{"data":{"id":"e3f5c605-0cad-474d-8990-21e2799fb3b7","title":"CVE-2025-46153: PyTorch before 3.7.0 has a bernoulli_p decompose function in decompositions.py even though it lacks full consistency wit","summary":"PyTorch versions before 3.7.0 have a bug in the bernoulli_p decompose function (a mathematical operation used in the dropout layers) that doesn't work the same way as the main CPU implementation, causing problems with nn.Dropout1d, nn.Dropout2d, and nn.Dropout3d when fallback_random=True (a setting that uses random number generation as a backup method).","solution":"N/A -- no mitigation discussed in source.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2025-46153","publishedAt":"2025-09-25T19:16:12.603Z","cveId":"CVE-2025-46153","cweIds":["CWE-1176"],"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":0.0007,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":null,"atlasIds":null}}