{"data":{"id":"0d1aaf56-b6e4-4081-b641-b1b8e9d89dc9","title":"CVE-2025-15379: A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the `_","summary":"MLflow has a command injection vulnerability (a type of attack where an attacker inserts malicious commands into input that gets executed) in its model serving code when deploying models with `env_manager=LOCAL`. The vulnerability occurs because MLflow reads dependency information from a file called `python_env.yaml` in the model artifact and directly uses it in a shell command without checking if it's safe, allowing an attacker to execute arbitrary commands on the system deploying the model.","solution":"Update MLflow to version 3.8.2, which fixes the vulnerability. Version 3.8.0 is affected.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2025-15379","publishedAt":"2026-03-30T08:16:15.667Z","cveId":"CVE-2025-15379","cweIds":["CWE-77"],"cvssScore":null,"cvssSeverity":null,"severity":"critical","attackType":["supply_chain"],"issueType":"vulnerability","affectedPackages":null,"affectedVendors":[],"affectedVendorsRaw":["MLflow"],"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":"2026-03-30T08:16:15.667Z","capecIds":["CAPEC-88"],"crossRefCount":0,"attackSophistication":"moderate","impactType":["integrity","availability"],"aiComponentTargeted":"inference","llmSpecific":false,"classifierConfidence":0.95,"researchCategory":null,"atlasIds":["AML.T0010"]}}