Anthropic says its most powerful AI cyber model is too dangerous to release publicly — so it built Project Glasswing

Anthropic on Tuesday announced Project Glasswing, a sweeping cybersecurity initiative that pairs an unreleased frontier AI model — Claude Mythos Preview — with a coalition of twelve major technology and finance companies in an effort to find and patch software vulnerabilities across the world's most critical infrastructure before adversaries can exploit them.

The launch partners include Amazon Web Services, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, Nvidia, and Palo Alto Networks. Anthropic says it has also extended access to more than 40 additional organizations that build or maintain critical software, and is committing up to $100 million in usage credits for Claude Mythos Preview across the effort, along with $4 million in direct donations to open-source security organizations.

The announcement arrives at a moment of extraordinary momentum — and extraordinary scrutiny — for the San Francisco-based AI startup. Anthropic disclosed on Sunday that its annualized revenue run rate has surpassed $30 billion, up from approximately $9 billion at the end of 2025, and the number of business customers each spending over $1 million annually now exceeds 1,000, doubling in less than two months. The company simultaneously announced a multi-gigawatt compute deal with Google and Broadcom. On the same day, Bloomberg reported that Anthropic had poached a senior Microsoft executive, Eric Boyd, to lead its infrastructure expansion.

But Glasswing is something categorically different from a revenue milestone or a compute deal. It’s Anthropic's most ambitious attempt to translate frontier AI capabilities — capabilities the company itself describes as dangerous — into a defensive advantage before those same capabilities proliferate to hostile actors.

Why Anthropic built a model it considers too dangerous to release publicly

At the center of Project Glasswing sits Claude Mythos Preview, a general-purpose frontier model that Anthropic says has already identified thousands of high-severity zero-day vulnerabilities — meaning flaws previously unknown to software developers — in every major operating system and every major web browser, along with a range of other critical software.

The company is not making the model generally available.

"We do not plan to make Claude Mythos Preview generally available due to its cybersecurity capabilities," Newton Cheng, Frontier Red Team Cyber Lead at Anthropic, told VentureBeat in an exclusive interview. "However, 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."

That language — "the fallout could be severe" — is striking coming from the company that built the model. Anthropic is effectively arguing that the tool it created is powerful enough to reshape the cybersecurity landscape, and that the only responsible thing to do is to keep it restricted while giving defenders a head start.

The technical results reinforce that claim. According to Anthropic's press release, Mythos Preview was able to find nearly all of the vulnerabilities it surfaced, and develop many related exploits, entirely autonomously, without any human steering. Three examples stand out: The model found a 27-year-old vulnerability in OpenBSD — widely regarded as one of the most security-hardened operating systems in the world and commonly used to run firewalls and critical infrastructure. The flaw allowed an attacker to remotely crash any machine running the OS simply by connecting to it. It also discovered a 16-year-old vulnerability in FFmpeg — the near-ubiquitous video encoding and decoding library — in a line of code that automated testing tools had exercised five million times without ever catching the problem. And perhaps most alarmingly, Mythos Preview autonomously found and chained together several vulnerabilities in the Linux kernel to escalate from ordinary user access to complete control of the machine.

All three vulnerabilities have been reported to the relevant maintainers and have since been patched. For many other vulnerabilities still in the remediation pipeline, Anthropic says it is publishing cryptographic hashes of the details today, with plans to reveal specifics after fixes are in place.

On the CyberGym evaluation benchmark, Mythos Preview scored 83.1%, compared to 66.6% for Claude Opus 4.6, Anthropic's next-best model. The gap is even wider on coding benchmarks: Mythos Preview achieves 93.9% on SWE-bench Verified versus 80.8% for Opus 4.6, and 77.8% on SWE-bench Pro versus 53.4%.

How Anthropic plans to disclose thousands of zero-days without overwhelming open-source maintainers

Finding thousands of zero-days at once sounds impressive. Actually handling the output responsibly is a logistical nightmare — and one of the sharpest criticisms that security researchers have raised about AI-driven vulnerability discovery. Flooding open-source maintainers, many of whom are unpaid volunteers, with an avalanche of critical bug reports could easily do more harm than good.

Cheng told VentureBeat that Anthropic has built a triage pipeline specifically to manage this problem. "We triage every bug that we find and then send the highest severity bugs to professional human triagers we have contracted to assist in our disclosure process by manually validating every bug report before we send it out to ensure that we send only high-quality reports to maintainers," he said.

That pipeline is designed to prevent exactly the scenario that maintainers fear most: an automated firehose of unverified reports. "We do not submit large volumes of findings to a single project without first reaching out in an effort to agree on a pace the maintainer can sustain," Cheng added.

When Anthropic has access to the source code, the company aims to include a candidate patch with every report, labeled by provenance — meaning the maintainer knows the patch was written or reviewed by a model — and offers to collaborate on a production-quality fix. "Models can write patches," Cheng noted, "but there are many factors that impact patch quality, and we strongly recommend that autonomously-written patches are put under the same scrutiny and testing that human-written patches are."

On disclosure timelines, Anthropic says it follows a coordinated vulnerability disclosure framework. Once a patch is available, the company will generally wait 45 days before publishing full technical details, giving downstream users time to deploy the fix before exploitation information becomes public. Cheng said the company may shorten that buffer "if the details are already publicly known through other channels, or if earlier publication would materially help defenders identify and mitigate ongoing attacks," or extend it "when patch deployment is unusually complex or the affected footprint is unusually broad."

Those are reasonable principles, but they will be tested at a scale that no vulnerability disclosure program has ever attempted. The sheer volume of findings — thousands of zero-days across every major platform — means that even a well-designed triage process will face bottlenecks. And the 45-day disclosure window assumes that maintainers can actually produce, test, and ship a patch in that time, which is far from guaranteed for complex kernel-level bugs or deeply embedded cryptographic flaws.

The source code leak, the CMS blunder, and why trust is Anthropic's biggest vulnerability

The irony of a company claiming to build the most capable cyber model ever constructed while simultaneously suffering a string of embarrassing security lapses has not been lost on observers.

In late March, a draft blog post about Mythos was left in an unsecured and publicly searchable data store — a CMS misconfiguration that exposed roughly 3,000 internal assets, inc