Your Undivided Attention
Anthropic’s Mythos Has Changed Cybersecurity Forever. What Now?
14 May 2026
Chapter 1: How has the evolution of technology changed our critical infrastructure?
Hey everyone, it's Tristan Harris, and welcome to your Undivided Attention. Now, a generation ago, your bank had a fault. Your medical records were in a filing cabinet, our car was a physical machine, and an electric grid just ran on dials and switches that someone physically turned on or off. And today, all of those things are digital. The vault is a database. Our filing cabinet is a server.
Your car, your Tesla, is a robot on wheels. And in a world where all these systems are mostly secure, life just gets more convenient and efficient because of all this. But all that comes into question when suddenly an AI system can break through the security that runs the world. Now, recently, you probably heard Anthropic announced their most powerful AI model yet, Claude Mythos.
You've probably read the headlines. Claude was looking for flaws and vulnerabilities in the software that runs the world. And within just a few weeks and a few hours, it found thousands of them. It found vulnerabilities in every major operating system and web browser. These are systems that human security researchers had thought were secure for years.
Now, Mythos was so dangerous that Anthropix shared it with a select group of companies responsible for cyber defense so that they could use it to find and patch the vulnerabilities before anyone else got access. That plan, though, is already showing cracks.
A couple of weeks after the announcement, Bloomberg reported that a group of unauthorized users had gotten into Mythos through one of Anthropix's vendors. And OpenAI announced that they now have a model that's nearly as capable, with Chinese open source models just a few months behind.
I actually have been talking to some people who run security at some of the companies that got access to Mythos, companies whose job is to keep us safe from cyber attacks. And they've told me, you know, this model is a big deal and we should be concerned about it.
So how do we live in a world where a private company suddenly has a skeleton key that can unlock the entire digital world with no government oversight or accountability? And what does Mythos mean for all of us who rely on digital security to go about our lives? To answer these questions, we've invited two people who spend their careers thinking about AI and cybersecurity.
Josephine Wolff is a professor of cybersecurity policy at Tufts University, where she focuses on the economic impact of cyberattacks. And Fred Heiding is a research fellow at the Defense Emerging Technology and Strategy Program at Harvard's Kennedy School of Government. Josephine and Fred, welcome to your invited attention.
Thanks so much for having us.
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Chapter 2: What vulnerabilities did Claude Mythos expose in cybersecurity?
And that's actually massive. That type of collaboration can be a complete game changer. So there's technical things, there's collaborative things, and both of them are really big.
There are some people who criticize that cloud mythos is just hype. Anthropic is trying to hype their capabilities and their model that this is, oh, this is so dangerous. We can't even release it to the public. This is just marketing. And so they can raise more investor dollars. Oh, the thing we're building is so powerful. How do we assess how powerful this is?
The first fundamental way to verify this is just to look at the vulnerabilities that we find, right? And there's a lot of really bad vulnerabilities that could cause a lot of damage that Anthropic managed to find using these AI automated tools. So I think we can definitely say that this is bad. And yeah, of course, a lot of people are developing AI models.
Other AI models can also do these things. I think that matters less. We should feel as defenders that this is really bad. We may have a few months advantage in terms of time as defenders from the Frontier Labs, but very soon, you know, Chinese unregulated open weight models, which is just models that everyone can download and use, they will be able to do these same things.
So we should use this time to really do everything we can as defenders, but we shouldn't feel safe because, yeah, Anthropic has done a great job with their model.
but other companies will very soon be able to do this if not now i want to kind of contextualize what i think mythos really represents like you hit return in your keyboard and you literally the command is as simple as find a vulnerability in the system that's it you just put in plain english you hit return and you come back 30 minutes or an hour later and it's found it
You know, the NSA used to have a statement called Nobus or nobody but us, the false idea that, hey, no one else has the capabilities that we have. But suddenly the kind of scarcity around zero day vulnerabilities that we used to have has turned into kind of an abundance. And we talk about AI abundance and how it's going to create all this access to things for cheaply.
But suddenly zero days are now abundant in a way that we also created. And I just want to like help further kind of just settle into this picture of what is the world that we're now living in when we hear all that. Josephine?
So I think that when we sort of think about the risks that Mythos presents, to me, it's less of a, oh my gosh, whichever, you know, powerful country with significant cyber capabilities gets this first is going to be a real risk because they're already a real risk. And they're already the people with the time and the resources and the expertise to find these zero-day vulnerabilities.
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Chapter 3: How does Claude Mythos challenge traditional cybersecurity measures?
companies. So what happens if I'm in the Philippines and I'm running old infrastructure? I'm defenseless now. What happens if I'm in Africa and I'm in Nigeria? I'm defenseless now. What happens if in Germany?
And as you said, Fred, there's kind of a time question of maybe this time around we have three months to patch the systems, but every time further, what if that collapses down to two months, to one month, to one day? Do you want to speak to how you see the cat and mouse game happening in terms of the time horizon?
Yeah, I think that's a really good point. And the time horizon is changing a lot. So first to address some of the other things you mentioned, it gets way easier for small state actors or actors that aren't the big ones, right? Like US and China, it gets way easier for them to launch really devastating cyber attacks, at least for a while, right?
Because these AI models can just find vulnerabilities that we haven't found ourselves. And we see that exactly as you said with Iran. And it's so cheap to do it now, right? So I think we will see way more of that. There's a few other interesting remarks I think is worthwhile making. One is that the landscape is changing.
As we talk now, mufos and these AI tools makes it way easier for defenders to test our systems. And that's great. But this is very, very short-sighted in a way because, of course, AI tools are also being used to rewrite technical infrastructure. So our infrastructure will not look What it looks like today, it will not look like in one year.
And that's very problematic, potentially good, because AI can write really secure code. But very soon, we will be in a world where AI is writing all the code. We have no idea what's going on. They may even write their own program languages. And AI funds all the vulnerabilities in that. But that basically takes the humans completely out of the loop.
And that amount of just opaqueness, we will not understand what's going on. And then that's a really big problem.
I think Fred's absolutely right to say we're going to see more and more AI-generated code, that we aren't going to have as much intuition for how it works or where the vulnerabilities may be. But I think that's also in some ways a familiar problem. When you think about code maintenance, use an enormous amount of software that humans today don't really understand.
Not because it was written by AI, but because if you go to any big tech company that's been around for a decade or longer, there's some usually huge body of code that has been in their products for as long as anyone can remember.
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Chapter 4: What are the implications of a private company controlling AI security tools?
And nobody knows exactly how it works, but they know that if you change anything, everything breaks. So I would say already we have a little bit of this dynamic where there are languages that people used to code in that most people don't know anymore, where there's legacy code that we're sort of stuck with, but we don't fully understand or know how to debug.
And the question is going to be, what do we view as being the crucial sort of human touch elements here? Or do we view there as being any, right? Are there going to be people signing off on this? If so, what does that entail? What kinds of tests are they going to be running? How good, how effective are those tests?
I think a lot of uncertainty there around how well we can assess any of these things using the AI tools themselves. So I agree that it's worth thinking about and worth preparing for. I also think that to some extent, this is a challenge we're already facing. And I think there will definitely be new challenges and new potential adversaries, right?
If the AI tools themselves are working at odds with the people who design them or the people who are deploying them, I'm less pessimistic about the idea that this will be so much worse than the world that we live in today. I think it's certainly a possibility, but I think it could also help sort of
fix a lot of the challenges we've had around what happens when you're not one of the biggest tech companies in the whole world, right? If you're an open source developer and you're trying to secure your code, then having access to the same kinds of tools that the biggest tech companies are using could be a real game changer.
So I guess I'm confused a little bit about why we shouldn't be more concerned because Anthropic only chose those first, whatever it was, 12 to 20 companies to partner with. And then the rest of the world is sort of just screwed where they're just vulnerable.
So is the world that you're talking about dependent on Anthropic turning around and making sure that they're just going to GitHub and basically automatically patching everything across all of GitHub, you know, in some automated way? Like what is the world that you're envisioning that enables the lower risk?
Yeah, I think for it to be an equalizer, you have to have pretty widely accessible tools. I agree with Fred that I think those are coming, whether we want them or not. But I also, I would say, and again, I don't mean to be too Pollyanna-ish about this, 20 tech companies could be a lot of code all over the world, right? It's not, you know, if you go to Microsoft,
You are not just talking about patching machines in the United States. You are not just talking about a small piece of the world whose software you're trying to protect. There is a small number of tech companies that control a lot of the most widely deployed code in the whole world. So I don't know if that's the right number. I don't know if this is the right set. But I would not...
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Chapter 5: How can AI models automate the process of cybersecurity?
Everyone else, every single other citizen is completely helpless. I don't like that. I don't like that at all. That doesn't feel good to me. And to a large degree, we have had a world where we didn't fully understand our code. That is one of the biggest security problems of our time. However, we did write it, right? There was always someone who could understand it.
If all the critical infrastructure, all the power goes down in Massachusetts, for example, someone could figure out how that works. Well, let's see in a future world, all the electricity in Massachusetts goes down and no one has any idea what's happening in the code. And we don't know how to recover from it. Yeah, I think that's really bad.
I mean, we saw what happened during COVID with just crisis everywhere and it could be so much worse and no one has any idea of how to fix it. I think that's problematic.
Yeah, I mean, I lean on the side of this is much worse. And so there's this interesting thing. I mean, I'm happy to go back and forth with you, Josephine, on this. I just, how do we differentiate between, you know, there's nothing new here. State-level actors had this capability, but now we have just like thousands and thousands more actors who can do this stuff.
And then the point that you're also raising, Fred, is like, how comfortable should we feel that just one company has this capability? So, yeah, how should we think about that, Josephine?
I think one of the open questions that I don't know the answer to is, is there some point at which the AI vulnerability finding systems level out, right? So far we've seen, you know, continuous improvement and the things that the models developed this year can do are much more impressive than the things that the models developed last year can do.
If that continues to be the case for the next 10 years, then you're right. Whoever has the newest, fanciest model has a really significant advantage. I don't know if that is the case or if we're going to sort of hit a little bit of a plateau where everybody has models that can find roughly the same set of vulnerabilities and patch and exploit them to roughly the same degree.
My general instinct has been more the latter. There is, you know, going to be a very significant improvement in how well we can find vulnerabilities with AI until there isn't, until we, you know, have developed systems that can find most of them. And then we're going to see more of a leveling off.
In terms of the sort of what do we do when the AI writes all the code and none of us can possibly understand it, I want to emphasize that's a choice, right? It doesn't mean it won't happen. But if we decide we're going to replace all of the software powering the Massachusetts electric grid with software written in a language that no human has ever used and has ever tried to code or patch,
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Chapter 6: What risks do AI hacking capabilities pose to global security?
I genuinely don't know. What I have seen so far since the announcement of Mythos has been fairly well contained, which suggests to me, by the way, that the way Anthropic has done this is not necessarily terrible. That choosing a couple large tech companies and working with them to patch some of the most widely deployed software might be a sensible first step.
It's obviously not where they're going to leave it, right? But nothing that I have seen in the wild so far has made me feel like, oh, this is a worse threat. These are bigger and scarier losses than any I've seen before.
Fred, do you agree, disagree with that? Yeah, I think all these are really good points. I think it's really good with optimism. I'm really pessimistic, and that's why we make for a good conversation partner. And I always, yeah, I think you're always sort of spot on in everything you say, Josefin. Some things I think about a lot is that, you know,
So let's say AI makes people develop code quicker. That's true. We see it all around right now. Does AI make you develop secure code? Well, it depends. If you ask it to, it will. But almost no one asks it to for two reasons, right? People don't think about this because they just say,
create code that can solve task X. Usually people don't think about explicitly telling the AI to make the code secure. It's also more expensive, right? So this is a game of resources as cybersecurity always have been because it costs tokens and everything will just become a token economy in the end. That's how the AI will work. And will we...
create a regulation that says you have to spend 20 of your tokens on security i don't think we will but that would be great so you just rush forward and let's take this power plants in massachusetts again right a lot of critical infrastructures owned decentralized by by private partners if they know that they can use this ai generated super fast code that just is incredibly much cheaper easier to keep up to date easier to
to work with, et cetera, et cetera. It's not as secure as it should be, but it saves a lot of cost. Oftentimes they'll have to do it. They just can't afford not using it right now. I'm just not confident we'll break long enough and we will have time to implement all the regulations to stop this. So it could work out and that would be really good if it does.
I just see so many scenarios where, again, we have this arms race dynamic, everyone is rushing, there's a lot of cost savings to be done, and security usually doesn't fit into that cost equation until it's too late, basically. So I'm skeptical. I guess the only thing... Yeah, the other thing I want to say is that we could find all the vulnerabilities today with AI.
I'm certain we could, and that's great. The problem is that the tech is moving. The tech infrastructure we have today will not be the one we use in one year. It's always changing. And that's a problem, right? So we're not going to find all the vulnerabilities that we use because these will be outdated and then new ones will be created.
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