HighVulnerability

CVE-2024-37052: MLflow deserialization of untrusted data via uploaded scikit-learn model

Source: NVD(opens in a new tab)
Identifier: CVE-2024-37052
Published: June 4, 2024
Record updated: October 9, 2026

Affected: mlflow >= 1.1.0, <= 2.14.1
Fixed in: No fixed version was stated when the source was last read.
Known exploitation: Not listed in the CISA Known Exploited Vulnerabilities catalog at the last check.
EPSS: 0.7%

Summary

CVE-2024-37052 affects the MLflow platform in versions 1.1.0 and newer. Deserialization of untrusted data lets a maliciously uploaded scikit-learn model run arbitrary code on an end user's system when that model is interacted with. The weakness is classified as CWE-502, and NVD has not yet provided an assessment.

Mitigation

The source does not state a fix yet. Check the original advisory for updates.

Details

Scores and exploitation

CVSS score: 8.8(high)
EPSS: 0.7%Estimated probability that this CVE is exploited in the next 30 days, from the FIRST Exploit Prediction Scoring System. Read on November 4, 2026.

Weaknesses and techniques

Weakness (CWE): CWE-502
CWE-502
Attack pattern (CAPEC): CAPEC-586
AI threat technique (MITRE ATLAS): AML.T0010

Affected

Packages: mlflow@>= 1.1.0, <= 2.14.1
Vendors: HuggingFace

Classification

Attack type: Supply chain
Attack sophistication: Moderate
AI component targeted: Framework
Impact: Confidentiality,
Integrity,
Availability
Labels: security

How this record was produced

Summaries, mitigations and labels on this page are generated automatically from the source. The linked source is authoritative. The source gives this advisory a description and no title, so the title above is a headline generated from the source text.

Original source: https://nvd.nist.gov/vuln/detail/CVE-2024-37052

First tracked: February 15, 2026 at 08:42 PM ET, from NVD/CVE Database

Classifier: claude-haiku-5-5, prompt v4

Classifier confidence: 90% (self-assessed)

Affected packages in the Exposure Registry

Matched by package name and ecosystem. Each entry shows whether the package delegates to a language model and how many tracked packages depend on it.

mlflowPyPILLM dependency since 2024-05-30 · 17 tracked dependents

Summary

Mitigation

Affected packages in the Exposure Registry

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