{"data":{"id":"8f7657e7-ab83-4366-9c7e-c97cf60bb457","title":"OpenAI Launches Full-Scale Effort to Patch Open-Source Bugs as It Takes on Anthropic’s Mythos","summary":"OpenAI launched \"Patch the Planet,\" a program partnering with security firms Trail of Bits, HackerOne, and Calif to provide free security consulting to open-source software maintainers. The initiative helps developers find and patch vulnerabilities (security weaknesses in code), strengthen their code bases, and incorporate AI security tools, addressing the problem that AI-powered bug-hunting tools have overwhelmed maintainers with large numbers of vulnerability reports they struggle to prioritize.","solution":"OpenAI is providing free security consulting services through Patch the Planet to help open-source maintainers find and patch vulnerabilities, strengthen code bases, and incorporate AI security tools into their development process. The company is also subsidizing Codex Security scanner usage (an AI tool that finds bugs in code) for open-source and private code projects, and Trail of Bits has committed long-term resources funded by OpenAI to work on large-scale open-source security issues by tailoring support to each project's specific priorities.","labels":["security","industry"],"sourceUrl":"https://www.wired.com/story/openai-launches-full-scale-effort-to-patch-open-source-bugs-as-it-takes-on-anthropics-mythos/","publishedAt":"2026-06-22T17:00:00.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"news","affectedPackages":null,"affectedVendors":["OpenAI"],"affectedVendorsRaw":["OpenAI","Anthropic","Trail of Bits","HackerOne"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":"2026-06-22T17:00:00.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":null,"llmSpecific":true,"classifierConfidence":0.85,"researchCategory":null,"atlasIds":null}}