{"data":{"id":"335b3f8d-d8c6-41a7-a719-6c03630bde79","title":"Measuring how AI agents handle everyday wet-lab science","summary":"OpenAI introduced BioBasicsBench, a 100-task benchmark developed with Ligo that measures how well AI agents interpret raw wet-lab experimental data, including gel images, colony plates, microscopy and instrument readouts. At the 'xhigh' reasoning setting, GPT-6 Astra earned an average of 66.7% of available credit, compared with 43.8% for GPT-5.6 Sol. The results show progress on routine lab analysis but leave room for improvement in image interpretation, control checking and applying experimental context.","solution":"N/A -- no mitigation discussed in source.","labels":["research","industry"],"sourceUrl":"https://openai.com/index/measuring-how-ai-agents-handle-wet-lab-science","publishedAt":"2026-11-06T00:00:00.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"research","affectedPackages":null,"affectedPackageNames":null,"affectedPackageRefs":null,"affectedVendors":["OpenAI"],"affectedVendorsRaw":["OpenAI","GPT-6 Astra","GPT-5.6 Sol","BioBasicsBench","Ligo"],"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":"2026-11-06T00:00:00.000Z","fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":null,"llmSpecific":true,"classifierConfidence":0.85,"researchCategory":"industry","atlasIds":null}}