CVE-2025-15379: Mlflow MLflow Command Injection Vulnerability Vulnerability

CRITICAL
Advisory Identifier: GHSA-r23q-823p-vmf7
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CVSS 10.0
CWE-77
Published
Advisory Summary

CVE-2025-15379 is a CRITICAL (CVSS 10.0) mlflow command injection vulnerability vulnerability (CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection')) affecting Mlflow libraries in the PyPI ecosystem. The issue involves mlflow command injection vulnerability. Remediation is available by upgrading affected packages to version 3.8.1.

CVE-2025-15379 at a Glance

CVE Identifier CVE-2025-15379
GHSA Identifier GHSA-r23q-823p-vmf7
Severity CRITICAL
CVSS v3.1 Base Score 10.0
CWE Classification CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection')
Affected Product Mlflow
Package Ecosystem PyPI
Published Date
Last Updated

Security Impact

CVSS: 10.0

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

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

How to Fix CVE-2025-15379

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: 3.8.1 
pip install mlflow>=3.8.1
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-2025-15379, 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 3.8.1), 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-77: Improper Neutralization of Special Elements used in a Command ('Command Injection'), where the product constructs all or part of a command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended command when it is sent to a downstream component. 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's model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact's `python_env.yaml` 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 3.8.1.

CVE-2025-15379 Affected Mlflow Versions

1 component(s)
Fixed Versions:
3.8.1
Product / Package Ecosystem Affected Versions Fixed Version
mlflow
pypi/mlflow
PyPI
< 3.8.1
3.8.1

References

NVD — CVE-2025-15379 NVD
https://nvd.nist.gov/vuln/detail/CVE-2025-15379
Security Fix Commit FIX COMMIT
https://github.com/mlflow/mlflow/commit/361b6f620adf98385c6721e384fb5ef9a30bb05e
Security Fix Commit FIX COMMIT
https://github.com/mlflow/mlflow/commit/a22ce7157f646bdce4c95106fc38ccc9ca289205
Mlflow Source Repository REPOSITORY
https://github.com/mlflow/mlflow
huntr.com/bounties/dc9c1c20-7... WEB
https://huntr.com/bounties/dc9c1c20-7879-4050-87df-4d095fe5ca75

Frequently Asked Questions

What is CVE-2025-15379?
CVE-2025-15379 is a security vulnerability in Mlflow involving MLflow Command Injection vulnerability under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection').
Which Mlflow versions are affected?
Affected versions include releases prior to 3.8.1 across affected packages: mlflow.
What version fixes CVE-2025-15379?
Upgrading to 3.8.1 (or the latest patched release for your respective branch) resolves the vulnerability.
Is mlflow affected?
Yes, mlflow is affected in releases prior to 3.8.1. Upgrade your dependency to 3.8.1 or later.
What is the CVSS score of CVE-2025-15379?
CVE-2025-15379 has a CVSS v3.1 base score of 10.0 (CRITICAL) with vector string CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H.
What CWE is associated with CVE-2025-15379?
CVE-2025-15379 is classified under CWE-77: Improper Neutralization of Special Elements used in a Command ('Command Injection') (The product constructs all or part of a command using externally-influenced input from an upstream component, but it does not neutralize or incorrectly neutralizes special elements that could modify the intended command when it is sent to a downstream component.).
How can I check PyPI dependencies for CVE-2025-15379?
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-r23q-823p-vmf7",
  "modified" : "2026-04-01T19:08:35Z",
  "published" : "2026-03-30T09:31:28Z",
  "aliases" : [ "CVE-2025-15379" ],
  "summary" : "MLflow Command Injection vulnerability",
  "details" : "A command injection vulnerability exists in MLflow's model serving container initialization code, specifically in the `_install_model_dependencies_to_env()` function. When deploying a model with `env_manager=LOCAL`, MLflow reads dependency specifications from the model artifact's `python_env.yaml` 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 3.8.1.",
  "severity" : [ {
    "type" : "CVSS_V3",
    "score" : "CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H"
  } ],
  "affected" : [ {
    "package" : {
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      "name" : "mlflow"
    },
    "ranges" : [ {
      "type" : "ECOSYSTEM",
      "events" : [ {
        "introduced" : "0"
      }, {
        "fixed" : "3.8.1"
      } ]
    } ]
  } ],
  "references" : [ {
    "type" : "ADVISORY",
    "url" : "https://nvd.nist.gov/vuln/detail/CVE-2025-15379"
  }, {
    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/commit/361b6f620adf98385c6721e384fb5ef9a30bb05e"
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    "type" : "WEB",
    "url" : "https://github.com/mlflow/mlflow/commit/a22ce7157f646bdce4c95106fc38ccc9ca289205"
  }, {
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    "url" : "https://github.com/mlflow/mlflow"
  }, {
    "type" : "WEB",
    "url" : "https://huntr.com/bounties/dc9c1c20-7879-4050-87df-4d095fe5ca75"
  } ],
  "database_specific" : {
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    "severity" : "CRITICAL",
    "github_reviewed" : true,
    "github_reviewed_at" : "2026-04-01T00:08:33Z",
    "nvd_published_at" : "2026-03-30T08:16:15Z"
  }
}