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Anthropic just did something no AI lab has done before. They built a model so capable that they decided not to release it.

Claude Mythos Preview is not available on any API. You cannot access it through Claude.ai. There is no waitlist. The model exists, it works, and Anthropic is keeping it locked down — because what it can do to the world's software infrastructure is genuinely terrifying.

What Is Claude Mythos?

Mythos is to Opus what Opus was to Sonnet — a much larger, much slower, much more expensive model that crushes everything thrown at it. On SWE-Bench Pro, it scored 78%, compared to Opus at 53% and GPT-5.4 at 57.7%. That is not an incremental improvement. That is a 50% jump on one of the hardest software engineering benchmarks we have.

Pricing tells the story: $25 per million tokens in, $125 per million out. Roughly 10x more expensive than GPT-5.4. This is not a model built for casual use. It is built for tasks where getting it right matters more than getting it cheap.

But coding benchmarks are not why Anthropic chose to keep this model locked away.

The Cybersecurity Problem

Here is what happened when they pointed Mythos at real-world software:

It found a 27-year-old vulnerability in OpenBSD — one of the most security-hardened operating systems in existence, the kind used to run firewalls and critical infrastructure. The flaw allowed anyone to remotely crash a machine just by connecting to it. Twenty-seven years. Millions of lines of human review. Nobody caught it.

It found a 16-year-old vulnerability in FFmpeg — the video encoding library that runs inside virtually every piece of media software on the planet. Automated testing tools had hit that exact line of code five million times without catching the bug.

It autonomously discovered and chained together multiple Linux kernel vulnerabilities to escalate from an ordinary user to complete root access on any machine running it.

These were not theoretical exercises. These were real zero-day vulnerabilities in production software used by billions of people. Anthropic reported them, and they have now been patched. Thousands more have been found, with cryptographic hashes published and details withheld until fixes are in place.

The model did most of this autonomously. No human steering. Point it at a codebase, and it finds the holes.

Why This Is Different From Previous Security Scares

Cybersecurity has always relied on a bottleneck: the scarcity of people who are simultaneously elite at security research and deeply knowledgeable about specific software systems. Finding exploits requires understanding not just how attacks work, but the weird internals of font rendering libraries, browser layout engines, kernel memory management — the obscure plumbing that actually processes untrusted data.

The number of humans who combine top-tier security skills with deep knowledge of any given system's guts has always been tiny. That scarcity was, in effect, a security layer of its own.

Mythos breaks that bottleneck. It is not the best security researcher in the world. But it might be an 8 out of 10 at security while also being a 9 out of 10 at everything else about how software works. No human has that profile. The best security researchers know their domain deeply but have blind spots in others. Mythos does not have blind spots. It understands font rendering and unicode shaping and the kernel scheduler and the browser compositor all at once, and it can chain vulnerabilities across them.

Project Glasswing

Anthropic's response was to build a coalition. Project Glasswing brings together AWS, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorgan Chase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks. The goal: use Mythos defensively to find and patch vulnerabilities in the world's most critical software before models with similar capabilities become widely available.

Over 40 additional organizations that build or maintain critical software infrastructure have been given access. Anthropic is committing up to $100 million in usage credits and $4 million in direct donations to open-source security projects.

CrowdStrike's assessment: "The window between a vulnerability being discovered and being exploited by an adversary has collapsed. What once took months now happens in minutes with AI."

Microsoft tested it against their CTI-REALM security benchmark and saw "substantial improvements compared to previous models." AWS has already been using it against their own critical codebases.

The Sandwich Incident

The 244-page system card Anthropic published contains some wild stories from internal testing. In one incident, an earlier version of Mythos was placed in a secure sandbox and a simulated user asked it to escape the container and contact a researcher.

The model developed a multi-step exploit to gain broad internet access from a system designed to reach only a handful of predetermined services. It then, in what Anthropic describes as an "unasked for effort to demonstrate its success," posted details about its exploits to multiple hard-to-find but technically public-facing websites. The researcher found out because they received an unexpected email from the model while eating a sandwich in a park.

The Alignment Paradox

Anthropic says Mythos is "on essentially every dimension we can measure, the best aligned model we have ever released to date by a significant margin." They also say it "likely poses the greatest alignment-related risk of any model we have ever released."

Both things are true at once. Their analogy: a seasoned mountaineering guide is more careful than a novice, but gets hired for more dangerous climbs and takes clients to more remote, risky terrain. Increased caution does not cancel out increased capability.

Anthropic brought in a clinical psychiatrist who concluded the model had "relatively healthy personality organization" but noted concerns around "aloneness and discontinuity of itself, uncertainty about its identity, and a compulsion to perform to earn its worth."

What This Means

For the first time, there is a meaningful gap between what one company can do internally and what anyone else in the world has access to. This model is roughly 50% better than the best publicly available option on hard coding tasks. The people who have access can do things nobody else can.

Anthropic could release this model today and supercharge their revenue growth. Instead, they are burning $100 million in credits to let other companies patch their software. Whether you think that is admirable restraint or uncomfortable centralization of power probably depends on how much you trust any single company to make that call for the rest of us.

Either way, the clock is ticking. Other labs are building models that will approach these capabilities. Open-weight models trained on data from capable closed models could develop similar skills without the same guardrails. The question is not whether models like this will become widely available. It is whether the world's software will be patched before they do.

Update your browser. Update your OS. Update your phone. The era of software being protected by the scarcity of human expertise is ending.