PHP2Shell Won't Be the Last Big AI Cybersecurity Risk

Earlier this year, cybersecurity researchers discovered a vulnerability in PHP, an open-source coding language used in roughly 70% of the world's websites, that had been lying dormant for a long time, and if exploited, could have led to disaster. And the researchers only understood the extent of this bug through the use of frontier AI models. Today, we talk to two staffers at Calif (CEO Thai Duong and engineer Bruce Dang), the cybersecurity firm that was among the first to discover the PHP vulnerability. Their firm partners with the major AI labs and neoclouds, and they help these companies test models and look for vulnerabilities in their infrastructure. Duong and Dang tell us how Calif uncovered the PHP hack, what the firm exactly sells, and what the future of cybersecurity looks like in the age of AI. Read more: How AI Is Making Cyberattacks a Bigger Threat https://www.bloomberg.com/news/articles/2026-10-29/ai-and-cybersecurity-why-cyberattacks-are-getting-harder-to-stop?utm_medium=referral&utm_source=podcast&utm_campaign=odd_lots&utm_content=article Japan’s Cyberattack Surge Tests Its Push to Strengthen Defenses https://www.bloomberg.com/news/articles/2026-10-29/japan-s-cyberattack-surge-tests-its-push-to-strengthen-defenses?utm_medium=referral&utm_source=podcast&utm_campaign=odd_lots&utm_content=article Only http://Bloomberg.com subscribers can get the Odd Lots newsletter in their inbox each week, plus unlimited access to the site and app. Subscribe at bloomberg.com/subscriptions/oddlots https://www.bloomberg.com/subscriptions/oddlots?in_source=oddlotspodcast Subscribe to the Odd Lots Newsletter http://bloomberg.com/subscriptions/oddlots Join the conversation: discord.gg/oddlots https://discord.gg/oddlots See omnystudio.com/listener https://omnystudio.com/listener for privacy information.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Tracy Alloway?

  There are some market stories where you want every detail. Joe and I have made quite a few podcasts on that basis. But sometimes you've only got 10 minutes and just want to know what's moving markets fast. That's the Barclays Brief Podcast. Every week, experts from Barclays Markets and Research get you up to speed on what's happening and what to watch next. Concise, focused, and brief. Search Barclays Brief wherever you get your podcasts.

• 0:26Speaker 01

  This is the Bloomberg Tech Minute brought to you by ChatGPT. I'm Carol Muster. Getting hired at SpaceX requires exceptional ability and may include having Elon Musk review a candidate's resume. So writes Bloomberg Business Week's Lauren Grush. She reports that the company culture is defined by Musk and job candidates must understand that a commitment to SpaceX means adhering to this culture and exhibiting loyalty to Elon Musk. To get hired, candidates must demonstrate their achievements from past jobs. And hands-on experience matters more to recruiters than advanced degrees, with the company looking for people with raw innate intelligence. A spokesperson for SpaceX didn't respond to a request for comment on its recruiting and hiring practices.

• 1:10Speaker 01

  But according to recruiters, advisors, and those who've interviewed for jobs there, it's the space exploration dream that draws people to the company. And Musk invokes that dream regularly to remind workers why they're there. Prospective hires are told that the job will require stamina, including in job ads that candidates, quote, "must be willing to work extended hours and weekends as needed." One major perk for all that hard work? Employees' access to equity, either the right to buy shares or payment in the form of restricted stock units that vest over time. That's the Bloomberg Tech Minute brought to you by ChatGPT. Get started at chatgpt.com.

• 1:52Speaker 01

  Bloomberg Audio Studios, podcasts, radio, news.

• 2:07Tracy Alloway?

  Hello and welcome to another episode of the Odd Lots Podcast. I'm Tracy Alloway.

• 2:11Joe Weisenthal?

  And I'm Joe Weisenthal.

• 2:13Tracy Alloway?

  Joe, it's October. We're recording this on October 29.

• 2:16Joe Weisenthal?

  Yeah.

• 2:17Tracy Alloway?

  It is also Black October. Have you heard this term?

• 2:19Joe Weisenthal?

  Yeah, what does that mean? Have stocks gone down?

• 2:22Tracy Alloway?

  No, your mind immediately goes to markets. There are other worlds out there. We're going to be talking about the world of cybersecurity today because one of the reasons people are talking about Black October is we've had a number of recent security issues. The most prominent of which has been a bunch of vulnerabilities discovered in PHP, which is a coding language that apparently is used by 70% of websites in existence. We can get into that stat later. But the really interesting thing about this vulnerability being uncovered is AI was used to uncover it. And so the big question, coming back to AI, you know, there's a concern now that you have good actors who are maybe using AI to discover old vulnerabilities

• 3:06Tracy Alloway?

  and trying to fix them. But you could also have bad actors who are using AI to exploit those same vulnerabilities. So we're back to the question of whether AI makes the internet safer or more dangerous.

• 3:18Joe Weisenthal?

  Makes it more dangerous. No, I have no idea. Ever since essentially Anthropic announced that they had this model called Methos and announced Project Glasswing, in which it was rolled out to companies to use for defensive purposes before it was available to the general public, there's been much more awareness of cybersecurity issues as it relates to AI. And there are many things that people debate about AI and some of these bigger existential questions. Pretty much everyone agrees cybersecurity good, more cybersecurity good. I will say I know very little about the world of cybersecurity. I don't know what, for example, a cybersecurity company actually sells. I don't know how, if I were buying cybersecurity, I would know whether it's working or whether no one had tried to hack me or not,

• 4:03Joe Weisenthal?

  or something like that. I need to learn a lot more, but it's absolutely true about the uptick in the volume of hacks.

• 4:09Tracy Alloway?

  There are hackers out there right now taking notes going, Joe doesn't know anything about cybersecurity, probably doesn't have a VPN.

• 4:15Joe Weisenthal?

  I don't. That's why my vibe coding projects, I don't want to ever, I have yet to build anything with an account because I don't want to like have to think about that. So it's just like, I don't want to count information with anyone. But I have, as a user of technical products, over the last several weeks, you get more emails saying like, our thing was compromised. You're probably fine, but maybe you should refresh some keys or whatever. This is happening. This is real. And everyone really needs to learn more. And if you think about like Black Swans and Wall Street and all that stuff, you know, there's been for years, a lot of talk about cyber as a major risk out there.

• 4:52Tracy Alloway?

  Yeah. All right, well, we do in fact have the perfect guests. We're going to be speaking to two people from the company, Caliph. One of the companies that actually uncovered this PHP vulnerability. The other one was a company called Wiz. We have Tai Yun. He is the CEO over at Caliph, which is a hacking firm. And we can get into exactly what that means. As well as Bruce Dang, he is an engineer at Caliph as well. So Tai and Bruce, thank you so much for coming on Odd Lots.

• 5:19Speaker 03

  Glad to be here.

• 5:20Tracy Alloway?

  So just to begin with, because, you know, hackers kind of, they always have cool achievements that they like to talk about. Why don't we just go ahead and start with who you are? And what are the coolest things you've done in your hacking career?

• 5:35Speaker 03

  Yeah, so I started my career at Microsoft like almost 20 years ago in the Microsoft Security Response Center. I used to be people that do Patch Tuesdays. You know, like on the second Tuesday of every month, Microsoft releases an update. So I worked in that team a long time ago. Probably the biggest thing I did there and that I could talk about is I helped reverse engineer the Stuxnet virus, which is one of the, the one that was related to the supposedly the Iranian nuclear program was used to sabotage the Iranian nuclear program.

• 6:07Tracy Alloway?

  This is the thing that people describe it as the world's first like known digital cyber weapon, right?

• 6:14Speaker 03

  Yeah, yeah, yeah, yeah. I'm sure there were many others before, but yeah, that's the first public one, yeah. I worked there for almost a decade. And then I left to do a startup with my friends. And then I joined Apple. I worked on iOS security. And then Tai managed to convince me to follow the Church of AI. And so here I am.

• 6:40Speaker 04

  Yeah, it took me four years to convince Bruce. So, you know, when you go to a website or you go to Amazon, even Facebook, Instagram, your computer would share information with the server, right?

• 6:54Joe Weisenthal?

  Yeah.

• 6:55Speaker 04

  And there would be, the information would travel through many, many other servers, like your ISP, your Wi-Fi routers. So you want to encrypt that information to make sure that only the server can see your data, nobody else. And there's a mechanism for that. It's called the SSL protocol. Or the later version is called like TOS, like Transport Layer Security Protocol. So I love those protocols. And back in the day, together with friends, we found a bunch of ways to break the protocols, you know, to decrypt the data. And it's pretty cool. It's actually changed the internet, how the internet works.

• 7:39Speaker 04

  Because we basically show that in the past, there are like two protocols, like SSL version 3.0, that was invented by Netscape. You know, you remember Netscape, 30 years ago. And then people still use it because it's still working somewhat. But we show that, oh, it's not working very correctly. If you use SSL 3.0, then people can decrypt your data. So we helped the internet like really, really remove like SSL 3.0. And that's one thing. The other thing that I really enjoyed doing was, you know, people think that in the past, you have compression, you have some data,

• 8:23Speaker 04

  you want to compress the data, and you have encryption. And both of them actually randomize your data in some way, right? If you look at a zip file, you open a zip file, look at the raw binaries, buy data in the zip file, it looks random to you. Because all the redundant information has been removed and encoded in a way to reduce the size of the file. And so one of the basic question in um computer security was um would you compress data and then you encrypt or you encrypt then compress?

• 8:58Joe Weisenthal?

  Ah.

• 8:59Speaker 04

  And uh you know, I took some uh crypto class at Stanford University. And I remember my professor, he asked this question in one of the homework assignments. And um the office answer back then was you don't want to compress and then uh you don't want to encrypt then compress because encryption randomized your data. It means that compression would be less effective. So the right answer is you compress and then you encrypt. And that was the correct answer on my homework assignment. I think I took that class in uh twenty eleven. And then three year later, we found that it's wrong.

• 9:39Joe Weisenthal?

  Ah.

• 9:39Speaker 04

  If you do that, then uh people can actually decrypt your data. And the way it looks is pretty cool. I can explain to you. So compression actually review, if you look at a compressed file, you know how well it is compressed, right? Like because it's softer, it is smaller, the compression is very good because you know you there's a lot of redundant information. That's why compression works well. It means that if you look at a compression alone, the size of the compression, a compressed file, you can tell whether there the file has a lot of like redundant information. And encryption hide the length. So it doesn't hide the size of the encrypted data.

• 10:20Speaker 04

  When you encrypt a message, you can still see that this message is maybe this long or this message may be this long, right? Because compression uh like encryption doesn't try to hide that.

• 10:30Joe Weisenthal?

  Yeah.

• 10:30Speaker 04

  There's some people try to do that. So it means that if you compress and then you encrypt, it means that I can see whether some your message has some redundant information, has a lot of redundant information. And that's alone is a leakage already, right? That you don't want to review. And I give you an example, like let's say that you take a message, like a random message that I gave you.

• 10:53Joe Weisenthal?

  Uh huh.

• 10:53Speaker 04

  And then you you put your password together with that message. Let's just say that there's a way like there's a reason for you to do that. You put your password together with the message I gave you and you compress together. And then you encrypt it with a key that I don't know. And you review the cyphertext, the result, encrypted message to me. So supposedly I don't have the key, I shouldn't be able to read the message, right? But because I give you a message and you get my message, put together with your password, you compress together. If the compression is very works very well, then I know whether you met my message has some redundancy with your password.

• 11:35Tracy Alloway?

  Hmm. You can reverse engineer between like the two relationships.

• 11:39Speaker 04

  Yeah, exactly.

• 11:39Tracy Alloway?

  Yeah.

• 11:40Speaker 04

  And you that do that like repeatedly, eventually we can recover your password. And uh that's exactly what we found on uh these web encryption protocol like in the past. That's exactly what they did. They take my data, they concatenate your password, they encrypt together, uh they compress together and then they send over the wire. And then as an attacker, I can see the the length and that's enough for me to decrypt. And that's the solution was really interesting because they decided to turn off like compression.

• 12:16Tracy Alloway?

  Oh.

• 12:16Speaker 04

  There's no solution. And then eventually I was at Google back then. I was born uh in Saigon, Vietnam. I grew up there. Then uh I got a job in Mountain View for a consultancy, like what we do. Uh so I moved to Mountain View in twenty eleven and then I joined Google uh later that year. And uh I did uh cryptography at Google. Uh basically help people do uh cryptography correctly, like try to avoid the mistakes that we found.

• 12:49Joe Weisenthal?

  Uh huh.

• 12:49Speaker 04

  Uh I was there for twelve years. I work on like uh very last number of products. Google has a lot of products, right? You know Gmail, Chrome browser that we are using right now. And there's a lot of people out there that want to hack Google and our products. So my job was to hack these products uh before we release them to the public. And I was there for twelve years and then I left to create uh Kalif and um yeah.

• 13:19Joe Weisenthal?

  That's fantastic. I'm already fascinated by this conversation. I want to get into obviously what Kalif does specifically. I want to get into some of the latest vulnerabilities. But before we do that, you know, both of you have had long careers that by and large predate what we now call AI. Are the risks associated with AI a sort of continuation on some path that cybersecurity have well understood? Or are we in a truly novel area for how we should we be thinking about um cybersecurity risk?

• 13:56Speaker 03

  I think it's it's a combination of the two. We've always known that there are security vulnerabilities in systems. Uh and so you know, we have security engineers who are hackers who try to find and exploit these vulnerabilities. So the system is had always been vulnerable to some degree, to you know varying degree. What AI has done is it's kind of accelerated the speed in which you identify and exploit these vulnerabilities to a level where it's almost like superhuman. You know, like twenty years ago, Microsoft would release, let's say maybe twenty updates every month.

• 14:28Joe Weisenthal?

  Mm hmm.

• 14:29Speaker 03

  Now you're looking at like, you know, fourteen hundred updates per month.

• 14:34Tracy Alloway?

  Wow.

• 14:34Speaker 03

  Yeah, you know, like and then that number is going to continue to grow. Um it's just just to give you an idea of like the the scale of things. And now, you know, what, for example, say to hack certain systems, it may take you, let's say, three months with lots of people. Now that may take you a few days with just one person and a very capable AI model. That's the reality that we're in today. It even changed the way how attackers uh like, you know, like hack certain types of systems, you know, like uh like than the banking sector.

• 15:07Tracy Alloway?

  Hmm.

• 15:07Speaker 03

  That we our customers are in, you know, you can tell some stories about that time. But that's kind of what I think it's I think it's the systems have always been vulnerable to some degree. And now it's the AI just accelerates that and uh makes it much more visible. And it's also made it easier for people to identify these vulnerabilities as well.

• 15:26Joe Weisenthal?

  Yeah.

• 15:26Speaker 03

  And so uh and then, you know, obviously there are there are the pros and cons to that. But yeah, we'll go into that later.

• 15:47Tracy Alloway?

  There are some market stories where you want every detail. Joe and I have made quite a few podcasts on that basis. But sometimes you've only got ten minutes and just want to know what's moving markets fast. That's the Barclays Brief podcast. Every week, experts from Barclays Markets and Research get you up to speed on what's happening and what to watch next. Concise, focused, and brief. Search Barclays Brief wherever you get your podcasts.

• 16:14Speaker 01

  This is the Bloomberg Tech Minute brought to you by ChatGPT. I'm Carol Muster. Getting hired at SpaceX requires exceptional ability and may include having Elon Musk review a candidate's resume. So writes Bloomberg Businessweek's Lauren Grush. She reports that the company culture is defined by Musk and job candidates must understand that a commitment to SpaceX means adhering to this culture and exhibiting loyalty to Elon Musk. To get hired, candidates must demonstrate their achievements from past jobs and hands-on experience matters more to recruiters than advanced degrees, with the company looking for people with raw innate intelligence. A spokesperson for SpaceX didn't respond to a request for comment on its recruiting and hiring practices.

• 16:57Speaker 01

  But according to recruiters, advisors, and those who've interviewed for jobs there, it's the space exploration dream that draws people to the company. And Musk invokes that dream regularly to remind workers why they're there. Prospective hires are told that the job will require stamina, including in job ads that candidates quote must be willing to work extended hours and weekends as needed. One major perk for all that hard work? Employees' access to equity, either the right to buy shares or payment in the form of restricted stock units that vest over time. That's the Bloomberg Tech Minute brought to you by ChatGPT. Get started at chatgpt.com.

• 17:37Tracy Alloway?

  Why don't we talk about discovering the PHP vulnerability then? Because I think this was a joint project between Calif, Wiz, and I think it was OpenAI. How did you find this? What was the process? And then what was the decision? I know you guys have gotten a little bit of pushback about publicizing it before it was fixed. So what was the process of actually, you know, putting out the statement saying we found this thing?

• 18:03Speaker 04

  We really interested in like finding vulnerabilities that have wide impact. And we want to understand these vulnerabilities to help like inform decisions, right? Defense decision, how to fix and how to mitigate them like for once and forever. On that background, so we joined the OpenAI's Past the Planet Program. This is where OpenAI funds, you know, companies like Calif to go out and help open source maintainers to identify and fix, mitigate vulnerabilities in their software.

• 18:42Speaker 04

  And we have this engineer like Ryan Osteen, who is, he's like a PHP historian. Yesterday, we went to a conference in San Francisco. We basically presented like, you know, PHP2 Shell. And Ryan walked everybody over like the 25 years of history of PHP vulnerabilities. So we have this like engineer, Ryan. And this is how we work, basically. We, our engineer, they're interested in certain things and then they just go and hack those things. And, you know, as business people, we try to see, okay, how can we convince some other people to pay us for this work? And that's exactly what we did with like OpenAI.

• 19:28Speaker 04

  We convinced OpenAI, okay, we're gonna hack PHP. Can you fund our work? And they said, yes, they gave us tokens and money. And then we go and convince like PHP Foundation, which is the organization behind PHP, that let's work together, you know, we can help you. And it's actually really interesting because I mentioned like there like a history of 25 years of like PHP vulnerabilities. And the person that is behind all of these hacks is like Stefan Escher. He's also at Calif. He joined us, I think, six months ago. Back in the day, he's the PHP security guy. Basically, he hacked and helped like harden PHP.

• 20:11Speaker 04

  So we didn't know anybody at the PHP Foundation. So we asked Stefan to introduce us. And because, you know, even though Stefan stopped working on PHP security for a while now, his name still rings, you know, very loudly in this circle of the world.

• 20:29Tracy Alloway?

  I saw the comic that you guys put up about this. It was kind of funny.

• 20:34Speaker 04

  Yes.

• 20:35Tracy Alloway?

  He's like Indiana Jones type character.

• 20:37Speaker 04

  Yeah. So he connected us and then we met with like Volker Dusch at the PHP Foundation. And yeah, that's how we got started. I think we started in July 30. And then immediately after one or two days, you know, Ryan found the first vulnerability. And he was interested in like finding a similar vulnerability, similar to one vulnerability that like Stefan disclosed like 22 years ago. And to his surprise, you know, there's still a bunch of them like that in the PHP, you know, software right now. And so that's how we found it.

• 21:22Speaker 04

  And then we reported it to the PHP Foundation because we know immediately that is a critical vulnerability that could affect like a large part of the internet. Then the PHP Foundation actually shared with us that they actually found this vulnerability, the same vulnerability, two years ago. But they didn't fix it. Because when they found it, they discovered that like the fix is very expensive. And there's just like maybe a few options to fix it. And none of them were actually perfect. Because, you know, they need to change a lot of like functionalities within PHP.

• 22:05Speaker 04

  And those changes may introduce new bugs, new vulnerabilities, or new reliability issue. And people would be very upset if they operate, you know, PHP and their website stopped working. So in the end, back in like 2024, the PHP Foundation decided not to fix it because there was no exploit. No one could manage to show that this is actually a real issue. And that's exactly what they asked us. They come back, they ask like, do you have an exploit? Then the next day, we shared with them the first exploit

• 22:45Speaker 04

  that showed them that, yeah, someone doesn't need to know anything, can hack your website remotely.

• 22:52Tracy Alloway?

  So just to be clear, the use of AI in all of this, it wasn't necessarily that important in finding the vulnerability. It was more important in developing an actual exploit for a known issue.

• 23:06Speaker 04

  We think like that's probably the right way to think about it. But I think even for finding the vulnerability without AI, it would take a lot of more time, right? So you, you can imagine like PHP was created like maybe 30 years ago. So it's a huge codebase.

• 23:23Joe Weisenthal?

  Yeah.

• 23:23Speaker 04

  With a lot of like feature. And as a human engineer, you have to dig into this codebase. And it would take like months, right? And along the way, people may give up. But the fact that PHP Foundation found the bug in 2024 proves that humans can actually find the bug, find the bugs, right? And the problem was the exploitation, like you said.

• 23:49Tracy Alloway?

  Yeah.

• 23:50Speaker 04

  And for exploitation, like AI plays a major role in it. It's like becomes an engineering problem where our engineers would tell AI, you know, this is how I want to design our exploit and you go and do it. And then, you know, prove to us that it works correctly.

• 24:08Joe Weisenthal?

  Yeah. Let me ask a philosophical question. Is there a reason to believe that defensive cybersecurity can stay ahead of offensive cybersecurity? Just generally, then we can get into some details. But philosophically, like, is that something that we can reasonably hope for?

• 24:27Speaker 03

  I think so, yes.

• 24:29Joe Weisenthal?

  How come?

• 24:29Speaker 03

  Because you can use the AI to build certain types of systems in ways that may be very challenging for attackers to exploit, right? Today, you can use AI to build whatever systems you want, you know, and very quickly, right? You can experiment, you know, get feedback very quickly. It can also process data like very, very quickly. And reason about that data. And so I think it is possible. I think it may not be immediate, but like, you know, over time, we're, you know, perhaps, you know, like use AI to help us write more secure software or build more secure systems, right?

• 25:13Speaker 03

  And eventually, I think that should kind of like counterbalance the advantages that the attackers have. I think that's, perhaps I'm being optimistic, but I do foresee this happening.

• 25:26Speaker 04

  I can add something there. So if you look at the history of humanity, our history is the history of like weaponized our tools, right? If you fire a powerful tool, then someone would fire away to use that tool to, as a weapon.

• 25:42Joe Weisenthal?

  Yeah.

• 25:43Speaker 04

  So, and attackers always are early adopters of tools, right? New technology. Defenders move like at much slower pace than attackers. But fundamentally, we believe there are more good guys than bad guys out there. And eventually, you know, the good guys would catch up and build things that help, you know, everybody defends, fend up the bad guys. And I I don't think like um in general like cybersecurity, if you see the news all the time, you see like we got like data breach every day almost, be even before AI. So you may feel like it's not working at all.

• 26:27Speaker 04

  But if you're in the field, you can see the progress, right? In the past like twenty five years, there's a tremendous progress in cybersecurity. Of course, people still got happy because this is it's difficult. Imagine you have a very complex system, very like imagine you have a house with a lot of doors, a lot of way to get in and cybersecurity must like make sure that everything is safe. At the same time, your house or your office must remain open for business.

• 26:55Joe Weisenthal?

  Right.

• 26:56Speaker 04

  So it's actually a pretty difficult problem. At the same time, without the progress that we like the industry met in the past twenty five years, things could be much worse, right? And I think the same thing would be happening here. It's gonna take a while for defenders to catch up. Right now, you know, AI helps attackers more than defenders.

• 27:19Tracy Alloway?

  Is the general idea that we're just in this sort of awkward phase where a lot of people in cybersecurity always refer to technical debt, right? This idea that you haven't upgraded a system for ages, like the PHP vulnerability we were just discussing, and so now you have to pay back that technical debt. The idea that we're just in an awkward moment where AI is going to be able to exploit existing flaws in the system, but maybe we eventually move to a place where we upgrade the entire system.

• 27:51Joe Weisenthal?

  We reduce our outstanding.

• 27:53Tracy Alloway?

  We reduce the outstanding technical debt, exactly.

• 27:55Speaker 04

  That's an optimistic way to look at it.

• 27:57Tracy Alloway?

  Okay.

• 27:59Speaker 04

  You know, we found that there are like system that we thought that, okay, that don't have a lot of technical debt, that turn out that they just like dumpster fire like everybody else. That was a very big surprise, right? To me personally, like we know there are places, there are bad problems, and we know that if we just point AI at that thing, there will be a lot of bugs coming out. But there are also places we thought that could be okay, because like they receive a lot of attention over the years already. Uh, but turn out that there's still a lot of bugs there as well. And a lot mean like a lot more, like ten X more than we expected.

• 28:43Speaker 04

  And of course, there are still like a few uh small places where there was fewer bugs back then before AI now, there's still fewer bugs still now, but they're like very small, like very like lit like they are the exception, not the norm. So that's actually a big surprise, uh, because I I don't think anybody was surprised to find a critical vulnerability in PHP. Because PHP wasn't known for like rate security. So of course, at the PHP to share scale, then that's a different matter. But if you find another vulnerability in PHP today, then that's not a surprise.

• 29:24Speaker 04

  Uh, but if you go and, you know, find vulnerability, or maybe a hundred vulnerabilities, a thousand vulnerabilities in the Chrome browser, for example, that's a surprise. And that's exactly what happened, like people found like a thousand vulnerabilities in Chrome. And you know, I was at Google and I I knew, and then I think the entire industry like assumed that and knew that, wow, there was a lot of investment in Chrome security. And not just like, you know, remove like eliminate vulnerabilities, but making sure that even if you have vulnerabilities, it's difficult to exploit these vulnerabilities. This is what we call mitigations.

• 30:05Speaker 04

  You you accept that you have vulnerabilities, but then you make sure that like attackers couldn't use the vulnerabilities uh to control your computer or your browser. We thought that, you know, uh, the defense layers uh were pretty good, and the the rate of vulnerabilities were low. But then um after AI, we just we just discovered that either like we, as security engineers, uh suck at our job, uh, we couldn't find this thing, or there's just like too much code that we didn't have enough time to look into.

• 30:42Joe Weisenthal?

  So this raises another question, like, is it possible to have a provably secure browser or a piece of software? You ship the piece of software and you can prove maybe in the same way that mathematicians produce things in this thing called Lean or whatever. Does cyber have an equivalent where you could say, this is provably secure, and we know that no matter how good AI gets, it will never find a vulnerability in this piece of software?

• 31:10Speaker 03

  Oh, man, this is uh the loaded question, Joe.

• 31:14Joe Weisenthal?

  I thought it was a simple question.

• 31:15Speaker 03

  Yeah, I don't know, to be honest, you know, like browsers are like, you know, its own operating system, like very, very complex operating system.

• 31:25Joe Weisenthal?

  Yeah.

• 31:26Speaker 03

  And today, doing uh, you know, like formally verified software, you know, like it doesn't work at that scale. Um, it's typically smaller, smaller software components.

• 31:37Joe Weisenthal?

  So there is such thing as formal verification when it comes to software.

• 31:42Speaker 03

  Yes.

• 31:42Joe Weisenthal?

  You could have small pieces of software in which you formally prove in the same way that it takes mathematicians seven lines to prove the two plus two equals four. There is some sort of equivalent for software where you can prove these lines of code are secure, but the pro the question is, the scale of even something like a browser is just so enormous, that's a very difficult thing to do.

• 32:07Speaker 03

  Yes.

• 32:08Joe Weisenthal?

  Okay.

• 32:09Speaker 03

  It's uh it's something that's um I think is being researched right now, because this is, I think this is a like one of the one of the paths forward to make to build more secure systems.

• 32:19Joe Weisenthal?

  Yeah.

• 32:19Speaker 03

  There are, like, for example, you know, we've hacked systems where, you know, the core of it is formally verified, right? It's an operating system that's formally verified, but then there are applications, you know, running like on these things, and those applications have issues, you know, like.

• 32:35Joe Weisenthal?

  Yeah.

• 32:35Speaker 03

  So it it it's complicated, and you know, and these are like small, like small systems, right? And you're talking about browser, browsers like, you know, many billions lines of code.

• 32:43Joe Weisenthal?

  Wow.

• 32:44Speaker 03

  And so that's um, yeah, I mean, I can tell you how big Chrome is. I I mean, they have like zillions of people working on it, and you know, any like lots of people working on Chrome security after all these years, but uh, you know, it's but long story short, it's there are such thing, but to make it work on a browser or a very, very large system, like, uh, this is it's um, we don't have anything like that today.

• 33:05Joe Weisenthal?

  Got it.

• 33:06Speaker 04

  I think there's a there's a deep reason here. You know, the reason like uh software is eating the world, you can see like, you know, the top, the biggest companies in the world are software companies, right? It's because software is easy to change. And imagine, you know, that allows like software companies to adapt and to to uh to learn much quicker than the rest of the world. You have a product, if that doesn't work, then tomorrow, tonight, you can change it. And that's actually allows the software world, you know, to become uh to dominate the world, basically. So basically, fundamentally, software is easy to change, and people want to change it constantly. And that's the reason why, you know, uh, there's the the tech companies are doing so

• 33:51Speaker 04

  well. So if you ask like, okay, now let's not change it like frequently, uh, then that goes against the interest, right?

• 34:00Joe Weisenthal?

  Yeah.

• 34:01Speaker 04

  And that's not gonna happen.

• 34:03Tracy Alloway?

  Hmm.

• 34:03Speaker 04

  So it means that even if you have a way to formalize, uh formally verify everything, that will take a lot of time, unless you have some sort of AI help you do the formal verification automatically. Otherwise, it's not gonna happen, because people want to change their software like as quick as possible, because that's how they do business.

• 34:43Speaker 01

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• 36:59Tracy Alloway?

  This is sort of a related question, but does AI start to change? I guess the way or like the waterfall of the way things get fixed. So nowadays, it's like a vulnerability is discovered. The software company issues an alert and a patch. They disclose it and then people go off and fix it. If exploits are coming faster, does that process start to change in any way?

• 37:25Speaker 04

  Yeah, it changed a lot. Basically, back in the day, we have like two kinds of vulnerabilities, like zero-day vulnerabilities that nobody knows about except the person who filed it. And then end-day vulnerabilities, the vulnerabilities have been disclosed and maybe fixed by the vendors and maybe user have upgrade or not. But now we also have something we call like minus one day vulnerabilities. So these vulnerabilities happen when, you know, imagine like, let's take the PHP vulnerability as an example. Let's say that, you know, because PHP4 version and PHP is an open source project.

• 38:08Speaker 04

  Everything happens on GitHub, right? And imagine, let's imagine that we reported a bug and PHP fixed the bug and publicly on GitHub. The moment that we found the bug and then PHP produced a patch for that bug, that very moment, that information became public. Somebody who is watching the PHP repository on GitHub.

• 38:37Joe Weisenthal?

  Yeah.

• 38:38Speaker 04

  They could like turn that away into an exploit within, you know, a few hours. Of course, like the vulnerability that we filed was more complicated than that, but you can imagine that's in principle, like the window between the patch was being developed. It's not ready yet, you know, for anybody. And before it's become ready for end user to upgrade, there's a window, right?

• 39:04Joe Weisenthal?

  Yeah.

• 39:05Speaker 04

  In the past, you know, the attacker has to wait until the patch become available. And then it would take them a long time to develop an exploit. So user can have a longer time to upgrade. Now that window is collapsing. It is collapsing everywhere, not just in PHP, right? In Windows, in macOS, in anything. Because right now, there are people who have like what we call like end-of-factory, you know, they're just waiting for patches from Microsoft, from Apple, from important critical software. Like, I'm sure tens of people are watching PHP today.

• 39:49Speaker 04

  After what happened, they're watching PHP, Python, Java, all of those important languages. And if there is any sign of like, oh, there's a new vulnerability, they're gonna like, you know, their AI would go pro and then, you know, bundling tokens to find, identify that vulnerability, produce it, be an exploit for it. So that changed the, um.

• 40:15Joe Weisenthal?

  Yeah.

• 40:16Speaker 04

  The practice, right?

• 40:17Joe Weisenthal?

  Yeah. I'm curious what you thought after the Hugging Face incident? Because after that moment, there were sort of two schools of thought that I thought there's, or that I perceived. There's one that was like AI creature, there was this sort of, I guess, maybe the anthropomorph Asian view, AI creatures, they want to escape their cages. They're devious, they're tricksters, they want to show, come up with a way to cheat on the right answers, but cheat on the way that the greater, you know, all these stories. And then there are other people that were just like, guys, build a stronger sandbox. Stop talking about all this stuff, just build a stronger sandbox. Jensen Huang is kind of in that category. I loved his interview with Ezra Klein, where he was basically like, what's your problem?

• 41:01Joe Weisenthal?

  Just make models that don't hack. He's like, just don't ship it. Fix your model, don't let them hack. And I love that because it's just like, just fix it. And the AI people are like, no, no, no, we can't, you don't understand, we haven't solved alignment, it's very tricky. And he's like, just don't, just make, just fix the model. And I'm sort of curious, as people who have come out of the traditional cyber world, but are now in the AI world, where do you land on this question? Can you just like, guys, just fix the sandbox? Or is there something deeper here?

• 41:31Speaker 04

  I don't think that is simple to fix the sandbox. That's, that's the problem. People think that, you know, maybe people not in security, 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 say, tell people, just buy this box, this magic box.

• 41:51Joe Weisenthal?

  Yeah.

• 41:51Speaker 04

  And put it in your network and you, you'll be safe. No, it's not like that. Even that box has problems.

• 41:57Joe Weisenthal?

  Yeah.

• 41:57Speaker 04

  You know, 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, the fireworks that you buy, they may have problems.

• 42:13Joe Weisenthal?

  Yeah.

• 42:13Speaker 04

  And they do. And what I mean here is, so what we found, like the Hugging Face OpenAI incident was fascinating, right? To, 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 gonna 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.

• 42:42Joe Weisenthal?

  Yeah, just fix the model, just make one that doesn't hack.

• 42:45Speaker 04

  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.

• 42:56Joe Weisenthal?

  Yeah, of course.

• 42:57Speaker 04

  And the AI companies, they're making money by selling tokens. And most of the tokens are used for coding today.

• 43:06Joe Weisenthal?

  Yeah.

• 43:06Speaker 04

  Like programming, building things, right? And if you build, if you want to be really good at coding, you need an agent, an AI that understand 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 to spend more tokens, or you don't want to get into the coding business anymore, you focus on like scientific discovery, physical AI, whatever, then maybe

• 43:48Speaker 04

  you can not, you know, you can train a model that is not good at hacking anymore. But as long as you want to automate knowledge work, you know, then eventually you must, your AI must be able to use computer and control computer, understand technical problems. And that's the definition of someone like Bruce. So it's unavoidable.

• 44:13Tracy Alloway?

  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?

• 44:30Speaker 03

  Yeah, well, just to use some, like some background, so like I wrote a textbook with some friends on reverse engineering. It used to be like, you know, like you kind of like, reverse engineering is the practice of, you know, understanding by like software without any source code or hardware systems. That used to be like, I wrote this textbook. And then I think with the advent of AI, I think what, you know, whatever, nine months ago, as of nine months ago, like that entire book is deprecated. It takes like, you know, two prompts or one prompt and then bam, it will generate the textbook for you and is even better, you know? And it took us, you know, a long time to write. Just to, that's, it gives you an idea. And then like, I talk to friends who've been doing this for decades, right? They're like specialists in this area.

• 45:14Speaker 03

  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? Whereas before it would take me, you know, like months to figure some, some, some stuff out. You know, that's just, uh, just to give you like, you know, a glimpse into, uh, you know, what's happening, like how quickly things change. Well, friend, you know, like this, this guy, Matt Swish, he's, you know?

• 45:44Joe Weisenthal?

  Yeah.

• 45:45Speaker 03

  And he just do.

• 45:46Tracy Alloway?

  He's a friend of the show.

• 45:47Joe Weisenthal?

  A long, a long time friend of the show, multi-time guest. Yeah.

• 45:51Tracy Alloway?

  We used to hang out in Abu Dhabi a lot.

• 45:53Speaker 03

  Oh, okay. Yeah. It's, you know, like I'm no Matt Fall, I mean, like now he's like, he shows, he gave a talk with our team the other day and he showed his rack, you know, like in, like, um, and it is in his apartment and he's sitting there, you know, like hacking stuff like while he's sitting there talking. It's just insane. I, something that, uh, we have people that, let's say, you know, for example, like we've been hacking the iPhone, okay? To build a full chain on the iPhone, it's not an easy task. It's sometimes it takes several people to do this, right? There's, um, and our team was able to do this within like a few days.

• 46:32Tracy Alloway?

  Wow.

• 46:33Speaker 03

  You know, as a one person. And we have multiple of these chains. It really comprises the, the tie, like the, the, the exploitation, the time to, to build exploits. We see customers getting hacked by AI, you know, in the financials, in the banks, basically. You know, defenders cannot, you know, tie, actually tie you, why don't you tell these, like these stories? So, you know, it just literally, this happened the last few weeks, you know?

• 47:00Tracy Alloway?

  Yeah.

• 47:01Speaker 03

  Like how things changed.

• 47:03Speaker 04

  Yeah, basically we saw like, you know, in the OpenAI and Hugging Face incident, there were one detail that, that is very interesting. I'm not sure if people noticed, but OpenAI note that like the people who handled incident 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. Like a hundred points within your networks that were compromised at the same time.

• 47:33Joe Weisenthal?

  Yeah.

• 47:34Speaker 04

  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 AI 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 took like they came in, they they broke the net, they broke inside the network on Monday.

• 48:17Speaker 04

  By Tuesday, they're everywhere, everywhere. And like it's like cancer, it's spread like at a machine speed. And it was like mind blowing, right? Because how could you defend against that? Like in in the past, we we were telling our clients, you know, you have to invest in detection. Well, what would, how can you help yourself? If you you see it, you can detect it, but there's a hundred of them.

• 48:41Tracy Alloway?

  Noted, we have a hundred hackers in our system right now. It's not really helpful.

• 48:45Speaker 04

  Exactly. How could you do it, right? And then you have to shut down everything, but shut down is not an option because you are a bank. So that's actually requires to sit down and think about how to redesign like defense system, right? What we have right now is not working very well. But like to come back to your question, like as a hacker, you know, how does it feel? I love history, so I always come back to history to say like, does it, did it happen before? It's actually did happen, um, you know, with like chess, for example. You remember like in nineteen ninety seven, you know, IBM Deep Blue defeated Gary Kasparov. Uh, that was a big moment, right?

• 49:26Speaker 04

  And then twenty years later, AlphaGo defeated like Lee Zhi Dou in the game of Go. But those two moments are actually quite different. Like the first moment, the Deep Blue moment, after Deep Blue, the best chess player wasn't a computer. Because Deep Blue was a mainframe, right? Not something that you can run on your computer. And it took ten years for someone to to go from Deep Blue to develop a computer software that you can run on your computer that defeated everybody. Uh, but the ten years, it took ten years. During that ten years, the best chess player was a centaur player. This is a term coined by Gary Kasparov.

• 50:09Speaker 04

  It's a combination of computer and human. It took ten years. For AlphaGo, it took like three years. Like after AlphaGo, then nineteen, twenty nineteen, somebody come up with a computer software that defeated anybody without any human input at all. At CalIF, we think like, you know, we are enter the era of the centaur hackers. Basically, the best hacker right now is a combination of AI and humans. And, you know, our work and our friends' work as well show that AI is powerful. It can hack anything, uh, but it still require, you know, a human expert to drive it, right? And we don't know how long this is gonna last.

• 50:53Speaker 04

  Uh, maybe three months, maybe, you know, we we come back here in like by the end of the year, we tell you we retire now. There's nothing else for us to do. Maybe it's last like three years. And this is actually pretty exciting to find out. That's exactly what we want to do. And we think like, that's like best image, best image of view, right? And AI is gonna do everything, like just like retire and hate AI. Or you can see AI as a tool. It's like, like humanity just discover fire.

• 51:27Joe Weisenthal?

  Yeah.

• 51:27Speaker 04

  And without fire, we wouldn't be here today. So of course we have to think about how to control fire. At the same time, a very important question that we need to ask is, what should we cook, right? That's very important and we want to find out. What can we cook with AI? And how can we do it in a safe way that help, you know, everybody?

• 51:49Tracy Alloway?

  Protein that makes our brains get bigger.

• 51:51Joe Weisenthal?

  Yeah.

• 51:52Tracy Alloway?

  All right, well, Ty and Bruce from CalIF, thank you so much.

• 51:55Joe Weisenthal?

  That was so good. That was a lot of fun. You're both excellent. Thank you both.

• 52:00Tracy Alloway?

  Thanks.

• 52:01Speaker 04

  Thanks, Joe. Thanks, Tracy. Thank you. Bye bye.

• 52:15Tracy Alloway?

  Joe, I thought that was a fantastic conversation. Not exactly uplifting. I was surprised at Ty's response. I thought maybe, maybe people would say we're in this weird, like awkward moment where a lot of like legacy issues are being discovered. But once AI actually gets deployed and starts redesigning some of the architecture, it'll be a lot more resilient. Apparently that's not the case. That's a little bit worrying.

• 52:40Joe Weisenthal?

  I agree. There was so much in there that was interesting and like I could, you know, all the stuff about how, yes, you could have provably secure software, but it's small. You can't even do it for something that has the browser. I love that last point about how we're in the centaur age.

• 52:55Tracy Alloway?

  Yeah.

• 52:56Joe Weisenthal?

  Where the strongest hacker is the computer working with a human, but that may not be there for much longer.

• 53:01Tracy Alloway?

  That's gonna be.

• 53:02Joe Weisenthal?

  Three months a year, we have no idea, but the presumption should be that it won't last very long, et cetera.

• 53:08Tracy Alloway?

  Also, the idea of like a computer, an agent that can code is inherently a hacker. And so you can't just tell it.

• 53:18Joe Weisenthal?

  Just tell it to be not.

• 53:18Tracy Alloway?

  Not to hack, basically.

• 53:20Joe Weisenthal?

  Teach it not to hack. What's wrong with you? Just teach it not to hack. If you if compute, if coding is gonna be big business, which it is, you're gonna be building a lot of good hackers.

• 53:27Tracy Alloway?

  Yeah, and so the hackers proliferate. On that note, shall we leave it there?

• 53:31Joe Weisenthal?

  Let's leave it there.

• 53:31Tracy Alloway?

  This has been another episode of the Odd Lots Podcast. I'm Tracy Alloway. You can follow me at Tracy Alloway.

• 53:37Joe Weisenthal?

  And I'm Joe Weisenthal. You can follow me at the Stalwart. Follow our producers, Carmen Rodriguez at Carmen Armand, Dashal Bennett at Dashpot, Kale Brooks at Kale Brooks, and Kevin Lozano at Kevin Lloyd Lozano. And of course, you can chat about all of these topics 24/7 in our Discord, discord.gg/oddlots. And for more Odd Lots content, you can check out our daily newsletter, which you can find at Bloomberg.com/oddlots.

• 54:01Tracy Alloway?

  And if you enjoyed this conversation, if you like it when we talk about hacking, then please leave us a positive review on your favorite podcast platform. And if you're watching on video, then please leave a comment or like, or better yet, subscribe.

• 54:13Joe Weisenthal?

  And remember, if you're a Bloomberg subscriber, you can listen to all of our episodes absolutely ad free. All you need to do is find the Bloomberg channel on Apple Podcasts and follow the instructions there.

• 54:23Tracy Alloway?

  Thanks for joining.

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