Oh my, that was a close call! Thankfully, Anthropic launched Project Glasswing:

Today we’re announcing Project Glasswing, a new initiative that brings together Amazon Web Services, Anthropic, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks in an effort to secure the world’s most critical software.

We formed Project Glasswing because of capabilities we’ve observed in a new frontier model trained by Anthropic that we believe could reshape cybersecurity. Claude Mythos Preview is a general-purpose, unreleased frontier model that reveals a stark fact: AI models have reached a level of coding capability where they can surpass all but the most skilled humans at finding and exploiting software vulnerabilities.

Mythos Preview has already found thousands of high-severity vulnerabilities, including some in every major operating system and web browser. Given the rate of AI progress, it will not be long before such capabilities proliferate, potentially beyond actors who are committed to deploying them safely. The fallout—for economies, public safety, and national security—could be severe. Project Glasswing is an urgent attempt to put these capabilities to work for defensive purposes.

As part of Project Glasswing, the launch partners listed above will use Mythos Preview as part of their defensive security work; Anthropic will share what we learn, so the whole industry can benefit. We have also extended access to a group of over 40 additional organizations that build or maintain critical software infrastructure so they can use the model to scan and secure both first-party and open-source systems. Anthropic is committing up to $100M in usage credits for Mythos Preview across these efforts, as well as $4M in direct donations to open-source security organizations.

Project Glasswing is a starting point. No one organization can solve these cybersecurity problems alone: frontier AI developers, other software companies, security researchers, open-source maintainers, and governments across the world all have essential roles to play. The work of defending the world’s cyber infrastructure might take years; frontier AI capabilities are likely to advance substantially over just the next few months. For cyber defenders to come out ahead, we need to act now.

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We have already seen the serious consequences of cyberattacks for important corporate networks, healthcare systems, energy infrastructure, transport hubs, and the information security of government agencies across the world. On the global stage, state-sponsored attacks from actors like China, Iran, North Korea, and Russia have threatened to compromise the infrastructure that underpins both civilian life and military readiness. Even smaller-scale attacks, such as those where individual hospitals or schools are targeted, can still inflict substantial economic damage, expose sensitive data, and even put lives at risk. The current global financial costs of cybercrime are challenging to estimate, but might be around $500B every year.

Many flaws in software go unnoticed for years because finding and exploiting them has required expertise held by only a few skilled security experts. With the latest frontier AI models, the cost, effort, and level of expertise required to find and exploit software vulnerabilities have all dropped dramatically. Over the past year, AI models have become increasingly effective at reading and reasoning about code—in particular, they show a striking ability to spot vulnerabilities and work out ways to exploit them. Claude Mythos Preview demonstrates a leap in these cyber skills—the vulnerabilities it has spotted have in some cases survived decades of human review and millions of automated security tests, and the exploits it develops are increasingly sophisticated.

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Although the risks from AI-augmented cyberattacks are serious, there is reason for optimism: the same capabilities that make AI models dangerous in the wrong hands make them invaluable for finding and fixing flaws in important software—and for producing new software with far fewer security bugs. Project Glasswing is an important step toward giving defenders a durable advantage in the coming AI-driven era of cybersecurity.

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Over the past few weeks, we have used Claude Mythos Preview to identify thousands of zero-day vulnerabilities (that is, flaws that were previously unknown to the software’s developers), many of them critical, in every major operating system and every major web browser, along with a range of other important pieces of software.

In a post on our Frontier Red Team blog, we provide technical details for a subset of these vulnerabilities that have already been patched and, in some cases, the ways that Mythos Preview found to exploit them. It was able to identify nearly all of these vulnerabilities—and develop many related exploits—entirely autonomously, without any human steering. The following are three examples:

  • Mythos Preview found a 27-year-old vulnerability in OpenBSD—which has a reputation as one of the most security-hardened operating systems in the world and is used to run firewalls and other critical infrastructure. The vulnerability allowed an attacker to remotely crash any machine running the operating system just by connecting to it;
  • It also discovered a 16-year-old vulnerability in FFmpeg—which is used by innumerable pieces of software to encode and decode video—in a line of code that automated testing tools had hit five million times without ever catching the problem;
  • The model autonomously found and chained together several vulnerabilities in the Linux kernel—the software that runs most of the world’s servers—to allow an attacker to escalate from ordinary user access to complete control of the machine.

We have reported the above vulnerabilities to the maintainers of the relevant software, and they have all now been patched. For many other vulnerabilities, we are providing a cryptographic hash of the details today (see the Red Team blog), and we will reveal the specifics after a fix is in place.

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In addition to our own work, many of our partners have already been using Claude Mythos Preview for several weeks.

The NYT is slightly hysterical: Anthropic Claims Its New A.I. Model, Mythos, Is a Cybersecurity ‘Reckoning’:

Anthropic, the artificial intelligence company that recently fought the Pentagon over the use of its technology, has built a new A.I. model that it claims is too powerful to be released to the public.

Instead, Anthropic said on Tuesday, it will make the new model — known as Claude Mythos Preview — available to a consortium of more than 40 technology companies, including Apple, Amazon and Microsoft, which will use the model to find and patch security vulnerabilities in critical software programs.

Anthropic said it had no plans to release its new technology more widely, but was announcing the new model’s capabilities in one area in particular — identifying security vulnerabilities in software — in an effort to sound the alarm over what the company believes will be a new, scarier era of A.I. threats.

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The company’s decision to hold back Claude Mythos Preview, while giving access only to partners out of concern for how it might be misused, has some precedent. In 2019, OpenAI announced it had built a new model, GPT-2, but was not releasing the full version right away. The company claimed that its text-generation capabilities could be used to automate the mass-production of propaganda or misinformation. (It later released the model, after conducting additional safety testing on it.) Many of the leaders of the GPT-2 project later left OpenAI to start Anthropic.

This time, Anthropic is making a different, more urgent claim. The company’s executives say Claude Mythos Preview is already capable of carrying out autonomous security research, including scanning for and exploiting so-called zero-day vulnerabilities in critical software programs, flaws that are unknown even to the software’s developer. These efforts can often be triggered by amateurs with simple prompts. The company claims that the new model has already identified “thousands” of bugs and vulnerabilities in popular software programs, including every major operating system and browser.

One of the vulnerabilities Claude found, the company said, was a 27-year-old bug in OpenBSD, an open-source operating system that was designed to be difficult to hack. Many internet routers and secure firewalls incorporate OpenBSD’s technology. Another was a longstanding issue in a piece of popular video software that automated testing tools had scanned five million times, without finding any problems.

“This model is good at finding vulnerabilities that would be well understood and findable by security researchers,” Mr. Graham said. “At the same time, it has found vulnerabilities, and in some cases crafted exploits, sophisticated enough that they were both missed by literally decades of security researchers, as well as all the automated tools designed to find them.”

Anthropic announced on Monday that its projected annual revenue had more than tripled in 2026, to more than $30 billion from $9 billion. The growth has come largely because of the popularity of Anthropic’s Claude as a tool for programming.

Anthropic has focused on making Claude good at completing lengthy coding tasks, in hopes of making it more useful to professional programmers and amateur “vibecoders.” But an A.I. system designed to be good at coding is also good at spotting the flaws in code — running automated scans for bugs and vulnerabilities that can allow hackers to take control of users’ machines, expose sensitive user information or wreak other havoc.

The cybersecurity industry has been bracing for years for what more capable A.I. models could do to critical tech infrastructure. Until recently, only expert human researchers with access to specialized tools were capable of finding the most severe security vulnerabilities. Now, the fear is that a powerful A.I. model could discover them on its own.

“Imagine a horde of agents methodically cataloging every weakness in your technology infrastructure, constantly,” Nikesh Arora, the chief executive of Palo Alto Networks, wrote in a blog post last week.

Mr. Graham said one of the unanswered questions about Claude Mythos Preview, and other future models that will be capable of doing similar things, was whether most or all of the world’s critical software would need to be patched or rewritten as a result of these new models.

“There are a lot of really critical systems around the world, whether it’s physical infrastructure or things that protect your personal data, that are running on old versions of code,” Mr. Graham said. “If these previously were mostly secure because it took a lot of human effort to attack them, does that paradigm of security even work anymore?”

It is wise to take claims about unreleased model capabilities from A.I. companies with a grain of salt. In this case, though, cybersecurity researchers who have been given access to Claude Mythos Preview have characterized the model as a significant cybersecurity risk.

Indeed, it’s not difficult to make $30 billion once you literally steal subscribers’ money because your shitty Claude Code is so buggy that one can say, “Hi, please continue!” and get almost all their credits consumed!

So, in the end, the Apocalypse is going to be Made in the USA, not Made in China. We’re living on borrowed time.