{"data":{"id":"f66ac5b2-72e7-432c-8157-f392444144c8","title":"CVE-2026-96775: MLflow's dspy flavor, versions >= 2.0,  applies the MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False security control only when","summary":"MLflow's dspy flavor (a component for machine learning model management) in versions 2.0 and later has a security flaw where it only checks the MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False setting (a control that prevents loading untrusted serialized Python objects) when a model file ends in .pkl. An attacker can bypass this protection by using a different file extension in a crafted MLmodel artifact (a package containing model data), allowing them to run arbitrary code (malicious commands) on the system.","solution":"N/A -- no mitigation discussed in source.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2026-96775","publishedAt":"2026-09-23T17:17:25.407Z","cveId":"CVE-2026-96775","cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"high","attackType":["supply_chain"],"issueType":"vulnerability","affectedPackages":null,"affectedVendors":["HuggingFace"],"affectedVendorsRaw":["MLflow","dspy"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":"unknown","epssScore":0,"patchAvailable":null,"disclosureDate":"2026-09-23T17:17:25.407Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity","confidentiality","availability"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.92,"researchCategory":null,"atlasIds":["AML.T0010"]}}