CVE-2025-14287: Mlflow MLflow Has A Command Injection Vulnerability

HIGH
Advisory Identifier: GHSA-xch3-2f9x-wh9f
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CVSS 7.5
CWE-94
Published
Advisory Summary

CVE-2025-14287 is a HIGH (CVSS 7.5) mlflow has a command injection vulnerability (CWE-94: Improper Control of Generation of Code ('Code Injection')) affecting Mlflow libraries in the PyPI ecosystem. The issue involves mlflow has a command injection in mlflow/sagemaker/__init__.py. Remediation is available by upgrading affected packages to version 3.8.0rc0.

CVE-2025-14287 at a Glance

CVE Identifier CVE-2025-14287
GHSA Identifier GHSA-xch3-2f9x-wh9f
Severity HIGH
CVSS v3.1 Base Score 7.5
CWE Classification CWE-94: Improper Control of Generation of Code ('Code Injection')
Affected Product Mlflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 7.5

The security impact metrics below are parsed directly from the CVSS v3.1 vector string (CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H).

Attack Vector Network (AV:N)
Attack Complexity High (AC:H)
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-2025-14287

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: 3.8.0rc0 
pip install mlflow>=3.8.0rc0
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-2025-14287, 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 3.8.0rc0), 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-94: Improper Control of Generation of Code ('Code Injection'), where the product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment. 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

A command injection vulnerability exists in mlflow/mlflow versions before v3.7.0, specifically in the `mlflow/sagemaker/__init__.py` file at lines 161-167. The vulnerability arises from the direct interpolation of user-supplied container image names into shell commands without proper sanitization, which are then executed using `os.system()`. This allows attackers to execute arbitrary commands by supplying malicious input through the `--container` parameter of the CLI. The issue affects environments where MLflow is used, including development setups, CI/CD pipelines, and cloud deployments.

CVE-2025-14287 Affected Mlflow Versions

1 component(s)
Fixed Versions:
3.8.0rc0
Product / Package Ecosystem Affected Versions Fixed Version
mlflow
pypi/mlflow
PyPI
< 3.8.0rc0
3.8.0rc0

References

NVD — CVE-2025-14287 NVD
https://nvd.nist.gov/vuln/detail/CVE-2025-14287
Mlflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow/pull/19277
Security Fix Commit FIX COMMIT
https://github.com/mlflow/mlflow/commit/8b8792a7034fb33a14b0b31cabcaa9b912d3485f
Mlflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow
Mlflow Release RELEASE
https://github.com/mlflow/mlflow/releases/tag/v3.8.0rc0
huntr.com/bounties/229cd526-4... WEB
https://huntr.com/bounties/229cd526-41aa-4819-b6f0-e2d0371c89e3

Frequently Asked Questions

What is CVE-2025-14287?
CVE-2025-14287 is a security vulnerability in Mlflow involving MLflow has a command injection in mlflow/sagemaker/__init__.py under CWE-94: Improper Control of Generation of Code ('Code Injection').
Which Mlflow versions are affected?
Affected versions include releases prior to 3.8.0rc0 across affected packages: mlflow.
What version fixes CVE-2025-14287?
Upgrading to 3.8.0rc0 (or the latest patched release for your respective branch) resolves the vulnerability.
Is mlflow affected?
Yes, mlflow is affected in releases prior to 3.8.0rc0. Upgrade your dependency to 3.8.0rc0 or later.
What is the CVSS score of CVE-2025-14287?
CVE-2025-14287 has a CVSS v3.1 base score of 7.5 (HIGH) with vector string CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H.
What CWE is associated with CVE-2025-14287?
CVE-2025-14287 is classified under CWE-94: Improper Control of Generation of Code ('Code Injection') (The product constructs all or part of a code segment using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the syntax or behavior of the intended code segment.).
How can I check PyPI dependencies for CVE-2025-14287?
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-xch3-2f9x-wh9f",
  "modified" : "2026-03-17T19:53:09Z",
  "published" : "2026-03-16T15:30:41Z",
  "aliases" : [ "CVE-2025-14287" ],
  "summary" : "MLflow has a command injection in mlflow/sagemaker/__init__.py",
  "details" : "A command injection vulnerability exists in mlflow/mlflow versions before v3.7.0, specifically in the `mlflow/sagemaker/__init__.py` file at lines 161-167. The vulnerability arises from the direct interpolation of user-supplied container image names into shell commands without proper sanitization, which are then executed using `os.system()`. This allows attackers to execute arbitrary commands by supplying malicious input through the `--container` parameter of the CLI. The issue affects environments where MLflow is used, including development setups, CI/CD pipelines, and cloud deployments.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H"
  } ],
  "affected" : [ {
    "package" : {
      "ecosystem" : "PyPI",
      "name" : "mlflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "3.8.0rc0"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2025-14287"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/pull/19277"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/commit/8b8792a7034fb33a14b0b31cabcaa9b912d3485f"
  }, {
    "type" : "PACKAGE",
    "url" : "https://github.com/mlflow/mlflow"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/releases/tag/v3.8.0rc0"
  }, {
    "type" : "WEB",
    "url" : "https://huntr.com/bounties/229cd526-41aa-4819-b6f0-e2d0371c89e3"
  } ],
  "database_specific" : {
    "cwe_ids" : [ "CWE-94" ],
    "severity" : "HIGH",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-03-17T19:53:09Z",
    "nvd_published_at" : "2026-03-16T14:17:55Z"
  }
}