{"data":{"id":"1f306eba-acd9-4ed1-a02e-08889059eb06","title":"CVE-2025-2953: A vulnerability, which was classified as problematic, has been found in PyTorch 2.6.0+cu124. Affected by this issue is t","summary":"A vulnerability in PyTorch 2.6.0+cu124 affects the torch.mkldnn_max_pool2d function, a component used for processing image data. The vulnerability can cause a denial of service (making a system unavailable), but requires local access to the machine. The vulnerability's real existence is still disputed.","solution":"N/A -- no mitigation discussed in source.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2025-2953","publishedAt":"2025-03-30T20:15:14.380Z","cveId":"CVE-2025-2953","cweIds":["CWE-404"],"cvssScore":"3.3","cvssSeverity":"low","severity":"low","attackType":["denial_of_service"],"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":0.00139,"patchAvailable":null,"disclosureDate":null,"capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["availability"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.85,"researchCategory":null,"atlasIds":null}}