WEBVTT - PHP2Shell Won't Be the Last Big AI Cybersecurity Risk

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<v Speaker 1>Bloomberg Audio Studios. Podcasts.

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<v Speaker 2>Radio.

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<v Speaker 3>News.

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<v Speaker 4>Hello and welcome to another episode of the Oddbots Podcast.

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<v Speaker 4>I'm Tracey Alloway.

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<v Speaker 1>And I'm Joe Weisenthal.

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<v Speaker 4>Joe, it's October. We're recording this on October 29th.

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<v Speaker 5>Yeah.

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<v Speaker 4>It is also Black October. Have you heard this term?

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<v Speaker 5>Yeah.

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<v Speaker 1>What does that mean? Have stocks gone down?

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<v Speaker 2>No.

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<v Speaker 4>Your mind immediately goes to markets. There are other worlds

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<v Speaker 4>out there. We're going to be talking about the world

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<v Speaker 4>of cybersecurity today because one of the reasons people are

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<v Speaker 4>talking about Black October is we've had a number of

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<v Speaker 4>recent security issues, the most prominent of which has been

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<v Speaker 4>a bunch of vulnerabilities discovered in PHP, which is a

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<v Speaker 4>coding language that apparently is used by 70% of websites

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<v Speaker 4>in existence. We can get into that stat later. But

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<v Speaker 4>the really interesting thing about this vulnerability being uncovered is

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<v Speaker 4>AI was used to uncover it. And so the big

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<v Speaker 4>question coming back to AI, there's a concern now that

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<v Speaker 4>you have good actors who are maybe using AI to

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<v Speaker 4>discover old vulnerabilities and trying to fix them. But you

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<v Speaker 4>could also have bad actors who are using AI to

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<v Speaker 4>exploit those same vulnerabilities. So we're back to the question

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<v Speaker 4>of whether AI makes the internet safer or more dangerous.

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<v Speaker 1>It makes it more dangerous. No, I have no idea.

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<v Speaker 1>Ever since essentially Anthropic announced that they had this model

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<v Speaker 1>called Mythos and now it's Project Glasswing, which was rolled

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<v Speaker 1>out to companies to use for defensive purposes before it

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<v Speaker 1>was available to the general public, there has been much

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<v Speaker 1>more awareness of cybersecurity issues as it relates to AI.

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<v Speaker 1>And there are many things that people debate about AI

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<v Speaker 1>and some of these bigger existential questions. Pretty much everyone

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<v Speaker 1>agrees cybersecurity good, more cybersecurity good. I will say I

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<v Speaker 1>know very little about the world of cybersecurity. I don't

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<v Speaker 1>know what, for example, a cybersecurity company actually sells. I

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<v Speaker 1>don't know how if I were buying cybersecurity, I would

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<v Speaker 1>know whether it's working or whether no one had tried

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<v Speaker 1>to hack me or not or something like that. I

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<v Speaker 1>need to learn a lot more, but it's absolutely true

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<v Speaker 1>about the uptick in the volume of hacks.

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<v Speaker 4>There are hackers out there right now taking notes going,

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<v Speaker 4>Joe doesn't know anything about cybersecurity, probably doesn't have a VPN.

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<v Speaker 5>I don't.

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<v Speaker 1>That's why my vibe coding projects, I don't want to ever,

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<v Speaker 1>I have yet to build anything with an account because

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<v Speaker 1>I don't want to like have to think about that.

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<v Speaker 1>So it's just like, I don't want to count information

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<v Speaker 1>with anyone. But I have as a user of technical products,

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<v Speaker 1>over the last several weeks, you get more emails saying like,

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<v Speaker 1>Our thing was compromised. You're probably fine, but maybe you

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<v Speaker 1>should refresh some keys or whatever. This is happening. This

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<v Speaker 1>is real. And everyone really needs to learn more. And

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<v Speaker 1>if you think about like black swans and Wall Street

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<v Speaker 1>and all that stuff, you know, there's been for years

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<v Speaker 1>a lot of talk about cyber as a major risk

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<v Speaker 1>out there.

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<v Speaker 2>Yeah.

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<v Speaker 4>All right, well, we do, in fact, have the perfect guest.

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<v Speaker 4>We're going to be speaking to two people from the

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<v Speaker 4>company Calif, one of the companies that actually uncovered this

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<v Speaker 4>PHP vulnerability. The other one was a company called Wiz.

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<v Speaker 4>We have Tai Yun. He is the CEO over at Calif,

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<v Speaker 4>which is a hacking firm, and we can get into

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<v Speaker 4>exactly what that means, as well as Bruce Dang. He

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<v Speaker 4>is an engineer at Calif as well. So, Tai and Bruce,

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<v Speaker 4>thank you so much for coming on All Thoughts.

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<v Speaker 2>We're glad to be here. So.

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<v Speaker 4>Just to begin with, because hackers kind of, they always

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<v Speaker 4>have cool achievements that they like to talk about. Why

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<v Speaker 4>don't we just go ahead and start with who you

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<v Speaker 4>are and what are the coolest things you've done in

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<v Speaker 4>your hacking career?

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<v Speaker 3>Yeah. So I started my career at Microsoft almost 20

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<v Speaker 3>years ago in the Microsoft Security Response Center. These are

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<v Speaker 3>the people that do patch Tuesdays. On the second Tuesday

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<v Speaker 3>of every month, Microsoft releases an update. So I worked

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<v Speaker 3>in that team a long time ago. Probably the biggest

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<v Speaker 3>thing I did there and that I could talk about

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<v Speaker 3>is I helped reverse engineer the Stuxnet virus, which is

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<v Speaker 3>one of the one that was related to the supposedly

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<v Speaker 3>the Iranian nuclear program was used to sabotage the Iranian

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<v Speaker 3>nuclear program.

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<v Speaker 4>This is the thing that people describe it as the

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<v Speaker 4>world's first like known digital cyber weapon, right?

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<v Speaker 2>Yeah, yeah, yeah, yeah.

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<v Speaker 3>I'm sure there were many others before, but yeah, that's

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<v Speaker 3>the first public one, yeah. I worked there for almost

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<v Speaker 3>a decade. And then I left to do a startup

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<v Speaker 3>with my friends. And then I joined Apple. I worked

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<v Speaker 3>on iOS security. And then Ty managed to convince me

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<v Speaker 3>to follow the Church of AI.

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<v Speaker 2>And so here I am.

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<v Speaker 5>Yeah, it took me four years to convince Bruce. So,

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<v Speaker 5>you know, when you go to a website or you

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<v Speaker 5>go to Amazon, even Facebook, Instagram, your computer will share

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<v Speaker 5>information with the server, right? Yeah. And that would be,

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<v Speaker 5>the information would travel through many, many other servers, like

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<v Speaker 5>your ISP, your Wi-Fi routers. So you want to encrypt

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<v Speaker 5>that information to make sure that only the server can

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<v Speaker 5>see your data, nobody else. And there's a mechanism for that.

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<v Speaker 5>It's called the SSL protocol, or the later version is

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<v Speaker 5>called like TOS, like transport layer protocol. security protocol. So, um,

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<v Speaker 5>I love those protocols and, um, back in the day,

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<v Speaker 5>together with, uh, friends, we found a bunch of ways

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<v Speaker 5>to break the protocols, you know, to decrypt the data. And, um,

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<v Speaker 5>it's pretty cool. It's actually changed the internet, how the

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<v Speaker 5>internet works, because we basically, um, showed that in the

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<v Speaker 5>past that like two protocols, like SSL Versus 3.0, that

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<v Speaker 5>was invented by Netscape. You remember Netscape? Yeah, yeah. 30

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<v Speaker 5>years ago. And then people still use it because it's

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<v Speaker 5>still working somewhat. But we show that, oh, it's not

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<v Speaker 5>working very correctly. If you use SSL 3.0, then people

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<v Speaker 5>can decrypt your data. So we hope the internet really,

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<v Speaker 5>really removes SSL 3.0. And that's one thing. The other

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<v Speaker 5>thing that I really enjoy doing was, you know, people

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<v Speaker 5>think that in the past you have compression, you have

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<v Speaker 5>some data and you want to compress the data and

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<v Speaker 5>you have encryption. And both of them actually randomize your

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<v Speaker 5>data in some way, right? If you look at a

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<v Speaker 5>zip file, you open a zip file, look at the

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<v Speaker 5>raw binaries, buy data in the zip file, look random

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<v Speaker 5>to you. Because... all the redundant information has been removed

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<v Speaker 5>and encoded in a way to reduce the size of

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<v Speaker 5>the file. And so one of the basic question in

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<v Speaker 5>computer security was, would you compress data and then you

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<v Speaker 5>encrypt or you encrypt then compress? And I took some

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<v Speaker 5>crypto class at Stanford University and I remember my professor,

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<v Speaker 5>he asked this question in one of the homework assignments.

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<v Speaker 5>And the obvious answer back then was you don't want

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<v Speaker 5>to compress and then you don't want to encrypt and

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<v Speaker 5>compress because encryption randomize your data. It means that compression

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<v Speaker 5>would be less effective. So the right answer is you

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<v Speaker 5>compress and then you encrypt. And that was the correct

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<v Speaker 5>answer on my homework assignment. I think I took that

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<v Speaker 5>class in 2011. And then three years later, we found

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<v Speaker 5>that it's wrong. If you do that, then people can

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<v Speaker 5>actually decrypt your data. And the way it works is

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<v Speaker 5>pretty cool. I can explain to you. So compression actually reveals,

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<v Speaker 5>if you look at a compressed file, you know how

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<v Speaker 5>well it is compressed, right? Because it's softer. If it's smaller,

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<v Speaker 5>the compression is very good because there's a lot of

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<v Speaker 5>redundant information. That's why compression works well. It means that

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<v Speaker 5>if you look at a compression alone, the size of

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<v Speaker 5>the compression, a compressed file, you can tell whether the

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<v Speaker 5>file has a lot of redundant information. And encryption hides

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<v Speaker 5>the length. So it doesn't hide the size of the

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<v Speaker 5>encrypted data. When you encrypt a message, you can still

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<v Speaker 5>see that this message is maybe this long or this

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<v Speaker 5>message may be this long, right? Because encryption doesn't try

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<v Speaker 5>to hide that. There's some people try to do that.

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<v Speaker 5>So it means that if you compress and then you encrypt,

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<v Speaker 5>it means that I can see where your message has

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<v Speaker 5>some redundant information, has a lot of redundant information. And

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<v Speaker 5>that alone is a leakage already, right? That you don't

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<v Speaker 5>want to review. And I gave you an example. Let's

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<v Speaker 5>say that you take a message, like a random message

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<v Speaker 5>that I gave you, and then you put your password

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<v Speaker 5>together with that message. Let's just say that there's a

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<v Speaker 5>reason for you to do that. You put your password

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<v Speaker 5>together with the message I gave you and you compress together.

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<v Speaker 5>And then you encrypt it. with a key that I

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<v Speaker 5>don't know. And you reveal the ciphertext, the result encrypted

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<v Speaker 5>message to me. So supposedly I don't have the key.

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<v Speaker 5>I shouldn't be able to read the message, right? But

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<v Speaker 5>because I give you a message and you get my

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<v Speaker 5>message put together with your password, you compress together. If

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<v Speaker 5>the compression works very well, then I know whether my

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<v Speaker 5>message has some redundancy with your password.

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<v Speaker 4>You can reverse engineer between the two relationships.

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<v Speaker 5>Yeah, exactly. And you do that repeatedly. Eventually, we can

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<v Speaker 5>recover your password. And that's exactly what we found on

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<v Speaker 5>the web encryption protocols. In the past, that's exactly what

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<v Speaker 5>they did. They take my data, they concatenate your password,

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<v Speaker 5>they compress together, and then they send over the wire.

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<v Speaker 5>And then as an attacker, I can see the length

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<v Speaker 5>And that's enough for me to decrypt. And the solution

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<v Speaker 5>was really interesting, because they decided to turn off compression.

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<v Speaker 5>There's no solution. And then eventually, I was at Google

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<v Speaker 5>back then. I was born in Saigon, Vietnam. I grew

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<v Speaker 5>up there. Then I got a job in Mountain View

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<v Speaker 5>for a consultancy, like what we do. So I moved

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<v Speaker 5>to Mountain View in 2011. And then I joined Google.

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<v Speaker 5>later that year. And I did cryptography at Google, basically

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<v Speaker 5>help people do cryptography correctly, like try to avoid the

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<v Speaker 5>mistakes that we found. I was there for 12 years.

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<v Speaker 5>I work on like very last number of products. Google

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<v Speaker 5>has a lot of products, right? Gmail, Chrome browser that

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<v Speaker 5>we are using right now. And there's a lot of

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<v Speaker 5>people out there that want to hack Google and our products.

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<v Speaker 2>Yeah.

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<v Speaker 5>So my job was to hack these products before we

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<v Speaker 5>released them to the public. And I was there for

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<v Speaker 5>12 years and then I left to create Calif. And yeah.

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<v Speaker 1>That's fantastic. I'm already fascinated by this conversation. I want

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<v Speaker 1>to get into obviously what Calif does specifically. I want

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<v Speaker 1>to get into some of the latest vulnerabilities. But before

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<v Speaker 1>we do that, you know, both of you have had

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<v Speaker 1>long careers that by and large predate what we now

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<v Speaker 1>call AI. Are the risks associated with AI a sort

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<v Speaker 1>of continuation on some path that cybersecurity have well understood,

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<v Speaker 1>or are we in a truly novel area for how

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<v Speaker 1>we should we be thinking about cybersecurity risk?

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<v Speaker 3>I think it's a combination of the two. We've always

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<v Speaker 3>known that there are security vulnerabilities in systems. And so

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<v Speaker 3>we have security engineers who are hackers.

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<v Speaker 2>Who try to find and exploit these vulnerabilities.

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<v Speaker 3>So the system has always been vulnerable to some degree,

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<v Speaker 3>to a varying degree. What AI has done is it's

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<v Speaker 3>kind of accelerated the speed in which you identify and

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<v Speaker 3>exploit these vulnerabilities to a level where it's almost like superhuman.

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<v Speaker 3>You know, like 20 years ago, Microsoft would release, let's say,

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<v Speaker 3>maybe 20 updates every month. Now you're looking at like,

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<v Speaker 3>you know, 1,400 updates per month. And that number is

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<v Speaker 3>going to continue to grow. Just to give you an

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<v Speaker 3>idea of the scale of things. And now, for example,

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<v Speaker 3>to have certain systems, it may take you, let's say,

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<v Speaker 3>three months with lots of people. Now, that may take

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<v Speaker 3>you a few days with just one person and a

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<v Speaker 3>very capable AI model.

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<v Speaker 2>That's the reality that we're in today.

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<v Speaker 3>It even changed the way how Attackers have certain types

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<v Speaker 3>of systems, like in the banking sector, that our customers

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<v Speaker 3>are in. You can tell some stories about that time.

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<v Speaker 3>But that's kind of what I think. I think it's

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<v Speaker 3>the systems have always been vulnerable to some degree.

0:13:26.510 --> 0:13:31.079
<v Speaker 2>And now it's the AI just... accelerates that and makes

0:13:31.120 --> 0:13:31.960
<v Speaker 2>it much more visible.

0:13:32.480 --> 0:13:35.579
<v Speaker 3>And it's also made it easier for people to identify

0:13:35.620 --> 0:13:37.300
<v Speaker 3>these vulnerabilities as well.

0:13:37.400 --> 0:13:40.390
<v Speaker 2>And so, and then, you know, obviously there are pros

0:13:40.429 --> 0:13:42.510
<v Speaker 2>and cons to that. But yeah, you can go into

0:13:42.530 --> 0:13:42.830
<v Speaker 2>that later.

0:13:58.940 --> 0:14:02.520
<v Speaker 4>Why don't we talk about discovering the PHP vulnerability then?

0:14:02.540 --> 0:14:06.949
<v Speaker 4>Because I think this was a joint project between Calif, Wiz,

0:14:07.230 --> 0:14:10.910
<v Speaker 4>and I think it was OpenAI. How did you find this?

0:14:10.990 --> 0:14:13.090
<v Speaker 4>What was the process? And then what was the decision?

0:14:13.110 --> 0:14:14.689
<v Speaker 4>I know you guys have gotten a little bit of

0:14:14.730 --> 0:14:20.130
<v Speaker 4>pushback about publicizing it before it was fixed. So what

0:14:20.150 --> 0:14:23.630
<v Speaker 4>was the process of actually putting out the statement saying

0:14:23.670 --> 0:14:24.410
<v Speaker 4>we found this thing?

0:14:24.830 --> 0:14:30.080
<v Speaker 5>We're really interested in finding vulnerabilities that have wide impact.

0:14:30.780 --> 0:14:36.210
<v Speaker 5>And we want to understand these vulnerabilities to help inform decisions,

0:14:36.690 --> 0:14:40.710
<v Speaker 5>defense decisions, how to fix and how to mitigate them

0:14:40.750 --> 0:14:45.370
<v Speaker 5>for once and forever. On that background, we joined the

0:14:45.690 --> 0:14:51.760
<v Speaker 5>OpenAI's Pass the Planet program. This is where OpenAI funds

0:14:51.780 --> 0:14:56.640
<v Speaker 5>companies like Calif to go out and help open source

0:14:56.680 --> 0:15:02.820
<v Speaker 5>maintainers to identify and fix, mitigate vulnerabilities in their software.

0:15:03.980 --> 0:15:08.600
<v Speaker 5>And we have this engineer, like Ryan Osteen, who is,

0:15:09.280 --> 0:15:13.080
<v Speaker 5>he's like a PHP historian. Yesterday, we went to a

0:15:13.120 --> 0:15:18.470
<v Speaker 5>conference in San Francisco. We basically presented like, you know,

0:15:18.570 --> 0:15:23.750
<v Speaker 5>PHP 2 shell, and Ryan walked everybody over like the

0:15:23.750 --> 0:15:28.780
<v Speaker 5>25 years of history of PHP vulnerabilities. So we have

0:15:28.800 --> 0:15:32.810
<v Speaker 5>this engineer, Ryan, and this is how we work, basically.

0:15:34.010 --> 0:15:37.310
<v Speaker 5>Our engineer, they're interested in certain things, and then they

0:15:37.350 --> 0:15:40.130
<v Speaker 5>just go and hack those things. And, you know, as

0:15:40.190 --> 0:15:42.810
<v Speaker 5>business people, we try to see, okay, how can we

0:15:43.270 --> 0:15:46.080
<v Speaker 5>convince some other people to pay us for this work?

0:15:46.680 --> 0:15:50.960
<v Speaker 5>And that's exactly what we did with OpenAI. We convinced OpenAI, okay,

0:15:50.980 --> 0:15:54.980
<v Speaker 5>we're going to hack PHP. Can you fund our work?

0:15:55.590 --> 0:15:58.430
<v Speaker 5>And they said, yes, they gave us tokens and money.

0:15:58.990 --> 0:16:01.990
<v Speaker 5>And then we go and convince like PHP Foundation, which

0:16:02.050 --> 0:16:05.990
<v Speaker 5>is the organization behind PHP, that let's work together, you know,

0:16:06.030 --> 0:16:09.310
<v Speaker 5>we can help you. And it's actually pretty interesting because

0:16:09.330 --> 0:16:12.710
<v Speaker 5>I mentioned like they're like a history of 25 years

0:16:12.870 --> 0:16:17.990
<v Speaker 5>of like PHP vulnerabilities. And the person that is behind

0:16:18.310 --> 0:16:22.110
<v Speaker 5>all of these hacks is like Stephen Escher. He's also

0:16:22.170 --> 0:16:24.880
<v Speaker 5>at Calif. He joined us, I think, six months ago.

0:16:25.600 --> 0:16:28.420
<v Speaker 5>Back in the day, he's the PHP security guy. Basically,

0:16:28.450 --> 0:16:33.390
<v Speaker 5>he hacked and helped, like, harden PHP. So we didn't

0:16:33.430 --> 0:16:37.030
<v Speaker 5>know anybody at the PHP Foundation. So we asked Stefan

0:16:37.130 --> 0:16:40.790
<v Speaker 5>to introduce us. And because, you know, even though Stefan

0:16:41.430 --> 0:16:45.050
<v Speaker 5>stopped working on PHP security for a while now, his

0:16:45.130 --> 0:16:50.090
<v Speaker 5>name still rings, you know, very... loudly in this circle

0:16:50.110 --> 0:16:50.710
<v Speaker 5>of the world.

0:16:50.890 --> 0:16:54.370
<v Speaker 4>I saw the comic that you guys put up about this.

0:16:54.390 --> 0:16:55.730
<v Speaker 4>It was kind of funny.

0:16:55.950 --> 0:16:56.270
<v Speaker 3>Yes.

0:16:56.510 --> 0:16:59.210
<v Speaker 4>He's like Indiana Jones type character.

0:16:59.290 --> 0:17:03.500
<v Speaker 5>Yeah. So he connected us and then we met with

0:17:03.720 --> 0:17:07.939
<v Speaker 5>Volker Dusch at the PHP Foundation. And yeah, that's how

0:17:08.000 --> 0:17:13.320
<v Speaker 5>we got started. I think we started in July 30.

0:17:13.320 --> 0:17:16.380
<v Speaker 5>And then immediately after one or two days, you know,

0:17:16.420 --> 0:17:22.350
<v Speaker 5>Ryan found the first vulnerability, and he was interested in

0:17:22.810 --> 0:17:29.859
<v Speaker 5>finding a vulnerability similar to one vulnerability that Stefan disclosed

0:17:29.859 --> 0:17:35.619
<v Speaker 5>22 years ago. And to his surprise, there's still a

0:17:35.660 --> 0:17:39.780
<v Speaker 5>bunch of them like that in the PHP software right now.

0:17:41.040 --> 0:17:44.489
<v Speaker 5>And so that's how we found it. And then we

0:17:44.530 --> 0:17:48.200
<v Speaker 5>reported it to the PHP Foundation. because we know immediately

0:17:48.260 --> 0:17:52.450
<v Speaker 5>that is a critical vulnerability that could affect a large

0:17:52.490 --> 0:17:56.210
<v Speaker 5>part of the internet. Then the Peace Preach Foundation actually

0:17:56.290 --> 0:18:00.070
<v Speaker 5>shared with us that they actually found this vulnerability, the

0:18:00.109 --> 0:18:04.179
<v Speaker 5>same vulnerability, two years ago. But they didn't fix it.

0:18:04.960 --> 0:18:09.379
<v Speaker 5>Because when they found it, they discovered that the fix

0:18:09.740 --> 0:18:14.360
<v Speaker 5>is very expensive. And there's just maybe a few options

0:18:14.859 --> 0:18:18.670
<v Speaker 5>to fix it. and none of them were actually perfect

0:18:19.330 --> 0:18:25.870
<v Speaker 5>because they need to change a lot of functionalities within PHP.

0:18:26.790 --> 0:18:32.689
<v Speaker 5>And those changes may introduce new bugs, new vulnerabilities, or

0:18:32.750 --> 0:18:36.570
<v Speaker 5>new reliability issue. And people would be very upset if

0:18:36.650 --> 0:18:42.409
<v Speaker 5>they upgrade PHP and their website stop working. So in

0:18:42.430 --> 0:18:47.780
<v Speaker 5>the end, back in like 2024, The PHP Foundation decided

0:18:47.920 --> 0:18:52.380
<v Speaker 5>not to fix it because there was no exploit. No

0:18:52.520 --> 0:18:55.200
<v Speaker 5>one could manage to show that this is actually a

0:18:55.240 --> 0:18:59.380
<v Speaker 5>real issue. And that's exactly what they asked us. They

0:18:59.420 --> 0:19:01.860
<v Speaker 5>come back, they ask like, do you have an exploit?

0:19:02.880 --> 0:19:05.419
<v Speaker 5>Then the next day we share with them the first

0:19:05.560 --> 0:19:11.000
<v Speaker 5>exploit that showed them that, yeah, someone doesn't need to

0:19:11.060 --> 0:19:13.530
<v Speaker 5>know anything. can hack your website remotely.

0:19:13.730 --> 0:19:16.830
<v Speaker 4>So just to be clear, the use of AI in

0:19:16.930 --> 0:19:20.680
<v Speaker 4>all of this, it wasn't necessarily that important in finding

0:19:20.720 --> 0:19:24.959
<v Speaker 4>the vulnerability. It was more important in developing an actual

0:19:25.080 --> 0:19:27.119
<v Speaker 4>exploit for a known issue.

0:19:27.460 --> 0:19:29.790
<v Speaker 5>We think like that's probably the right way to think

0:19:29.850 --> 0:19:33.149
<v Speaker 5>about it. But I think even for finding the vulnerability

0:19:33.230 --> 0:19:35.730
<v Speaker 5>without AI, it would take a lot more time, right?

0:19:36.550 --> 0:19:41.860
<v Speaker 5>So you can imagine like PHP was created like maybe

0:19:41.859 --> 0:19:45.270
<v Speaker 5>30 years ago. So it's a huge code base with

0:19:45.330 --> 0:19:49.920
<v Speaker 5>a lot of features. And as a human engineer, you

0:19:49.960 --> 0:19:53.840
<v Speaker 5>have to dig into this code base and it will

0:19:53.859 --> 0:19:56.520
<v Speaker 5>take like months, right? And along the way, people may

0:19:56.560 --> 0:20:00.209
<v Speaker 5>give up. But the fact that PHP Foundation filed the

0:20:00.230 --> 0:20:06.090
<v Speaker 5>bug in 2024 proved that humans can actually file the bugs, right?

0:20:07.070 --> 0:20:11.650
<v Speaker 5>And the problem was the exploitation, like you said. And

0:20:11.830 --> 0:20:15.899
<v Speaker 5>for exploitation, like AI plays a major role in it.

0:20:16.600 --> 0:20:20.180
<v Speaker 5>It's like becomes an engineering problem where our engineers would

0:20:20.220 --> 0:20:22.280
<v Speaker 5>tell AI, you know, this is how I want to

0:20:22.300 --> 0:20:26.880
<v Speaker 5>design our exploit and you go and do it. And then,

0:20:27.060 --> 0:20:30.600
<v Speaker 5>you know, prove to us that it works correctly. Yeah.

0:20:31.000 --> 0:20:35.030
<v Speaker 1>Let me ask a philosophical question. Is there a reason

0:20:35.090 --> 0:20:40.950
<v Speaker 1>to believe that defensive cybersecurity can stay ahead of offensive cybersecurity,

0:20:41.010 --> 0:20:43.170
<v Speaker 1>just generally, and then we can get into some details.

0:20:43.550 --> 0:20:48.530
<v Speaker 1>But philosophically, is that something that we can reasonably hope for?

0:20:49.150 --> 0:20:50.030
<v Speaker 2>I think so, yes.

0:20:50.310 --> 0:20:50.670
<v Speaker 1>How come?

0:20:51.170 --> 0:20:55.670
<v Speaker 3>Because you can use the AI to build certain types

0:20:55.859 --> 0:21:00.810
<v Speaker 3>of systems in ways that may be very challenging. for

0:21:00.930 --> 0:21:06.290
<v Speaker 3>attackers to exploit. Today, you can use AI to build

0:21:06.590 --> 0:21:11.730
<v Speaker 3>whatever systems you want very quickly. You can experiment, get

0:21:11.770 --> 0:21:16.640
<v Speaker 3>feedback very quickly. It can also process data very, very

0:21:16.680 --> 0:21:18.980
<v Speaker 3>quickly and reason about that data.

0:21:19.660 --> 0:21:22.120
<v Speaker 2>And so I think it is possible.

0:21:22.240 --> 0:21:26.400
<v Speaker 3>I think it may not be immediate, but over time,

0:21:26.460 --> 0:21:31.220
<v Speaker 3>we're going to perhaps use AI to help us write

0:21:31.260 --> 0:21:35.680
<v Speaker 3>more secure software or build more secure systems. And eventually,

0:21:35.700 --> 0:21:41.080
<v Speaker 3>I think that should counterbalance the advantages.

0:21:40.680 --> 0:21:45.810
<v Speaker 2>That the attackers have. Perhaps I'm being optimistic, but I

0:21:45.850 --> 0:21:47.369
<v Speaker 2>do foresee this happening.

0:21:47.910 --> 0:21:50.770
<v Speaker 5>I can add something there. So if you look at

0:21:50.790 --> 0:21:54.580
<v Speaker 5>the history of humanity, our history is the history of

0:21:54.650 --> 0:21:59.480
<v Speaker 5>like weaponize our tools, right? If you find a powerful tool,

0:21:59.600 --> 0:22:02.120
<v Speaker 5>then someone would find a way to use that tool

0:22:03.000 --> 0:22:03.520
<v Speaker 5>as a weapon.

0:22:03.820 --> 0:22:04.060
<v Speaker 4>Yeah.

0:22:04.300 --> 0:22:10.040
<v Speaker 5>So, and attackers always are early adopters of tools, right?

0:22:10.540 --> 0:22:16.040
<v Speaker 5>New technology. Defenders move like at much slower pace than attackers.

0:22:16.810 --> 0:22:20.350
<v Speaker 5>But fundamentally, we believe there are more good guys than

0:22:20.410 --> 0:22:25.310
<v Speaker 5>bad guys out there. And eventually, the good guys would

0:22:25.350 --> 0:22:30.990
<v Speaker 5>catch up and build things that help everybody defend off

0:22:31.190 --> 0:22:38.520
<v Speaker 5>the bad guys. And I don't think in general, cybersecurity,

0:22:38.740 --> 0:22:40.460
<v Speaker 5>if you see the news all the time, you see

0:22:40.700 --> 0:22:44.920
<v Speaker 5>we got data breach every day almost, even before AI.

0:22:45.510 --> 0:22:48.190
<v Speaker 5>So you may feel like it's not working at all.

0:22:48.930 --> 0:22:51.450
<v Speaker 5>But if you're in the field, you can see the progress, right?

0:22:51.550 --> 0:22:55.370
<v Speaker 5>In the past, like, 25 years, there's a tremendous progress

0:22:55.430 --> 0:22:58.730
<v Speaker 5>in cybersecurity. Of course, people still got hacked because this

0:22:58.830 --> 0:23:04.150
<v Speaker 5>is difficult. Imagine you have a very complex system. Like,

0:23:04.210 --> 0:23:07.260
<v Speaker 5>imagine you have a house with lots of doors and

0:23:07.280 --> 0:23:11.000
<v Speaker 5>lots of ways to get in. And cybersecurity must, like,

0:23:11.040 --> 0:23:13.160
<v Speaker 5>make sure that everything is safe. At the same time,

0:23:13.220 --> 0:23:16.770
<v Speaker 5>your house or your Office must remain open for business.

0:23:17.609 --> 0:23:20.660
<v Speaker 5>So it's actually a pretty difficult problem. At the same time,

0:23:20.680 --> 0:23:25.060
<v Speaker 5>without the progress that the industry made in the past

0:23:25.060 --> 0:23:29.860
<v Speaker 5>25 years, things could be much worse. And I think

0:23:29.900 --> 0:23:32.820
<v Speaker 5>the same thing would be happening here. It's going to

0:23:32.859 --> 0:23:37.010
<v Speaker 5>take a while for defenders to catch up. Right now,

0:23:37.510 --> 0:23:40.770
<v Speaker 5>AI helps attackers more than defenders.

0:23:41.540 --> 0:23:44.140
<v Speaker 4>Is the general idea that we're just in this sort

0:23:44.160 --> 0:23:48.730
<v Speaker 4>of awkward phase where a lot of people in cybersecurity

0:23:48.770 --> 0:23:51.850
<v Speaker 4>always refer to technical debt, right? This idea that you

0:23:51.890 --> 0:23:56.170
<v Speaker 4>haven't upgraded a system for ages, like the PHP vulnerability

0:23:56.230 --> 0:23:57.950
<v Speaker 4>we were just discussing, and so now you have to

0:23:57.990 --> 0:24:01.560
<v Speaker 4>pay back that technical debt. The idea that we're just

0:24:01.600 --> 0:24:03.879
<v Speaker 4>in an awkward moment where AI is going to be

0:24:03.960 --> 0:24:08.170
<v Speaker 4>able to exploit existing flaws in the system is But

0:24:08.300 --> 0:24:11.600
<v Speaker 4>maybe we eventually move to a place where we upgrade

0:24:11.660 --> 0:24:12.879
<v Speaker 4>the entire system.

0:24:13.100 --> 0:24:14.820
<v Speaker 1>We reduce our outstanding technical debt.

0:24:14.840 --> 0:24:16.980
<v Speaker 4>We reduce the outstanding technical debt. Exactly.

0:24:17.320 --> 0:24:19.030
<v Speaker 5>That's an optimistic way to look at it.

0:24:19.280 --> 0:24:19.780
<v Speaker 2>Okay.

0:24:20.540 --> 0:24:23.020
<v Speaker 5>You know, we found that there are systems that we

0:24:23.359 --> 0:24:27.370
<v Speaker 5>thought that, okay, that don't have a lot of technical debt.

0:24:27.869 --> 0:24:31.910
<v Speaker 5>That turned out that they just like dumpster fire like

0:24:32.150 --> 0:24:37.260
<v Speaker 5>everybody else. That was a very big surprise to me personally.

0:24:37.800 --> 0:24:41.540
<v Speaker 5>We know there are places, there are bad problems, and

0:24:41.820 --> 0:24:44.619
<v Speaker 5>we know that if we just point AI at that thing,

0:24:44.640 --> 0:24:47.219
<v Speaker 5>there will be a lot of bugs coming out. But

0:24:47.240 --> 0:24:50.520
<v Speaker 5>there are also places we thought that could be okay

0:24:50.740 --> 0:24:55.139
<v Speaker 5>because they received a lot of attention over the years already.

0:24:55.160 --> 0:24:58.060
<v Speaker 5>But it turns out that there's still a lot of

0:24:58.080 --> 0:25:02.180
<v Speaker 5>bugs there as well. And a lot means a lot more,

0:25:02.220 --> 0:25:05.640
<v Speaker 5>like 10x more than we expected. And of course there

0:25:05.660 --> 0:25:10.419
<v Speaker 5>are still like a few small places where there was

0:25:10.880 --> 0:25:13.720
<v Speaker 5>fewer bugs back then before AI. Now there's still fewer

0:25:13.800 --> 0:25:17.500
<v Speaker 5>bugs still now, but they're like very small, like very

0:25:17.640 --> 0:25:21.419
<v Speaker 5>like lit, like they are the exception, not the norms.

0:25:21.840 --> 0:25:26.310
<v Speaker 5>So that's actually a big surprise because I don't think

0:25:26.369 --> 0:25:31.409
<v Speaker 5>anybody was surprised to find a critical vulnerability in PHP.

0:25:32.830 --> 0:25:36.990
<v Speaker 5>because PHP wasn't known for like race security. So of

0:25:37.030 --> 0:25:40.230
<v Speaker 5>course at the PHP 2.0 scale, then that's a different matter.

0:25:40.290 --> 0:25:43.830
<v Speaker 5>But if you find another vulnerability in PHP today, then

0:25:44.090 --> 0:25:47.350
<v Speaker 5>that's not a surprise. But if you go and, you know,

0:25:48.590 --> 0:25:51.929
<v Speaker 5>find a vulnerability or maybe a hundred vulnerabilities, a thousand

0:25:51.950 --> 0:25:55.430
<v Speaker 5>vulnerabilities in the Chrome browser for example, that's a surprise.

0:25:56.250 --> 0:25:59.330
<v Speaker 5>And that's exactly what happened. Like people found like a

0:25:59.350 --> 0:26:03.560
<v Speaker 5>thousand vulnerabilities in Chrome and you know, I was at

0:26:03.580 --> 0:26:07.760
<v Speaker 5>Google and I knew, and then the entire industry like

0:26:07.920 --> 0:26:12.080
<v Speaker 5>assumed that and knew that, wow, there was a lot

0:26:12.100 --> 0:26:16.870
<v Speaker 5>of investment in Chrome security. And not just like, you know, remove,

0:26:17.109 --> 0:26:20.969
<v Speaker 5>like eliminate vulnerabilities, but making sure that even if you

0:26:20.990 --> 0:26:24.470
<v Speaker 5>have vulnerabilities, it's difficult to exploit these vulnerabilities. This is

0:26:24.510 --> 0:26:28.050
<v Speaker 5>what we call mitigations. You accept that you have vulnerabilities,

0:26:28.670 --> 0:26:32.700
<v Speaker 5>but then you make sure that like attackers couldn't use

0:26:32.720 --> 0:26:36.979
<v Speaker 5>these vulnerabilities to control your computer or your browser. We

0:26:37.010 --> 0:26:40.970
<v Speaker 5>thought that, you know, the defense layers were pretty good

0:26:41.670 --> 0:26:47.390
<v Speaker 5>and the rate of vulnerabilities were low. But then after AI,

0:26:47.710 --> 0:26:53.379
<v Speaker 5>we just discovered that either like we, as security engineers,

0:26:54.280 --> 0:26:58.310
<v Speaker 5>suck at our job. We couldn't find these things. Or

0:26:58.690 --> 0:27:01.530
<v Speaker 5>they're just like too much code that we didn't have

0:27:01.609 --> 0:27:02.930
<v Speaker 5>enough time to look into.

0:27:03.350 --> 0:27:08.320
<v Speaker 1>So this raises another question. Like, is it possible to

0:27:08.359 --> 0:27:11.939
<v Speaker 1>have a provably secure browser or a piece of software?

0:27:12.000 --> 0:27:15.080
<v Speaker 1>You ship the piece of software and you can prove

0:27:15.180 --> 0:27:18.300
<v Speaker 1>maybe in the same way that mathematicians produce things and

0:27:18.320 --> 0:27:21.139
<v Speaker 1>this thing called lean or whatever. Does cyber have an

0:27:21.200 --> 0:27:25.219
<v Speaker 1>equivalent where you could say, This is provably secure. And

0:27:25.270 --> 0:27:28.609
<v Speaker 1>we know that no matter how good AI gets, it

0:27:28.650 --> 0:27:31.670
<v Speaker 1>will never find a vulnerability in this piece of software.

0:27:32.470 --> 0:27:35.800
<v Speaker 2>Oh, man, this is a loaded question, Joe.

0:27:36.020 --> 0:27:37.060
<v Speaker 1>I thought it was a simple question.

0:27:38.640 --> 0:27:38.860
<v Speaker 2>Yeah.

0:27:39.940 --> 0:27:42.650
<v Speaker 3>I don't know, to be honest, you know, like browsers

0:27:42.750 --> 0:27:45.330
<v Speaker 3>are like, you know, its own operating system, like very,

0:27:45.369 --> 0:27:49.830
<v Speaker 3>very complex operating systems. Yeah. And today doing, you know,

0:27:49.850 --> 0:27:53.670
<v Speaker 3>like formally verified software, you know, like it doesn't work

0:27:54.180 --> 0:27:58.520
<v Speaker 3>at that scale. It's typically smaller, smaller software components.

0:27:58.960 --> 0:28:02.040
<v Speaker 1>So there is such thing as formal verification when it

0:28:02.119 --> 0:28:03.240
<v Speaker 1>comes to software.

0:28:03.300 --> 0:28:03.540
<v Speaker 3>Yes.

0:28:03.780 --> 0:28:06.090
<v Speaker 1>You could have small piece of software in which you

0:28:06.140 --> 0:28:09.760
<v Speaker 1>formally prove in the same way that It takes mathematicians

0:28:09.800 --> 0:28:13.340
<v Speaker 1>seven lines to prove the two plus two equals four.

0:28:13.840 --> 0:28:17.240
<v Speaker 1>There is some sort of equivalent for software where you

0:28:17.260 --> 0:28:21.639
<v Speaker 1>can prove these lines of code are secure, but the

0:28:22.220 --> 0:28:26.119
<v Speaker 1>question is the scale of even something like a browser

0:28:26.180 --> 0:28:29.050
<v Speaker 1>is just so enormous. That's a very difficult thing to do.

0:28:29.230 --> 0:28:29.470
<v Speaker 4>Yes.

0:28:30.369 --> 0:28:33.990
<v Speaker 3>It's something that I think is being researched right now

0:28:34.350 --> 0:28:38.489
<v Speaker 3>because I think this is one of the paths forward

0:28:38.600 --> 0:28:44.460
<v Speaker 3>to build more secure systems. For example, we've had systems

0:28:44.520 --> 0:28:47.960
<v Speaker 3>where the core of it is formally verified. It's an

0:28:48.000 --> 0:28:51.680
<v Speaker 3>operating system that's formally verified, but then there are applications

0:28:51.720 --> 0:28:56.800
<v Speaker 3>running on these things. Those applications... that have issues. So

0:28:57.420 --> 0:29:01.489
<v Speaker 3>it's complicated. And these are small systems, right? And you're

0:29:01.510 --> 0:29:04.430
<v Speaker 3>talking about browser. Browser is like many billions of lines

0:29:04.470 --> 0:29:07.590
<v Speaker 3>of code. And so that's, yeah, I mean, I can

0:29:07.610 --> 0:29:09.490
<v Speaker 3>tell you how big Chrome is. I mean, they have

0:29:09.530 --> 0:29:12.830
<v Speaker 3>like zillions of people working on it. And, you know,

0:29:12.950 --> 0:29:15.969
<v Speaker 3>like lots of people working on Chrome security all these years. But,

0:29:16.230 --> 0:29:18.530
<v Speaker 3>you know, it's, but long story short, there are such things,

0:29:18.850 --> 0:29:21.230
<v Speaker 3>but to make it work on a browser or at

0:29:21.270 --> 0:29:25.120
<v Speaker 3>a very, very large system, Like, this is, we don't

0:29:25.580 --> 0:29:26.740
<v Speaker 3>have anything like that today.

0:29:26.900 --> 0:29:27.260
<v Speaker 4>Got it.

0:29:27.380 --> 0:29:31.380
<v Speaker 5>I think there's a deeper reason here. You know, the

0:29:31.440 --> 0:29:35.170
<v Speaker 5>reason like software is eating the world. You can see like,

0:29:35.250 --> 0:29:37.830
<v Speaker 5>you know, the top, the biggest companies in the world

0:29:37.850 --> 0:29:42.080
<v Speaker 5>are software companies, right? It's because software is easy to change.

0:29:42.820 --> 0:29:46.700
<v Speaker 5>And imagine, you know, that allows like software companies to

0:29:46.840 --> 0:29:51.380
<v Speaker 5>adapt and to learn much quicker than the rest of

0:29:51.420 --> 0:29:53.700
<v Speaker 5>the world. You have a product, if that doesn't work,

0:29:54.020 --> 0:29:56.900
<v Speaker 5>then tomorrow, tonight, you can change it. And that's actually

0:29:56.940 --> 0:30:00.820
<v Speaker 5>allows the software world, you know, to become, uh, to

0:30:00.840 --> 0:30:05.160
<v Speaker 5>dominate the world basically. So basically fundamentally software is easy

0:30:05.200 --> 0:30:08.400
<v Speaker 5>to change and people want to change it constantly. And

0:30:08.440 --> 0:30:12.270
<v Speaker 5>that's the reason why, you know, uh, the tech companies

0:30:12.330 --> 0:30:15.770
<v Speaker 5>are doing so well. So if you ask like, okay,

0:30:15.910 --> 0:30:20.130
<v Speaker 5>now let's not change this like frequently, uh, then that

0:30:20.190 --> 0:30:21.390
<v Speaker 5>goes against the interest.

0:30:21.470 --> 0:30:21.730
<v Speaker 2>Right.

0:30:22.590 --> 0:30:26.310
<v Speaker 5>And that's not going to happen. So it means that

0:30:26.550 --> 0:30:32.030
<v Speaker 5>even if you have a way to formally verify everything,

0:30:32.210 --> 0:30:33.890
<v Speaker 5>that would take a lot of time unless you have

0:30:34.050 --> 0:30:40.140
<v Speaker 5>some sort of AI help you do the formal verification automatically. Otherwise,

0:30:40.180 --> 0:30:42.520
<v Speaker 5>it's not going to happen because people want to change

0:30:42.560 --> 0:30:46.420
<v Speaker 5>their software as quick as possible because that's how they

0:30:46.900 --> 0:30:47.400
<v Speaker 5>do business.

0:31:03.740 --> 0:31:06.700
<v Speaker 4>This is sort of a related question, but does AI

0:31:06.820 --> 0:31:10.640
<v Speaker 4>start to change, I guess, the way or like the

0:31:10.700 --> 0:31:13.700
<v Speaker 4>waterfall of the way things get fixed? So nowadays it's

0:31:13.720 --> 0:31:18.110
<v Speaker 4>like a vulnerability is discovered. The software company issues an

0:31:18.170 --> 0:31:21.690
<v Speaker 4>alert and a patch. They disclose it and then people

0:31:21.730 --> 0:31:26.190
<v Speaker 4>go off and fix it. If exploits are coming faster,

0:31:26.530 --> 0:31:29.310
<v Speaker 4>does that process start to change in any way?

0:31:29.930 --> 0:31:32.600
<v Speaker 5>Yeah, it changed a lot. Basically, back in the day,

0:31:32.760 --> 0:31:36.940
<v Speaker 5>we have like two kinds of vulnerabilities, like zero-day vulnerabilities

0:31:37.180 --> 0:31:40.080
<v Speaker 5>that nobody knows about except the person who filed it.

0:31:40.820 --> 0:31:46.830
<v Speaker 5>And then end-day vulnerabilities, the vulnerabilities have been disclosed and

0:31:47.050 --> 0:31:50.310
<v Speaker 5>maybe fixed by the vendors and maybe users have upgraded

0:31:50.470 --> 0:31:53.730
<v Speaker 5>or not. But now we also have something we call

0:31:53.810 --> 0:32:00.870
<v Speaker 5>like minus one-day vulnerabilities. So these vulnerabilities... happen when, you know,

0:32:01.410 --> 0:32:06.550
<v Speaker 5>imagine like, let's take the PHP wannabe as an example.

0:32:07.090 --> 0:32:10.340
<v Speaker 5>Let's say that, you know, because PHP Foundation and PHP

0:32:10.410 --> 0:32:15.040
<v Speaker 5>itself is an open source project, everything happens on GitHub, right?

0:32:15.520 --> 0:32:19.280
<v Speaker 5>And imagine, let's imagine that we reported a bug and

0:32:19.520 --> 0:32:25.660
<v Speaker 5>PHP fixed the bug publicly on GitHub. The moment we

0:32:25.740 --> 0:32:31.380
<v Speaker 5>found the bug and then PHP produce a patch for

0:32:31.420 --> 0:32:38.040
<v Speaker 5>that bug, that very moment, that information became public. Somebody

0:32:38.140 --> 0:32:43.260
<v Speaker 5>who is watching the PHP repository on GitHub, they could

0:32:43.420 --> 0:32:48.650
<v Speaker 5>turn that away into an exploit within a few hours.

0:32:49.390 --> 0:32:52.930
<v Speaker 5>Of course, the vulnerability that we found was more complicated

0:32:52.970 --> 0:32:56.590
<v Speaker 5>than that. But you can imagine that in principle, the

0:32:56.630 --> 0:33:01.120
<v Speaker 5>window between the passwords being developed, it's not ready yet,

0:33:01.500 --> 0:33:05.500
<v Speaker 5>you know, for anybody. And before it's become ready for

0:33:05.620 --> 0:33:10.130
<v Speaker 5>end user to upgrade, there's a window, right? In the past,

0:33:10.530 --> 0:33:15.170
<v Speaker 5>you know, the attacker has to wait until the past

0:33:15.210 --> 0:33:18.850
<v Speaker 5>become available. And then it would take them a long

0:33:18.890 --> 0:33:22.530
<v Speaker 5>time to develop and exploit. So user can have longer

0:33:22.590 --> 0:33:27.520
<v Speaker 5>time to upgrade. Now that window is collapsing. It is

0:33:27.580 --> 0:33:31.400
<v Speaker 5>collapsing everywhere, not just in PHP, right? In Windows, in

0:33:31.560 --> 0:33:36.640
<v Speaker 5>Mac OS, in anything. Because right now there are people

0:33:37.100 --> 0:33:41.360
<v Speaker 5>who have like what we call like end day factory.

0:33:41.560 --> 0:33:46.340
<v Speaker 5>You know, they're just waiting for patches from Microsoft, from Apple,

0:33:46.420 --> 0:33:51.780
<v Speaker 5>from important critical software. Like I'm sure tens of people

0:33:51.840 --> 0:33:57.500
<v Speaker 5>are watching PHP today. After what happened, they're watching PHP, Python, Java,

0:33:58.000 --> 0:34:02.130
<v Speaker 5>all of those important languages. And if there is any

0:34:02.210 --> 0:34:05.130
<v Speaker 5>sign of like, oh, there's a new vulnerability, they're going

0:34:05.150 --> 0:34:10.050
<v Speaker 5>to like, you know, their AI would go pro and then,

0:34:10.140 --> 0:34:15.050
<v Speaker 5>you know, bundling tokens to identify that vulnerability, reproduce it,

0:34:15.440 --> 0:34:21.110
<v Speaker 5>be an exploit for it. So that changed the... the practice, right?

0:34:21.330 --> 0:34:21.529
<v Speaker 2>Yeah.

0:34:21.790 --> 0:34:26.030
<v Speaker 1>I'm curious what you thought after the hugging face incident,

0:34:26.110 --> 0:34:28.830
<v Speaker 1>because after that moment, there were sort of two schools

0:34:28.890 --> 0:34:31.069
<v Speaker 1>of thought that I thought there's, or that I perceived.

0:34:31.320 --> 0:34:34.620
<v Speaker 1>There's one that was like AI creature, there was this

0:34:34.640 --> 0:34:38.660
<v Speaker 1>sort of, I guess maybe the anthropomorphic Asian view, AI creatures,

0:34:38.680 --> 0:34:42.799
<v Speaker 1>they want to escape their cages. They're devious, they're tricksters.

0:34:42.860 --> 0:34:45.360
<v Speaker 1>They want to show, come up with a way to

0:34:45.440 --> 0:34:48.359
<v Speaker 1>cheat on the right answers, but cheat on the way

0:34:48.540 --> 0:34:51.100
<v Speaker 1>that the greater, you know, all these stories. And then

0:34:51.120 --> 0:34:54.290
<v Speaker 1>there are other people that were just like, guys, build

0:34:54.330 --> 0:34:57.089
<v Speaker 1>a stronger sandbox. Stop talking about all this stuff. Just

0:34:57.110 --> 0:35:00.080
<v Speaker 1>build a stronger sandbox. Jensen Wong is kind of in

0:35:00.120 --> 0:35:03.020
<v Speaker 1>that category. I loved his interview with Ezra Klein, where

0:35:03.080 --> 0:35:06.520
<v Speaker 1>he was basically like, what's your problem? Just make models

0:35:06.580 --> 0:35:09.580
<v Speaker 1>that don't hack. He's like, just don't ship it. Fix

0:35:09.600 --> 0:35:12.299
<v Speaker 1>your model. Don't let them hack. And I love that

0:35:12.540 --> 0:35:15.279
<v Speaker 1>because it's just like, just fix it. And the AI

0:35:15.300 --> 0:35:17.299
<v Speaker 1>people are like, no, no, no, we can't. You don't understand.

0:35:17.340 --> 0:35:20.050
<v Speaker 1>We haven't solved alignment. It's very tricky. And he's like,

0:35:20.130 --> 0:35:23.589
<v Speaker 1>just fix the model. And I'm sort of curious, as

0:35:23.670 --> 0:35:26.370
<v Speaker 1>people who have come out of the traditional cyber world,

0:35:26.650 --> 0:35:30.319
<v Speaker 1>but are now in the AI world, Where do you

0:35:30.400 --> 0:35:32.779
<v Speaker 1>land on this question? Can you just like, guys, just

0:35:32.840 --> 0:35:35.359
<v Speaker 1>fix the sandbox, or is there something deeper here?

0:35:35.660 --> 0:35:38.200
<v Speaker 5>I don't think that it's simple to fix the sandbox.

0:35:38.430 --> 0:35:41.129
<v Speaker 5>That's the problem. People think that, you know, maybe people

0:35:41.150 --> 0:35:44.090
<v Speaker 5>are not insecure. They think that there's a simple solution

0:35:44.110 --> 0:35:47.670
<v Speaker 5>to cybersecurity. Just do this thing and you're safe. And

0:35:47.690 --> 0:35:50.630
<v Speaker 5>that's how we have so many problems, you know. Vendors

0:35:50.730 --> 0:35:54.210
<v Speaker 5>go out and tell people, just buy this box, this

0:35:54.290 --> 0:35:57.739
<v Speaker 5>magic box. and put it in your network and you'll

0:35:57.760 --> 0:36:00.560
<v Speaker 5>be safe. No, it's not like that. Even that box

0:36:00.680 --> 0:36:04.230
<v Speaker 5>has problems. If you look into like, there's a famous

0:36:04.870 --> 0:36:08.509
<v Speaker 5>idea in security, like product security is not the same

0:36:08.570 --> 0:36:12.710
<v Speaker 5>as security product. Like security products may not have product security.

0:36:13.410 --> 0:36:17.470
<v Speaker 5>Even like the firewalls that you buy, they may have problems.

0:36:17.930 --> 0:36:22.130
<v Speaker 5>And they do. And what I mean here is, so...

0:36:22.700 --> 0:36:25.520
<v Speaker 5>What we found, like the Hugging Face and OpenAI incident

0:36:25.560 --> 0:36:31.040
<v Speaker 5>was fascinating, right? To watch. And it's difficult. Enterprise security

0:36:31.080 --> 0:36:35.400
<v Speaker 5>is very difficult. Anybody saying like, oh, just buy this thing,

0:36:35.460 --> 0:36:38.100
<v Speaker 5>just do that thing, you're going to be safe. No,

0:36:38.420 --> 0:36:43.120
<v Speaker 5>it's just like very complicated. And the reason is like,

0:36:43.320 --> 0:36:45.320
<v Speaker 5>and then people say, oh, just fix the model. And

0:36:45.360 --> 0:36:46.660
<v Speaker 5>that's a comeback to the- And.

0:36:46.620 --> 0:36:48.940
<v Speaker 1>Just fix the model, just make one that doesn't hack.

0:36:49.390 --> 0:36:51.910
<v Speaker 5>That comes back to the incentive again. And because if

0:36:51.930 --> 0:36:56.259
<v Speaker 5>you look at like how AI companies, and Jensen must

0:36:56.300 --> 0:36:58.420
<v Speaker 5>be careful here, right? Because if AI company is not

0:36:58.460 --> 0:37:00.600
<v Speaker 5>making money, he's not making money as well.

0:37:00.620 --> 0:37:01.200
<v Speaker 2>Yeah, of course.

0:37:01.460 --> 0:37:06.600
<v Speaker 5>And the AI companies, they're making money by selling tokens.

0:37:07.060 --> 0:37:09.740
<v Speaker 5>And most of the tokens are used for coding today,

0:37:09.760 --> 0:37:13.489
<v Speaker 5>like programming, building things, right? And if you build, if

0:37:13.530 --> 0:37:15.950
<v Speaker 5>you want to be really good at coding, you need

0:37:16.530 --> 0:37:21.540
<v Speaker 5>an agent on AI that understands code understand technical problems,

0:37:21.880 --> 0:37:26.430
<v Speaker 5>can debug things, can control computers. But that's basically the

0:37:26.469 --> 0:37:30.870
<v Speaker 5>definition of a hacker. So you cannot really escape this.

0:37:30.890 --> 0:37:33.509
<v Speaker 5>You cannot have a cake and eat it too, right?

0:37:33.640 --> 0:37:36.620
<v Speaker 5>You need to be good at coding. Then you have

0:37:36.640 --> 0:37:41.000
<v Speaker 5>an AI that is good at hacking. So unless you

0:37:41.020 --> 0:37:44.279
<v Speaker 5>don't want spend more tokens, or you don't want to

0:37:44.320 --> 0:37:49.200
<v Speaker 5>get into the coding business anymore, you focus on scientific discovery,

0:37:49.719 --> 0:37:55.880
<v Speaker 5>physical AI, whatever, then maybe you can train a model

0:37:56.060 --> 0:38:00.149
<v Speaker 5>that is not good at hacking anymore. But as long

0:38:00.310 --> 0:38:06.070
<v Speaker 5>as you want to automate knowledge work, then eventually your

0:38:06.530 --> 0:38:09.110
<v Speaker 5>AI must be able to use computers and control computers

0:38:09.130 --> 0:38:13.130
<v Speaker 5>to understand technical problems. And that's the reason of someone

0:38:13.150 --> 0:38:16.609
<v Speaker 5>like Bruce. So it's unavoidable.

0:38:17.050 --> 0:38:19.649
<v Speaker 4>So actually, on this note, I'm curious, can you just

0:38:19.690 --> 0:38:23.489
<v Speaker 4>talk about what it's like being a hacker in the

0:38:23.610 --> 0:38:28.600
<v Speaker 4>age of AI versus, say, even three or four years ago, right? Like,

0:38:28.680 --> 0:38:31.700
<v Speaker 4>it's crazy how quickly stuff has shifted. But how has

0:38:31.739 --> 0:38:33.420
<v Speaker 4>your day to day changed?

0:38:34.160 --> 0:38:37.270
<v Speaker 3>Yeah, I'll just use some background. So I wrote a

0:38:37.310 --> 0:38:41.750
<v Speaker 3>textbook with some friends on reverse engineering. It used to

0:38:41.770 --> 0:38:44.290
<v Speaker 3>be like, you know, like you try to like reversing

0:38:44.350 --> 0:38:49.110
<v Speaker 3>is the practice of understanding software without any source code

0:38:49.130 --> 0:38:49.880
<v Speaker 3>or hardware systems.

0:38:50.730 --> 0:38:54.029
<v Speaker 2>That used to be like, I wrote this textbook. And

0:38:54.050 --> 0:38:55.130
<v Speaker 2>then I think with the.

0:38:55.070 --> 0:38:57.410
<v Speaker 3>Advent of AI, I think what, like, you know, whatever,

0:38:57.770 --> 0:39:00.450
<v Speaker 3>nine months ago, as of nine months ago, like that

0:39:00.730 --> 0:39:03.029
<v Speaker 3>entire book is deprecating. It takes like, you know, two

0:39:03.090 --> 0:39:05.270
<v Speaker 3>prompts or one prompt and then bam, it will generate

0:39:05.290 --> 0:39:08.040
<v Speaker 3>the textbook for you. And it's even better, you know,

0:39:08.100 --> 0:39:09.879
<v Speaker 3>and it took us, you know, a long time to write.

0:39:10.560 --> 0:39:13.060
<v Speaker 3>Just that gives you an idea. And then I talk

0:39:13.080 --> 0:39:16.219
<v Speaker 3>to friends who've been doing this for decades, right?

0:39:16.239 --> 0:39:17.719
<v Speaker 2>They're like specialists in this area, right?

0:39:18.560 --> 0:39:20.680
<v Speaker 3>And they tell me that, oh yeah, man, like I spend,

0:39:20.719 --> 0:39:24.219
<v Speaker 3>you know, whatever, $ 5 on some open source model and

0:39:24.260 --> 0:39:27.810
<v Speaker 3>it reverse engineered the firmware on, you know, some Canon

0:39:27.930 --> 0:39:31.180
<v Speaker 3>or like you know, HP printer and it hacks it, Bruce.

0:39:31.300 --> 0:39:33.140
<v Speaker 3>You know, and whereas before it would take me, you know,

0:39:33.180 --> 0:39:35.390
<v Speaker 3>like months to figure some stuff out.

0:39:35.410 --> 0:39:38.090
<v Speaker 2>You know, that's just to give.

0:39:37.969 --> 0:39:43.430
<v Speaker 3>You like a glimpse into what's happening, like how quickly

0:39:43.469 --> 0:39:44.140
<v Speaker 3>things change.

0:39:44.880 --> 0:39:48.700
<v Speaker 2>Well, a friend, you know, like this guy, Matt Swish, he's,

0:39:48.719 --> 0:39:49.939
<v Speaker 2>you know, and he's this dude.

0:39:50.120 --> 0:39:52.060
<v Speaker 4>He's a friend of the show.

0:39:52.300 --> 0:39:54.960
<v Speaker 1>A longtime friend of the show, multi-time guest.

0:39:55.000 --> 0:39:55.360
<v Speaker 5>Yeah, keep going.

0:39:55.400 --> 0:39:58.719
<v Speaker 4>We used to hang out in Abu Dhabi a lot.

0:39:58.910 --> 0:40:01.070
<v Speaker 2>Oh, okay, yeah. Like, I'm no Matt Fawkes.

0:40:01.130 --> 0:40:03.950
<v Speaker 3>I mean, like, now he's like, he gave a talk

0:40:04.050 --> 0:40:06.130
<v Speaker 3>with our team the other day, and he showed his rack,

0:40:06.150 --> 0:40:11.690
<v Speaker 3>you know, in his apartment, and he's sitting there, you know, like,

0:40:11.790 --> 0:40:17.060
<v Speaker 3>hacking stuff, like, while he's sitting there talking. It's just insane.

0:40:17.620 --> 0:40:20.259
<v Speaker 3>We have people that, let's say, for example, we've been

0:40:20.280 --> 0:40:24.320
<v Speaker 3>hacking the iPhone. To build a full chain on the iPhone,

0:40:24.800 --> 0:40:28.120
<v Speaker 3>it's not an easy task. Sometimes it takes several people

0:40:28.400 --> 0:40:33.080
<v Speaker 3>to do this. And our team was able to do

0:40:33.120 --> 0:40:36.299
<v Speaker 3>this within.

0:40:35.600 --> 0:40:36.120
<v Speaker 2>A few days.

0:40:36.750 --> 0:40:37.050
<v Speaker 3>Wow.

0:40:37.090 --> 0:40:39.330
<v Speaker 2>You know, as a one person. And we have multiple

0:40:39.350 --> 0:40:39.950
<v Speaker 2>of these chains.

0:40:40.550 --> 0:40:45.719
<v Speaker 3>It really compresses the time, like the exploitation, the time

0:40:45.760 --> 0:40:48.600
<v Speaker 3>to build exploits.

0:40:49.960 --> 0:40:52.339
<v Speaker 2>We see customers getting hacked.

0:40:52.520 --> 0:40:56.740
<v Speaker 3>By AI, you know, in the financials, in the banks, basically.

0:40:56.760 --> 0:41:00.109
<v Speaker 3>You know, defenders cannot, you know, actually, Ty, why don't

0:41:00.130 --> 0:41:01.650
<v Speaker 3>you tell these stories?

0:41:01.730 --> 0:41:03.450
<v Speaker 2>And, you know, just a little bit, this has happened

0:41:03.469 --> 0:41:06.650
<v Speaker 2>in the last few weeks, you know. Yeah. how things changed.

0:41:07.190 --> 0:41:10.590
<v Speaker 5>Yeah, basically we saw like, you know, in the OpenAI

0:41:10.630 --> 0:41:15.220
<v Speaker 5>and HackingFace incident, there's one detail that is very interesting.

0:41:15.239 --> 0:41:19.360
<v Speaker 5>I'm not sure if people noticed, but OpenAI noticed that

0:41:19.560 --> 0:41:23.880
<v Speaker 5>like the people who handled incidents on the OpenAI side,

0:41:23.900 --> 0:41:26.010
<v Speaker 5>they said that they have handled a lot of incidents,

0:41:26.070 --> 0:41:28.750
<v Speaker 5>but this is the first time they saw that, you know,

0:41:28.770 --> 0:41:33.820
<v Speaker 5>an incident where you have like a hundred people points

0:41:34.000 --> 0:41:37.430
<v Speaker 5>within your networks that were compromised at the same time.

0:41:38.150 --> 0:41:41.170
<v Speaker 5>Like there were a hundred like hackers within your system.

0:41:42.050 --> 0:41:44.989
<v Speaker 5>Normally you have maybe one or two, right? Now you

0:41:45.030 --> 0:41:47.410
<v Speaker 5>have a hundred. And I saw that I was like, wow,

0:41:47.450 --> 0:41:51.000
<v Speaker 5>that was pretty interesting, but maybe because OpenAI have lots

0:41:51.020 --> 0:41:54.420
<v Speaker 5>of tokens, so their agents can just go, you know,

0:41:54.480 --> 0:41:58.299
<v Speaker 5>hack everything. And then just two weeks ago, we have

0:41:58.400 --> 0:42:02.489
<v Speaker 5>like two clients in the banking industry. And they got

0:42:02.530 --> 0:42:04.830
<v Speaker 5>hacked and they called us to help them with like

0:42:05.030 --> 0:42:08.750
<v Speaker 5>the incident response. We came in because we do hacking

0:42:08.810 --> 0:42:11.049
<v Speaker 5>as well. We know like usually it took us like

0:42:11.090 --> 0:42:13.739
<v Speaker 5>maybe a month or something. Once we come in a

0:42:13.760 --> 0:42:16.440
<v Speaker 5>network and then took a month for us to spread out.

0:42:17.180 --> 0:42:19.239
<v Speaker 5>For the AI, it took like, they came in, they

0:42:19.280 --> 0:42:22.780
<v Speaker 5>brought inside the network on Monday. By Tuesday, they're everywhere.

0:42:23.440 --> 0:42:23.820
<v Speaker 3>Everywhere.

0:42:24.219 --> 0:42:27.160
<v Speaker 5>And like, it's like cancer is spread like at a

0:42:27.180 --> 0:42:30.680
<v Speaker 5>machine speed. And it was like mind blowing, right? Because

0:42:30.739 --> 0:42:33.540
<v Speaker 5>how could you defend against that? Like in the past,

0:42:33.940 --> 0:42:36.920
<v Speaker 5>we were telling our clients, you know, you have to

0:42:36.980 --> 0:42:41.279
<v Speaker 5>invest in detection. Well, how can you help yourself? If

0:42:41.630 --> 0:42:43.750
<v Speaker 5>you see it, you can detect it, but there's a

0:42:43.790 --> 0:42:44.310
<v Speaker 5>hundred of them.

0:42:45.270 --> 0:42:45.690
<v Speaker 3>Noted.

0:42:45.890 --> 0:42:48.430
<v Speaker 4>We have a hundred hackers in our system right now.

0:42:48.489 --> 0:42:49.370
<v Speaker 4>It's not really helpful.

0:42:49.570 --> 0:42:50.010
<v Speaker 3>Exactly.

0:42:50.130 --> 0:42:51.650
<v Speaker 5>How could you do it, right? And then you have

0:42:51.670 --> 0:42:53.770
<v Speaker 5>to shut down everything. But shut down is not an

0:42:53.850 --> 0:42:56.890
<v Speaker 5>option because you are a bank. So that's actually true.

0:42:57.260 --> 0:43:00.520
<v Speaker 5>requires us to sit down and think about how to

0:43:00.540 --> 0:43:04.420
<v Speaker 5>redesign the defense system. What we have right now is

0:43:04.460 --> 0:43:08.100
<v Speaker 5>not working very well. But to come back to your question,

0:43:08.180 --> 0:43:12.370
<v Speaker 5>as a hacker, how does it feel? I love history.

0:43:12.850 --> 0:43:15.730
<v Speaker 5>So I always come back to history to see, did

0:43:15.770 --> 0:43:21.250
<v Speaker 5>it happen before? It actually did happen with chess, for example.

0:43:21.670 --> 0:43:26.410
<v Speaker 5>You remember in 1997, You know, IBM Deep Blue defeated

0:43:27.010 --> 0:43:31.910
<v Speaker 5>Garry Kasparov. That was a big moment, right? And then

0:43:31.910 --> 0:43:36.230
<v Speaker 5>20 years later, AlphaGo defeated like Lizzie Doe in the

0:43:36.250 --> 0:43:40.020
<v Speaker 5>game of Go. But those two moments are actually quite different.

0:43:40.700 --> 0:43:44.780
<v Speaker 5>Like the first moment, the Deep Blue moment, after Deep Blue,

0:43:45.380 --> 0:43:49.160
<v Speaker 5>the best chess player wasn't a computer because Deep Blue

0:43:49.219 --> 0:43:52.450
<v Speaker 5>was a mainframe, right? Not something that you can run

0:43:52.510 --> 0:43:56.489
<v Speaker 5>on your computer. And it took 10 years for someone

0:43:56.570 --> 0:44:00.509
<v Speaker 5>to go from Deep Blue to develop a computer software

0:44:00.790 --> 0:44:03.590
<v Speaker 5>that you can run on your computer that defeated everybody.

0:44:04.850 --> 0:44:07.350
<v Speaker 5>But the 10 years, it took 10 years. During that

0:44:07.350 --> 0:44:10.359
<v Speaker 5>10 years, the best chess player was a centaur player.

0:44:10.739 --> 0:44:13.700
<v Speaker 5>This is a term coined by Garry Kasparov. It's a

0:44:13.719 --> 0:44:19.239
<v Speaker 5>combination of computer and human. It took 10 years. For AlphaGo,

0:44:19.360 --> 0:44:24.160
<v Speaker 5>it took like three years. Like after AlphaGo, Then 2019,

0:44:24.160 --> 0:44:27.920
<v Speaker 5>somebody come up with a computer software that defeated anybody

0:44:28.219 --> 0:44:32.280
<v Speaker 5>without any human input at all. At Calif, we think like,

0:44:32.340 --> 0:44:36.710
<v Speaker 5>you know, we are enter the era of the central hackers. Basically,

0:44:36.750 --> 0:44:40.590
<v Speaker 5>the best hacker right now is a combination of AI

0:44:40.670 --> 0:44:44.370
<v Speaker 5>and humans. And, you know, our work and our friends'

0:44:44.430 --> 0:44:48.190
<v Speaker 5>work as well show that AI is powerful. It can

0:44:48.210 --> 0:44:53.180
<v Speaker 5>hack anything. but it still requires a human expert to

0:44:53.200 --> 0:44:55.960
<v Speaker 5>arrive at it. And we don't know how long this

0:44:55.980 --> 0:45:00.920
<v Speaker 5>is going to last, maybe three months. Maybe we come

0:45:00.940 --> 0:45:04.400
<v Speaker 5>back here and by the end of the year, we

0:45:04.420 --> 0:45:06.880
<v Speaker 5>tell you we retire now. There's nothing else for us

0:45:06.920 --> 0:45:10.770
<v Speaker 5>to do. Maybe it lasts like three years. And this

0:45:10.790 --> 0:45:13.270
<v Speaker 5>is actually pretty exciting to find out. That's exactly what

0:45:13.310 --> 0:45:17.210
<v Speaker 5>we want to do. And we think like, That's like

0:45:17.230 --> 0:45:21.710
<v Speaker 5>a pessimistic view, right? AI is going to do everything.

0:45:22.550 --> 0:45:26.569
<v Speaker 5>Let's just retire and hate AI. Or you can see

0:45:26.630 --> 0:45:30.760
<v Speaker 5>AI as a tool. It's like humanity just discovered fire.

0:45:31.640 --> 0:45:35.020
<v Speaker 5>And without fire, we wouldn't be here today. So, of course,

0:45:35.080 --> 0:45:37.960
<v Speaker 5>we have to think about how to control fire. At

0:45:38.000 --> 0:45:40.419
<v Speaker 5>the same time, a very important question that we need

0:45:40.440 --> 0:45:45.250
<v Speaker 5>to ask is, what should we cook, right? That's very important,

0:45:45.370 --> 0:45:47.750
<v Speaker 5>and we want to find out What can we cook

0:45:47.770 --> 0:45:51.050
<v Speaker 5>with AI and how can we do it in a

0:45:51.090 --> 0:45:53.150
<v Speaker 5>safe way that helps everybody?

0:45:53.450 --> 0:45:55.370
<v Speaker 4>Protein that makes our brains get bigger.

0:45:55.469 --> 0:45:56.830
<v Speaker 3>Yeah. All right.

0:45:56.890 --> 0:45:59.660
<v Speaker 4>Well, Ty and Bruce from Calif, thank you so much

0:45:59.680 --> 0:46:00.839
<v Speaker 4>for coming on All Thoughts.

0:46:00.880 --> 0:46:03.660
<v Speaker 1>That was a lot of fun. You're both excellent. Thank

0:46:03.700 --> 0:46:04.120
<v Speaker 1>you both.

0:46:04.400 --> 0:46:04.720
<v Speaker 5>Thanks.

0:46:05.040 --> 0:46:06.000
<v Speaker 2>Thanks, Joe. Thanks, Tracy.

0:46:06.060 --> 0:46:06.360
<v Speaker 5>Thank you.

0:46:06.380 --> 0:46:06.680
<v Speaker 2>Bye-bye.

0:46:06.700 --> 0:46:10.040
<v Speaker 3>Bye-bye.

0:46:19.600 --> 0:46:23.980
<v Speaker 4>Joe, I thought that was a fantastic conversation. Not exactly uplifting.

0:46:24.440 --> 0:46:29.439
<v Speaker 4>I was surprised at Ty's response. I thought maybe people

0:46:29.480 --> 0:46:32.040
<v Speaker 4>would say we're in this weird, awkward moment where a

0:46:32.080 --> 0:46:35.569
<v Speaker 4>lot of legacy issues are being discovered. But once AI

0:46:35.780 --> 0:46:39.290
<v Speaker 4>actually gets deployed and starts redesigning some of the architecture,

0:46:39.810 --> 0:46:42.890
<v Speaker 4>it'll be a lot more resilient. Apparently that's not the case.

0:46:42.930 --> 0:46:44.110
<v Speaker 4>That's a little bit worrying.

0:46:44.410 --> 0:46:46.790
<v Speaker 1>I agree. There was so much in there that was interesting.

0:46:46.989 --> 0:46:50.450
<v Speaker 1>And like I could, you know, all this stuff about how, yes,

0:46:50.469 --> 0:46:53.440
<v Speaker 1>you could have provably secure software, but it's small. You

0:46:53.460 --> 0:46:55.740
<v Speaker 1>can't even do it for something that says the browser.

0:46:56.219 --> 0:46:58.719
<v Speaker 1>I love that last point about how we're in the

0:46:58.800 --> 0:47:02.900
<v Speaker 1>centaur age where the strongest hacker is the computer working

0:47:02.920 --> 0:47:05.760
<v Speaker 1>with a human, but that may not be there for

0:47:05.800 --> 0:47:08.150
<v Speaker 1>much longer. Three months, a year. We have no idea,

0:47:08.230 --> 0:47:12.190
<v Speaker 1>but the presumption should be that it won't last very long. etc.

0:47:12.469 --> 0:47:16.239
<v Speaker 4>Also, the idea of like a computer, an agent that

0:47:16.280 --> 0:47:21.160
<v Speaker 4>can code is inherently a hacker. And so you can't

0:47:21.200 --> 0:47:23.590
<v Speaker 4>just tell it not to hack.

0:47:23.610 --> 0:47:25.430
<v Speaker 1>Just teach it not to hack. What's wrong with you?

0:47:25.469 --> 0:47:28.129
<v Speaker 1>Just teach it not to hack. If coding is going

0:47:28.150 --> 0:47:30.400
<v Speaker 1>to be big business, which it is, you're going to

0:47:30.420 --> 0:47:31.460
<v Speaker 1>be building a lot of good hackers.

0:47:31.520 --> 0:47:31.840
<v Speaker 5>Yeah.

0:47:31.980 --> 0:47:34.759
<v Speaker 4>And so the hackers proliferate. On that note, shall we

0:47:34.780 --> 0:47:35.120
<v Speaker 4>leave it there?

0:47:35.200 --> 0:47:35.700
<v Speaker 1>Let's leave it there.

0:47:35.940 --> 0:47:38.360
<v Speaker 4>This has been another episode of the All Thoughts Podcast.

0:47:38.460 --> 0:47:41.180
<v Speaker 4>I'm Traci Allaway. You can follow me at Traci Allaway.

0:47:41.360 --> 0:47:44.430
<v Speaker 1>And I'm Joe Wiesenthal. You can follow me at The Stalwart.

0:47:44.510 --> 0:47:48.109
<v Speaker 1>Follow our producers, Carmen Rodriguez at Carmen Arman, Dashiell Bennett

0:47:48.210 --> 0:47:51.370
<v Speaker 1>at Dashbot, Cale Brooks at Cale Brooks. and Kevin Lozano

0:47:51.489 --> 0:47:54.069
<v Speaker 1>at Kevin Lloyd Lozano. And of course, you can chat

0:47:54.090 --> 0:47:58.469
<v Speaker 1>about all of these topics 24-7 in our Discord, discord.gg

0:47:58.510 --> 0:48:01.430
<v Speaker 1>slash oddlots. And for more Oddlots content, you can check

0:48:01.469 --> 0:48:04.339
<v Speaker 1>out our daily newsletter, which you can find at bloomberg.com

0:48:04.380 --> 0:48:05.110
<v Speaker 1>slash oddlots.

0:48:05.280 --> 0:48:07.480
<v Speaker 4>And if you enjoyed this conversation, if you like it

0:48:07.540 --> 0:48:09.560
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0:48:12.690 --> 0:48:15.510
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0:48:27.980 --> 0:48:45.859
<v Speaker 4>Thanks for joining. Thank you.