00:35:35 · Thai Duong, Joe Weisenthal, S1
[00:35:35] S4: I don't think that it's simple to fix the sandbox. That's the problem. People think that, you know, maybe people are not insecure. They think that there's a simple solution to cybersecurity. Just do this thing and you're safe. And that's how we have so many problems, you know. Vendors go out and tell people, just buy this box, this magic box. and put it in your network and you'll be safe. No, it's not like that. Even that box has problems. If you look into like, there's a famous idea in security, like product security is not the same as security product. Like security products may not have product security. Even like the firewalls that you buy, they may have problems. And they do. And what I mean here is, so... What we found, like the Hugging Face and OpenAI incident was fascinating, right? To watch. And it's difficult. Enterprise security is very difficult. Anybody saying like, oh, just buy this thing, just do that thing, you're going to be safe. No, it's just like very complicated. And the reason is like, and then people say, oh, just fix the model. And that's a comeback to the- And. [00:36:46] S0: Just fix the model, just make one that doesn't hack. [00:36:49] S4: That comes back to the incentive again. And because if you look at like how AI companies, and Jensen must be careful here, right? Because if AI company is not making money, he's not making money as well. [00:37:00] S1: Yeah, of course.
00:37:00 · S1, Thai Duong, Tracy Alloway, Bruce Dang
[00:37:00] S1: Yeah, of course. [00:37:01] S4: And the AI companies, they're making money by selling tokens. And most of the tokens are used for coding today, like programming, building things, right? And if you build, if you want to be really good at coding, you need an agent on AI that understands code understand technical problems, can debug things, can control computers. But that's basically the definition of a hacker. So you cannot really escape this. You cannot have a cake and eat it too, right? You need to be good at coding. Then you have an AI that is good at hacking. So unless you don't want spend more tokens, or you don't want to get into the coding business anymore, you focus on scientific discovery, physical AI, whatever, then maybe you can train a model that is not good at hacking anymore. But as long as you want to automate knowledge work, then eventually your AI must be able to use computers and control computers to understand technical problems. And that's the reason of someone like Bruce. So it's unavoidable. [00:38:17] S3: So actually, on this note, I'm curious, can you just talk about what it's like being a hacker in the age of AI versus, say, even three or four years ago, right? Like, it's crazy how quickly stuff has shifted. But how has your day to day changed? [00:38:34] S2: Yeah, I'll just use some background. So I wrote a textbook with some friends on reverse engineering. It used to be like, you know, like you try to like reversing is the practice of understanding software without any source code or hardware systems.
00:38:34 · Bruce Dang, S1, Tracy Alloway, Joe Weisenthal, Thai Duong
[00:38:34] S2: Yeah, I'll just use some background. So I wrote a textbook with some friends on reverse engineering. It used to be like, you know, like you try to like reversing is the practice of understanding software without any source code or hardware systems. [00:38:50] S1: That used to be like, I wrote this textbook. And then I think with the. [00:38:55] S2: Advent of AI, I think what, like, you know, whatever, nine months ago, as of nine months ago, like that entire book is deprecating. It takes like, you know, two prompts or one prompt and then bam, it will generate the textbook for you. And it's even better, you know, and it took us, you know, a long time to write. Just that gives you an idea. And then I talk to friends who've been doing this for decades, right? [00:39:16] S1: They're like specialists in this area, right? [00:39:18] S2: And they tell me that, oh yeah, man, like I spend, you know, whatever, $ 5 on some open source model and it reverse engineered the firmware on, you know, some Canon or like you know, HP printer and it hacks it, Bruce. You know, and whereas before it would take me, you know, like months to figure some stuff out. [00:39:35] S1: You know, that's just to give. [00:39:37] S2: You like a glimpse into what's happening, like how quickly things change. [00:39:44] S1: Well, a friend, you know, like this guy, Matt Suiche, he's, you know, and he's this dude. [00:39:50] S3: He's a friend of the show. [00:39:52] S0: A longtime friend of the show, multi-time guest. [00:39:55] S4: Yeah, keep going.
00:39:55 · Thai Duong, Tracy Alloway, S1, Bruce Dang
[00:39:55] S4: Yeah, keep going. [00:39:55] S3: We used to hang out in Abu Dhabi a lot. [00:39:58] S1: Oh, okay, yeah. Like, I'm no Matt Fawkes. [00:40:01] S2: I mean, like, now he's like, he gave a talk with our team the other day, and he showed his rack, you know, in his apartment, and he's sitting there, you know, like, hacking stuff, like, while he's sitting there talking. It's just insane. We have people that, let's say, for example, we've been hacking the iPhone. To build a full chain on the iPhone, it's not an easy task. Sometimes it takes several people to do this. And our team was able to do this within. [00:40:35] S1: A few days. [00:40:36] S2: Wow. [00:40:37] S1: You know, as a one person. And we have multiple of these chains. [00:40:40] S2: It really compresses the time, like the exploitation, the time to build exploits. [00:40:49] S1: We see customers getting hacked. [00:40:52] S2: By AI, you know, in the financials, in the banks, basically. You know, defenders cannot, you know, actually, Ty, why don't you tell these stories? [00:41:01] S1: And, you know, just a little bit, this has happened in the last few weeks, you know. Yeah. how things changed.
00:41:01 · S1, Thai Duong, Bruce Dang
[00:41:01] S1: And, you know, just a little bit, this has happened in the last few weeks, you know. Yeah. how things changed. [00:41:07] S4: Yeah, basically we saw like, you know, in the OpenAI and Hugging Face incident, there's one detail that is very interesting. I'm not sure if people noticed, but OpenAI noticed that like the people who handled incidents on the OpenAI side, they said that they have handled a lot of incidents, but this is the first time they saw that, you know, an incident where you have like a hundred people points within your networks that were compromised at the same time. Like there were a hundred like hackers within your system. Normally you have maybe one or two, right? Now you have a hundred. And I saw that I was like, wow, that was pretty interesting, but maybe because OpenAI have lots of tokens, so their agents can just go, you know, hack everything. And then just two weeks ago, we have like two clients in the banking industry. And they got hacked and they called us to help them with like the incident response. We came in because we do hacking as well. We know like usually it took us like maybe a month or something. Once we come in a network and then took a month for us to spread out. For the AI, it took like, they came in, they brought inside the network on Monday. By Tuesday, they're everywhere. [00:42:23] S2: Everywhere.
00:42:23 · Bruce Dang, Thai Duong, Tracy Alloway
[00:42:23] S2: Everywhere. [00:42:24] S4: And like, it's like cancer is spread like at a machine speed. And it was like mind blowing, right? Because how could you defend against that? Like in the past, we were telling our clients, you know, you have to invest in detection. Well, how can you help yourself? If you see it, you can detect it, but there's a hundred of them. [00:42:45] S2: Noted. [00:42:45] S3: We have a hundred hackers in our system right now. It's not really helpful. [00:42:49] S2: Exactly.