{"data":{"id":"a9c1295a-9b68-4afa-bdf9-d299edb1eaeb","title":"CVE-2024-37059: Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.5.0 or newer, enabling…","summary":"CVE-2024-37059 affects the MLflow platform in versions 0.5.0 and newer. Deserialization of untrusted data can occur, so a maliciously uploaded PyTorch model can run arbitrary code on an end user's system when that user interacts with it. The weakness is classified as CWE-502, Deserialization of Untrusted Data, and HiddenLayer is the listed source.","solution":"N/A -- no mitigation discussed in source.","labels":["security"],"sourceUrl":"https://nvd.nist.gov/vuln/detail/CVE-2024-37059","publishedAt":"2024-06-04T16:15:12.227Z","cveId":"CVE-2024-37059","cweIds":["CWE-502","CWE-502"],"cvssScore":"8.8","cvssSeverity":"high","severity":"high","attackType":["other"],"issueType":"vulnerability","affectedPackages":["mlflow@>= 0.5.0, <= 3.4.0"],"affectedPackageNames":["mlflow"],"affectedPackageRefs":["pypi:mlflow"],"affectedVendors":[],"affectedVendorsRaw":["MLflow","PyTorch"],"classifierModel":"claude-haiku-5-5","classifierPromptVersion":"v4","summaryPromptVersion":"v2","headline":"MLflow deserialization of untrusted data via malicious PyTorch model","headlinePromptVersion":"h1","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":"unknown","epssScore":0.00623,"epssCheckedAt":"2026-11-04T12:08:35.127Z","kevDateAdded":null,"advisoryAliases":["GHSA-wf7f-8fxf-xfxc"],"affectedPackagesSource":"ghsa","affectedPackagesCheckedAt":"2026-10-10T03:55:52.255Z","patchAvailable":null,"disclosureDate":null,"fixReleasedAt":null,"daysToFix":null,"fixCheckedAt":null,"capecIds":["CAPEC-586"],"crossRefCount":0,"attackSophistication":"moderate","impactType":["confidentiality","integrity","availability"],"aiComponentTargeted":"framework","llmSpecific":false,"classifierConfidence":0.95,"researchCategory":null,"atlasIds":null,"fixes":[]}}