{"data":{"id":"faf8a008-0f24-4354-ac6f-1a02f66a8441","title":"CVE-2026-96804: MLflow's statsmodel flavor, versions 2.1.0 to 3.14.0, omits the MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False security contr","summary":"MLflow (a platform for managing machine learning workflows) versions 2.1.0 to 3.14.0 have a bug where they skip a security setting called MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False when loading statsmodel flavor (a type of statistical model) files. This allows an attacker to upload a malicious model file that runs harmful code on the system when the model is loaded.","solution":"N/A -- no mitigation discussed in source.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2026-96804","publishedAt":"2026-09-23T17:17:25.530Z","cveId":"CVE-2026-96804","cweIds":["CWE-502"],"cvssScore":"8.8","cvssSeverity":"high","severity":"high","attackType":["supply_chain"],"issueType":"vulnerability","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":["MLflow"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":"CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H","attackVector":"network","attackComplexity":"low","privilegesRequired":"low","userInteraction":"none","exploitMaturity":"unknown","epssScore":0,"patchAvailable":null,"disclosureDate":"2026-09-23T17:17:25.530Z","capecIds":["CAPEC-586"],"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity","confidentiality","availability"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.95,"researchCategory":null,"atlasIds":["AML.T0010"]}}