weight models, uh, what, what do we need to know about them? So, a lot of partnership, a lot of collaboration. Um, and I think, you know, that concept of community that we're talking a lot about this week is super important because if we don't do that, we're just not going to be on top of it.
>> Tons of attention on AI for very good reasons. Uh, is quantum getting under-discussed? And I say that because I've heard that there are adversaries who are hoovering up encrypted data with the hope that quantum computers in the future will be able to decrypt that data. They're stealing it now. They can't do anything with it. And so maybe even though AI is super important, we should be talking about it 99% of the time. Should we be talking about quantum 1% of the time?
Uh, we are, and, and it's, look, it's a big...
Not a day goes by where a customer, a partner, an analyst, someone asks a question about quantum and what that means.
I love the point, just to kind of dive in, where people are taking data. A lot of the time you see examples where attackers will basically exfiltrate all your data, and then you don't see it again. And you get the email saying, yes, your name was in clear text, but everything else was encrypted, and now you have to think in five years that might be decrypted.
Sure. But sometimes when those attacks happen, you understand, when you see your name in the list, you understand what they were doing. You understand that you are the person that they're monetizing.
But what happens when they take terabytes of data, they're not selling it, they're not acting on it, they're doing something,
They don't even know what it is, maybe.
Well, they didn't do it just because they wanted to have fun. So there's intent. Now, whether it's decrypting it down the road, whether it's training models, you know, you need to think every attacker, there's a motivation for it. And it's fascinating when you actually start to get behind what's interesting, what's driving them.
Yeah. Yeah. Yeah. You got to imagine there's at least a few people out there that...
Well, that's how it used to be like back in the day. You wrote malware because you wanted a company like CrowdStrike to say, 'Hey man, that Jordy guy, he... like he nailed it. Like this is an attack. This is really innovative.' We talked about it. We started, you felt good about it. You got it in the hard place.
Doesn't work that way anymore. Okay. Yeah. How is AI impacting various social engineering schemes?
Well, it's funny because you know, a few years ago it was really easy to tell people about social engineering and said, you know, if you read something and it reads like a 10-year-old wrote it or someone with bad English, you know, it's probably not the bank that you have all your money in, right? It was an easy telltale sign.
Now they learn how to use, you know, ChatGPT, they learn how to use Gemini. The emails that they write are phenomenal. We used to see about a year ago the click-through rate in phishing was about 11 to 12%.
Today with AI that still feels incredibly high.
It's over 60 now because they're written perfectly, grammatically. They probably write better than us now. And you kind of look at what comes out. It's really hard to work out what's real, what's not. So they're getting a lot of opportunity. The thing is, you grab an open-weight model and you basically say, 'How would I carry out this attack?' It's going to give you the playbook. You know, I've done cyber since university. You don't need any of that anymore. I kind of feel like wasted youth now because you just need a model. You ask the question and it tells you what to do.
Yeah. Okay, we got to move to the next. We got one more question. We got time for one more question. I mean, the company's on an absolute tear. I'm interested in how you know you oversee all these groups. What were you telling people during the SaaS apocalypse in earlier moments, even go back further, just throughout the company's history? You've had a very clear vision of where things are going, the value that you're creating long term, but there's gyrations. What is it like actually managing all of these different teams? It's got to be funny that like the height of the SaaS apocalypse, you probably had the phone ringing off the hook more than any other point in history because at the same time people were like realizing like, wow, models are now at the point where...
Look, I've known George, who you had on just before, for over 20 years, and I remember one of the first things he ever said to me: look after the customer, everything else takes care of itself. And that mantra goes throughout CrowdStrike. So all of this noise, you know, we just basically say keep looking after the customer, keep innovating, keeping them safe and secure, things will take care of themselves. We know the way the technology works. You know, for me, the SaaS apocalypse thing, there was no merit to it. It didn't make any sense at all. Even today, when people say, 'Hey, all the models are going to find all the vulnerabilities and then we're going to get this state of normality.' No, we're not. We're going to get more vulnerabilities. We're going to get more attacks. It's only going to get harder. And that comes from just having so many years of experience. It's having an engineering team that is at the cutting edge, at the forefront. But it's putting the customer first, and you know, it's a good formula and it always works.
I love it. Well, thank you so much for the show. Have a great day. Congratulations on fantastic Falcon. Up next we have Daniel Bernard, the chief business officer of... five minutes though.
Five minutes to hang out.
60% click-through rate on phishing emails. What are you guys doing? What are you doing? What are you guys doing? Speaking of phishing emails, there have been a raft of password reset attempts on X.
We got another minute I wanted to ask him about.
Oh, yeah. Yeah. Well, we can go into that with the next guest. Nick Carter posted on X: a lot of people getting unsolicited X password reset attempts in their email inbox. Do the following: go to X settings, security, account access, security, check password reset protection. Don't let people hack into your X account. It's simply too valuable. You can't let...
And this was because X Money is rolled out to a lot more people, notification, financial incentive now because you could potentially steal someone's money if you got in, as opposed to just post a Beamcoin link or something like that.
Anyway, the other story we got to talk about is YouTube creator, director Markiplier has acquired an 8.5% stake in GoPro. Did you see this? The action camera maker. They've been sort of in the doldrums. A lot of competition from China, but...
And then immediate questions because GoPro just got acquired today.
Oh, wait. It was a full acquisition?
Oh, I didn't know that. Wow.
Yeah. So, this news comes out yesterday and just today GoPro has entered into a definitive agreement to merge with privately held Starman Optical in a deal valued at 285 million. So it seems like Markiplier is up massively, which is going to immediately...
Like part of the deal. Yeah.
Well, it's going to immediately draw a lot of attention. Yeah, but a lot of times these things happen as like one piece of a larger deal and the stake gets disclosed at a certain time because it's part of this remaking of the business. Do you think GoPro can come back?
That's a good question. I owned a GoPro back in the day. I never... GoPro was one of those things where for the average person, you're capturing footage that is only entertaining to you and no one else is going to care.
You know, I'm a pretty good snowboarder, pretty good surfer,
Remember Shawn Maguire? Shawn Maguire was like throwing shots, but we'll set up a heat, Sean. But anyways, I always felt like I would film something with my GoPro and then it would be mildly entertaining for me and not that entertaining for someone else.
So you don't watch game footage. You don't get out there on the waves and rewatch.
If you're watching game footage, it's better to watch from the third person.
You don't want to watch the first person. Interesting. Interesting. Yeah.
I've owned a GoPro at various points in time, but again, like never really found a good use for it.
Yeah. Yeah. And it felt like the GoPro budget for consumers shifted to drones. They didn't get there. Again, that's a third-person view that is like I think a lot more interesting to...
And there's even some drones that will follow you out while you're surfing and track you well and stuff. Yeah. And then yeah, just the innovation... like I still have very positive feelings towards GoPro. They worked with so many amazing athletes over the years. They were a pioneer. The bigger challenge was just the iPhone. The iPhone got very durable and the quality got amazing. So why would I... you can take your phone out on a ski run or whatever, and you'll be fine. The other thing, like Meta glasses too, the Oakley Meta glasses.
I think Best Buy reported earnings and said that smart glasses are like driving significant in-store sales for them. Like they're actually moving. They're selling well. We've seen that.
