Findings

CVE-2025-15379

A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the function.

Published Mar 30, 2026 · corrected/updated Sep 4, 2026 · lfprojects mlflow · evidence confidence high

A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the function. When deploying a model with , MLflow reads dependency specifications from the model artifact's file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command execution on systems that deploy the model. The vulnerability affects versions 3.8.0 and is fixed in version 3.8.2.

Grounded briefings

Catalog interpretations for three audiences. Each brief cites ingested metadata and the original advisories below. They are not independent research and they do not invent exploit steps.

Executive

CVE-2025-15379 is a critical public vulnerability record for lfprojects mlflow. It is not currently listed in the CISA Known Exploited catalog. Check the linked vendor or CERT advisories for patch status. This summary is a catalog interpretation of the ingested metadata and cites the original advisories below.

System administrator

Identify whether lfprojects mlflow is in your estate, then compare installed versions with the affected ranges. Affected packages or ranges on record: lfprojects/mlflow. Check the linked vendor or CERT advisories for patch status. Prefer the vendor or distribution advisory linked in Sources before changing production systems. This is a catalog interpretation, not a runbook.

Security analyst

Signals on file: CVSS 10.0, EPSS 2.4%. It is not currently listed in the CISA Known Exploited catalog. Weakness classes: CWE-77, CWE-78. Sources contributing to this record: cve_org, epss, nvd. Public exploit references, when present, are outbound links only and are not proof of active exploitation. This is a catalog interpretation of stored metadata.

Exploitation and remediation

  • Exploitation evidence

    Not listed as known exploited in CISA KEV. Not in CISA KEV or VulnCheck KEV.

  • Patch and remediation

    No required-action text is stored yet. Use the vendor or CERT links in Sources for patch availability.

  • Safe detection guidance

    Compare installed versions with the affected ranges below and verify the advisory from the original publisher. This site stores metadata and outbound links only; it does not ship exploit code or proof-of-concept payloads.

Code

The project this record applies to. Exploit listings stay in References.

Timeline

Detection, updates, and resolution for this record.

  1. Mar 30, 2026 · NIST NVD

    Detected

    A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the function. When deploying a model with , MLflow reads dependency specifications from the model artifact's file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command executi

  2. Sep 4, 2026 · NIST NVD

    Updated

    A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the function. When deploying a model with , MLflow reads dependency specifications from the model artifact's file and directly interpolates them into a shell command without sanitization. This allows an attacker to supply a malicious model artifact and achieve arbitrary command executi

Affected

  • cpe lfprojects/mlflowversion unspecified

Sources

  • CVE.orgVulnerability recordCVE-2025-15379

    Official CVE identifier

    cve.org
  • FIRST EPSSExploitation probabilityCVE-2025-15379

    30-day exploitation probability 2.4%

    first.org
  • NIST NVDVulnerability recordCVE-2025-15379

    A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the function. When deploying a model with , MLflow reads dependency specifications from the model artifact's

    nvd.nist.gov

References