{"data":{"id":"e06ed1ab-5eca-4bb2-b5ef-4cfd60afe74e","title":"CVE-2025-14920: Hugging Face Transformers Perceiver Model Deserialization of Untrusted Data Remote Code Execution Vulnerability. This vu","summary":"A vulnerability in Hugging Face Transformers' Perceiver model allows attackers to run malicious code on a user's computer by tricking them into opening a malicious file or visiting a harmful webpage. The flaw happens because the software doesn't properly check data when loading model files, allowing untrusted code to be executed (deserialization of untrusted data, where a program reconstructs objects from stored data without verifying they're safe).","solution":"N/A -- no mitigation discussed in source.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2025-14920","publishedAt":"2025-12-24T02:15:47.183Z","cveId":"CVE-2025-14920","cweIds":["CWE-502"],"cvssScore":null,"cvssSeverity":null,"severity":"critical","attackType":["model_theft"],"issueType":"vulnerability","affectedPackages":null,"affectedVendors":["HuggingFace"],"affectedVendorsRaw":["Hugging Face","Transformers"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":"unknown","epssScore":0.00277,"patchAvailable":null,"disclosureDate":null,"capecIds":["CAPEC-586"],"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity","confidentiality"],"aiComponentTargeted":"model","llmSpecific":false,"classifierConfidence":0.95,"researchCategory":null,"atlasIds":null}}