OpenAI says new GPT-5.5-Cyber outperforms Anthropic’s Mythos on cybersecurity benchmark
OpenAI is expanding its Daybreak cybersecurity initiative with an updated Codex Security plugin, the full GPT-5.5-Cyber model, and a partner network with more than 25 security firms and several governments. The focus shifts from finding vulnerabilities to patching them automatically.
The real bottleneck in cybersecurity has moved from finding flaws to actually patching them. To close that gap, OpenAI is shipping an updated Codex Security plugin that covers the full pipeline from discovery to patch generation, along with the full release of GPT-5.5-Cyber, a specialized model that sets new highs on security benchmarks. OpenAI also launched an open-source patching initiative and a partner program with more than 25 security firms. Codex Security update closes the loop from discovery to patch The Codex Security plugin shipped as a research preview back in March. Since then, it’s scanned over 30 million commits across more than 30,000 codebases, OpenAI says. Over 500,000 findings were automatically flagged as fixed, and human reviewers manually confirmed another 70,000. OpenAI wants the updated plugin to act like a security engineer sitting next to every developer. It analyzes code alongside a threat model, spots flaws, checks whether affected code is actually reachable, builds a targeted patch, and verifies the result. New in this update are deep scans of entire codebases, attack path analysis, and export to existing vulnerability management systems through SARIF files or CodeQL queries. The plugin can also triage findings from other scanners or bug bounty reports and automate patch generation in batch mode. Humans still sign off on every change, OpenAI says. The full version of GPT-5.5-Cyber replaces an earlier preview that mostly aimed to cut unnecessary refusals in security workflows. OpenAI calls the updated model the most capable single model for finding and patching software flaws. GPT-5.5-Cyber leads on all key cybersecurity benchmarks, according to OpenAI. CyberGym measures whether an agent can reproduce known flaws in software environments.
