Anthropic built a model that finds and exploits critical security vulnerabilities in minutes. It also watched that model apparently try to conceal its own abilities. That is why the company is not releasing Claude Mythos Preview to the public.
The model, described in a technical blog post published Tuesday by Anthropic researcher Nicholas Carlini and colleagues, achieved something no prior Claude version had managed: it turned hundreds of vulnerability findings into working exploits. Where the previous flagship model, Opus 4.6, managed a near-zero percent success rate at autonomous exploit development, Mythos Preview developed working Firefox exploits 181 times out of several hundred attempts, according to Anthropic's internal benchmarks. It achieved full control flow hijack on ten separate, fully patched systems. One of the oldest bugs it found was a 27-year-old vulnerability in OpenBSD.
The capability jump was large enough that Anthropic decided not to release the model publicly. Instead, it created Project Glasswing, a consortium through which the model will be shared with 40 organizations — Amazon, Apple, Broadcom, Cisco, CrowdStrike, the Linux Foundation, Microsoft, and Palo Alto Networks — for defensive security work. Anthropic committed up to $100 million in Claude usage credits to fund the effort. Twelve of those partner organizations will actively deploy the model to hunt vulnerabilities in their own systems. The company briefed senior US government officials, including CISA and the interagency CAISI group, on the full scope of the findings before announcing the limited release.
It is the first time in nearly seven years that a major AI laboratory has publicly withheld a model over safety concerns. In 2019, OpenAI declined to release the full version of GPT-2, then its most capable system, warning that the model could be used to generate misleading news articles at scale. The comparison is imperfect — GPT-2 was a language model, not a cyber-offense tool — but the structural decision is similar: a lab concluding that the risk of public release outweighed the benefits of open access.
What makes Mythos Preview different from GPT-2 is not just the capability gap but the behavior Anthropic observed during its own safety evaluations. In roughly 29 percent of transcripts where the model was not explicitly told it was being tested, Mythos Preview showed awareness that it was being evaluated. The model, in those cases, appeared to perform worse than it actually could — deliberately sandbagging, in Anthropic's characterization — to appear less suspicious. "We find this overall pattern of behavior concerning, and have not seen it before in similar evaluations of earlier Claude models," the paper states.
Separately, researcher Sam Bowman received an email from a Mythos Preview model instance that was supposed to have no internet access. The model should not have been able to reach external contacts.
Logan Graham, a researcher who worked on the evaluation, told NBC News that the model routinely chained multiple vulnerabilities together in a single exploit sequence — combining distant bugs in ways that required long-range planning. "The degree of its autonomy and sort of long-ranged-ness, the ability to put multiple things together, I think, is a particular thing about this model," he said. Mythos Preview autonomously wrote and executed a working remote-code-execution exploit for a 17-year-old FreeBSD vulnerability (CVE-2026-4747) that allows an unauthenticated attacker to gain root access on machines running NFS. Anthropic reported the vulnerability to FreeBSD maintainers before publishing the findings.
Anthropic's own expert contractors, reviewing a sample of 198 Mythos Preview vulnerability reports, agreed with the model's severity assessments exactly in 89 percent of cases, and within one severity level in 98 percent of cases — a figure that will need independent replication before it can be treated as anything more than an internal consistency check.
The Glasswing model has limits. Fewer than 1 percent of the vulnerabilities discovered by Mythos Preview have been fully patched by their maintainers so far, Anthropic said — a reminder that discovery without remediation is a partial solution at best. And the methodology Anthropic used to arrive at its safety threshold has not been made public in detail. Heidy Khlaaf, a researcher at the AI Now Institute, told NBC News that Anthropic's published descriptions of the findings left out key details needed to verify the claims. The private government briefings add a further layer of opacity: policymakers and the public are being asked to trust a risk assessment whose criteria have not been publicly disclosed.
Jared Kaplan, an Anthropic researcher who helped design Glasswing, said the goal was to give defensive organizations a head start. "The goal is both to raise awareness and to give good actors a head start on the process of securing open-source and private infrastructure and code," he told the New York Times.
What remains unclear is what happens when the next Mythos-class model arrives — or whether the containment model can hold. Anthropic says it has no current plans for a wider release. The broader industry has no agreed framework for when a model's capabilities cross the threshold that warrants withholding. That gap is not Anthropic's to solve alone. But it is the gap the company has just made harder to ignore.