Collinear AI releases CWE-bench v2 with 100 security tasks
Collinear AI has published CWE-bench v2, a public benchmark of 100 security tasks covering 91 different weakness classes, announced on the Hugging Face blog. Each task gives an agent a checkout of a real open-source repository and a short instruction to find and fix a vulnerability without breaking existing functionality, and all scoring is programmatic, so results are deterministic and reproducible at no extra cost. A held-out set is available by request. The public set, grader and harness are open, with every task shipped as a Dockerized Harbor environment and tagged as an RL environment that can also reward training defensive agents. On the project's leaderboards, Gemini 4 Argon leads with 67.8% pass@1 and 81.0% pass@4, just ahead of Claude Opus 5.5, and 95 tasks are solved by at least one of the 11 evaluated models.
Why it matters
People picking a coding model get a reproducible, programmatic way to see whether it can actually locate and fix real security bugs, not just match a familiar pattern. Because the same verifiers are packaged as RL environments, they can also be used to train defensive agents.
Sources
- PrimaryHugging Face
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