{"data":{"id":"bde16603-8708-436f-be38-859ec9cecf84","title":"Red-Teaming OpenAI's Internal Agent Monitoring Systems","summary":"METR and Redwood Research staff ran a three-week pilot red-team exercise, July 21 to August 11, against OpenAI's internal misalignment monitoring system, with deep access to its codebase, monitor prompts and configuration, and interviews with about a dozen engineers. The exercise produced a 61-page internal report focused on how much agentic inference is monitored and whether agents could disable or subvert the monitor. The authors found that roughly 75–94% of eligible Responses API traffic from models at least as strong as GPT-5.5 was monitorable at the time, with 99.2% of internal Codex traffic eligible, while compaction events went unmonitored.","solution":"N/A -- no mitigation discussed in source.","labels":["security","safety"],"sourceUrl":"https://blog.redwoodresearch.org/p/red-teaming-openais-internal-agent","publishedAt":"2026-10-22T15:32:17.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"medium","attackType":["other"],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":["OpenAI"],"affectedVendorsRaw":["OpenAI","Codex","Responses API","GPT-5.5"],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":null,"headlinePromptVersion":null,"cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"epssCheckedAt":null,"kevDateAdded":null,"advisoryAliases":null,"affectedPackagesSource":null,"affectedPackagesCheckedAt":null,"patchAvailable":null,"disclosureDate":"2026-10-22T15:32:17.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"advanced","impactType":["integrity","safety"],"aiComponentTargeted":"agent","llmSpecific":true,"classifierConfidence":0.85,"researchCategory":"industry","atlasIds":null}}