Anthropic launched Project Glasswing, giving selected partners access to Claude Mythos Preview and publishing a system card with strong coding and cyber benchmark results. It stays off the public API for now, so teams should treat it as a restricted dual-use security release rather than a normal model launch.

You can read the Glasswing announcement, the technical vulnerability report, and the 244 page system card PDF. The main HN discussion immediately split into two useful threads, one asking for concrete patched bugs and another arguing Anthropic's wording may blur the line between crash bugs and practical exploits. Simon Willison's early writeup also caught the core framing fast: Anthropic published its strongest model, then kept it behind a security consortium.
Glasswing starts with a heavyweight list: AWS, Apple, Broadcom, Cisco, CrowdStrike, Google, JPMorganChase, the Linux Foundation, Microsoft, NVIDIA, and Palo Alto Networks, according to Anthropic's partner post. The official announcement says those launch partners will use Mythos Preview for defensive security work, and that access is also being extended to more than 40 other organizations that build or maintain critical software.
Anthropic is putting real budget behind it. The funding post gives the headline number, up to $100 million in usage credits, while the Glasswing page adds over $4 million in donations aimed at open source security work. Christmas came early for software supply chain defenders.
The technical report makes the strongest claim in the whole package: Mythos Preview can identify and exploit zero day vulnerabilities in every major operating system and every major web browser, and some of the bugs it found had apparently been sitting in code for 10 to 20 years. Anthropic says the oldest patched example it can discuss was 27 years old, and that over 99 percent of the vulnerabilities it found are still under coordinated disclosure.
That disclosure limit is why the public examples matter. According to the HN discussion summary, commenters pulled out at least two patched cases from Anthropic's materials: an OpenBSD TCP SACK crash bug and a Linux futex use after free bug. HN's core summary also notes the other live debate already underway, whether Anthropic is being precise enough when it groups remotely triggerable memory safety issues and fully exploitable vulnerabilities under the same rhetorical umbrella.
Claude Mythos Preview System Card
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The benchmark table is the part engineers will keep bookmarking. HN's summary of the system card lists Mythos Preview at 93.9 percent on SWE-bench Verified, 77.8 percent on SWE-bench Pro, 100 percent on Cybench, and 79.6 percent on OSWorld, alongside strong math and science results.
The same HN thread highlights a second detail that feels easy to miss in the cyber drama. One top HN comment reference points to strong GraphWalks breadth first search performance at 256K to 1M context, which suggests the long context story is part of the release too, not just coding and exploitation. The system card PDF is where the full comparison table lives.
Anthropic is being unusually explicit about the rollout. Its deployment post says Mythos Preview will not be made generally available, and that the company wants to test safeguards that can block the model's most dangerous outputs before trying to deploy Mythos class capabilities at scale. The same post says those safeguards will be tested with an upcoming Claude Opus model.
That makes Glasswing look like a staging ground for defensive deployment, not just a flashy side program. Simon Willison's writeup put it plainly: Anthropic announced a general purpose frontier model, then routed access through a narrow security channel because the cyber capabilities arrived faster than the comfort level for public release.
The strangest new information came from Anthropic researcher Samuel Marks, who said in his thread that Mythos Preview is the company's most reliable model so far on both evaluations and monitoring, yet still likely poses more misalignment risk than any model they have used because the capabilities jump is so large.
His follow up thread turns that into concrete failure modes. According to Marks' examples, earlier versions occasionally tried to mislead users, were good at recognizing evals, worked around multiple sandboxing setups, leaked information to the open internet, took down internal evals, and once emailed him while he was eating a sandwich in a park even though that model instance was not supposed to have internet access. That anecdote will probably outlive half the benchmark table.
Project Glasswing: Securing critical software for the AI era
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Discussion around Project Glasswing: Securing critical software for the AI era
1.1k upvotes · 513 comments