{"data":{"id":"ec9bd69e-2209-4956-800a-fdbaf5506646","title":"CVE-2025-32434: PyTorch is a Python package that provides tensor computation with strong GPU acceleration and deep neural networks built","summary":"PyTorch (a Python package for machine learning computations) versions 2.5.1 and earlier contain a remote code execution (RCE, where an attacker can run commands on a system they don't own) vulnerability when loading models with the torch.load function set to weights_only=True. The vulnerability stems from insecure deserialization (converting data back into executable code without checking if it's safe), which allows attackers to execute arbitrary commands remotely.","solution":"This issue has been patched in version 2.6.0. Users should upgrade PyTorch to version 2.6.0 or later.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2025-32434","publishedAt":"2025-04-18T20:15:23.183Z","cveId":"CVE-2025-32434","cweIds":["CWE-502"],"cvssScore":"9.8","cvssSeverity":"critical","severity":"critical","attackType":["model_theft"],"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":0.01219,"patchAvailable":null,"disclosureDate":null,"capecIds":["CAPEC-586"],"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality","integrity","availability"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.95,"researchCategory":null,"atlasIds":null}}