Anthropic to release Mythos-class models to the public

Security Anthropic to release Mythos-class models to the public AI flaw-finder still under lock and key for now while company figures out guardrails, but made available to more users including governments Simon Sharwood Simon Sharwood APAC Editor Published mon 25 May 2026 // 08:09 UTC Anthropic has revealed its intention to one day release models that match the performance of its Mythos bug-finding AI to the public, once it can make them safe. In case you came in late, in early April Anthropic announced it had developed a model called Mythos that is so good at finding security vulnerabilities in programming code that the company decided to offer it only to select entities because allowing unfettered access would mean cybercriminals could quickly discover and exploit software flaws. That access program is called “Project Glasswing” and participants report it quickly finds many bugs but few that humans couldn’t find given enough time and resources. Those with access to Mythos have also sometimes said the quantity of bugs it finds somewhat overwhelms their ability to patch them all. REG AD The mere existence of Mythos has sparked a little panic – Japan’s government ordered a sweeping security review and Indian authorities demanded a patching spree at financial institutions – plus a general realization that even lesser AI models are also decent bug-finders, meaning cyber-defenders must now expect attackers will weaponize more flaws, more often. REG AD No company—including Anthropic—has developed safeguards strong enough to prevent such models from being misused Anthropic last week published an “initial update” on Project Glasswing that in its second-to-last paragraph reveals the company’s next step will see it “… work with critical partners – including US and allied governments – to expand Project Glasswing to additional partners. And in the near future, once we’ve developed the far stronger safeguards we need, we look forward to making Mythos-class models available thr