{"data":{"id":"dc70cf75-f424-47c3-af85-07d07f967c99","title":"CVE-2025-46150: In PyTorch before 2.7.0, when torch.compile is used, FractionalMaxPool2d has inconsistent results.","summary":"CVE-2025-46150 is a bug in PyTorch (a machine learning framework) versions before 2.7.0 where FractionalMaxPool2d (a function that reduces image dimensions) produces inconsistent results when torch.compile (a performance optimization tool) is used. The issue causes the function to give different outputs under the same conditions, which is problematic for machine learning models that need reproducible, reliable results.","solution":"Upgrade to PyTorch version 2.7.0 or later.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2025-46150","publishedAt":"2025-09-25T19:16:12.303Z","cveId":"CVE-2025-46150","cweIds":null,"cvssScore":"5.3","cvssSeverity":"medium","severity":"medium","attackType":[],"issueType":"vulnerability","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":["PyTorch"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":"unknown","epssScore":0.00053,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":null,"atlasIds":null}}