MLflow has a command injection in mlflow/sagemaker/__init__.py

Exploitation

No confirmed exploitation recorded. Patch Next marks exploitation only from CISA KEV.

CVSS

7.5 · CVSS:3.0/AV:N/AC:H/PR:N/UI:R/S:U/C:H/I:H/A:H

EPSS

• CVE-2025-14287: 1.52% estimated exploitation activity in the next 30 days; percentile 74.54 (FIRST EPSS, 2026-11-03). This is a model estimate, not proof of exploitation or customer exposure.

As published by the source; long descriptions are shortened.

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.

Published by the source

16 Mar 2026, 15:30 UTC

Last modified by the source

10 Sep 2026, 03:51 UTC

Source last checked

26 Oct 2026, 13:37 UTC

1. Revision 2 · amended · 26 Oct 2026

   Amended from ghsa record GHSA-xch3-2f9x-wh9f

2. Revision 1 · created · 24 Oct 2026

   Published from osv record GHSA-xch3-2f9x-wh9f

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# Patch Next advisory brief: CVE-2025-14287

Advisory: MLflow has a command injection in mlflow/sagemaker/__init__.py
IDs: CVE-2025-14287, GHSA-xch3-2f9x-wh9f
Record: https://patchnext.com/advisories/cve-2025-14287 (revision 2, source checked 26 Oct 2026, 13:37 UTC)
Inventory: none attached. This brief comes from a public page and does not say whether any deployment is affected.
Severity: High (CVSS 7.5)
Exploitation: no confirmed exploitation recorded. Patch Next confirms exploitation only from CISA KEV.
Vendor response: Vendor fix available; fixed versions by package: mlflow 3.8.0rc0. A vendor fix does not mean a deployment is fixed.

## Affected components
- PyPI mlflow: affected < 3.8.0rc0; fixed in 3.8.0rc0

## Suggested inspection (read-only)
- `python -m pip show mlflow`: prints the installed version. Run with the environment that serves production active.

## Supported action
Upgrade each affected component to a fixed version on its release line. For a transitive dependency, upgrade the parent package or add an override or constraint, then regenerate the lockfile. Redeploy every environment that ran an affected version.

## Required regression checks
- Run the test suite and a production build.
- Exercise the features that depend on mlflow.
- Repeat the inspection and confirm that only fixed versions remain installed.

## Rollback considerations
- Keep the previous lockfile and deployment artifact. Rolling back reinstates the vulnerable version, so apply any documented mitigation while you fix forward.

## Unresolved questions
- Which deployments run an affected version?
- Exploitation status can change. Check again before lowering the priority.
- Mark the work resolved only after the fixed version is verified in production.

## Sources
- Verified: https://osv.dev/vulnerability/GHSA-xch3-2f9x-wh9f (OSV record GHSA-xch3-2f9x-wh9f lists affected ranges: PyPI mlflow >=0 <3.8.0rc0 (fixed))
- Verified: https://github.com/advisories/GHSA-xch3-2f9x-wh9f (GitHub-reviewed advisory GHSA-xch3-2f9x-wh9f lists affected ranges: PyPI mlflow >=0 <3.8.0rc0)

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