CVE-2024-37059: Mlflow MLFlow Unsafe Deserialization Vulnerability

HIGH
Advisory Identifier: GHSA-wf7f-8fxf-xfxc
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CVSS 8.8
CWE-502
Published
Advisory Summary

CVE-2024-37059 is a HIGH (CVSS 8.8) mlflow unsafe deserialization vulnerability (CWE-502: Deserialization of Untrusted Data) affecting Mlflow libraries in the PyPI ecosystem. The issue involves mlflow unsafe deserialization. Remediation is available in the latest vendor maintenance releases.

CVE-2024-37059 at a Glance

CVE Identifier CVE-2024-37059
GHSA Identifier GHSA-wf7f-8fxf-xfxc
Severity HIGH
CVSS v3.1 Base Score 8.8
CWE Classification CWE-502: Deserialization of Untrusted Data
Affected Product Mlflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 8.8

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H).

Attack Vector Network (AV:N)
Attack Complexity Low (AC:L)
Privileges Required None (PR:N)
User Interaction Required (UI:R)
Scope Unchanged (S:U)
Confidentiality High (C:H)
Integrity High (I:H)
Availability High (A:H)

How to Fix CVE-2024-37059

To remediate this vulnerability, upgrade all affected Mlflow dependencies to a patched release. Both direct and transitive dependencies should be checked, as frameworks or security libraries may pull in vulnerable versions transitively.

mlflow fixed: Latest secure release 
pip install mlflow>=Latest secure release
Verify Direct and Transitive Dependencies

Run the following command in your project directory to verify that all resolved dependencies use the patched release: 

pip show mlflow

How to Check if You Are Affected

To determine whether your Python environment is affected by CVE-2024-37059, inspect your installed packages using pip:

pip show mlflow

Analyze the terminal output to locate any version of Mlflow in your dependency tree. If any resolved version matches the vulnerable ranges listed in the table below (for example, versions earlier than the patched release), your application is affected.

Note: The pip show mlflow command checks currently installed packages in your active Python environment.

Technical Details

Vulnerability Mechanism & Technical Analysis

This vulnerability is classified under CWE-502: Deserialization of Untrusted Data, where the product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid. In Mlflow, software state validation or input boundaries are circumvented during processing. Review the official source advisory statement below for specific affected components, classes, and reproduction details.

Source Advisory Statement

Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.5.0 or newer, enabling a maliciously uploaded PyTorch model to run arbitrary code on an end user’s system when interacted with.

CVE-2024-37059 Affected Mlflow Versions

1 component(s)
Product / Package Ecosystem Affected Versions Fixed Version
mlflow
pypi/mlflow
PyPI
≥ 0.5.0
≤ 3.4.0

References

NVD — CVE-2024-37059 NVD
https://nvd.nist.gov/vuln/detail/CVE-2024-37059
Mlflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow
Mlflow Security Information SECURITY
https://hiddenlayer.com/sai-security-advisory/mlflow-june2024

Frequently Asked Questions

What is CVE-2024-37059?
CVE-2024-37059 is a security vulnerability in Mlflow involving MLFlow unsafe deserialization under CWE-502: Deserialization of Untrusted Data.
Which Mlflow versions are affected?
Affected versions include releases prior to current release patches across affected packages: mlflow.
What version fixes CVE-2024-37059?
Upgrading to current release patches (or the latest patched release for your respective branch) resolves the vulnerability.
Is mlflow affected?
Yes, mlflow is affected in releases prior to Latest secure release. Upgrade your dependency to Latest secure release or later.
What is the CVSS score of CVE-2024-37059?
CVE-2024-37059 has a CVSS v3.1 base score of 8.8 (HIGH) with vector string CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H.
What CWE is associated with CVE-2024-37059?
CVE-2024-37059 is classified under CWE-502: Deserialization of Untrusted Data (The product deserializes untrusted data without sufficiently ensuring that the resulting data will be valid.).
How can I check PyPI dependencies for CVE-2024-37059?
Run the dependency tree command: 'pip show mlflow'. This command lists direct and transitive dependencies in your build configuration so you can verify if a vulnerable version is resolved.
Machine-readable OSV JSON OSV v1.5 Schema
Normalized schema output
View Raw JSON 
{
  "schema_version" : "1.4.0",
  "id" : "GHSA-wf7f-8fxf-xfxc",
  "modified" : "2025-09-29T19:36:21Z",
  "published" : "2024-06-04T12:31:05Z",
  "aliases" : [ "CVE-2024-37059" ],
  "summary" : "MLFlow unsafe deserialization",
  "details" : "Deserialization of untrusted data can occur in versions of the MLflow platform running version 0.5.0 or newer, enabling a maliciously uploaded PyTorch model to run arbitrary code on an end user’s system when interacted with.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "mlflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0.5.0"
      }, {
        "last_affected" : "3.4.0"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2024-37059"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/mlflow/mlflow"
  }, {
    "type" : "WEB",
    "url" : "https://hiddenlayer.com/sai-security-advisory/mlflow-june2024"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-502" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2024-06-05T13:21:55Z",
    "nvd_published_at" : "2024-06-04T12:15:12Z"
  }
}