CVE-2025-15379

Published: Mar 30, 2026 Last Modified: Mar 30, 2026
ExploitDB:
Other exploit source:
Google Dorks:
CRITICAL 10,0
Source: [email protected]
Attack Vector: network
Attack Complexity: low
Privileges Required: none
User Interaction: none
Scope: changed
Confidentiality: high
Integrity: high
Availability: high

Description

AI Translation Available

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 3.8.2.

77

Improper Neutralization of Special Elements used in a Command ('Command Injection')

Draft
Abstraction: Class Structure: Simple
Common Consequences
Security Scopes Affected:
Integrity Confidentiality Availability
Potential Impacts:
Execute Unauthorized Code Or Commands
Applicable Platforms
Technologies: AI/ML
Likelihood of Exploit: High
View CWE Details
https://github.com/mlflow/mlflow/commit/361b6f620adf98385c6…
https://github.com/mlflow/mlflow/commit/361b6f620adf98385c6721e384fb5ef9a30bb05e
https://huntr.com/bounties/dc9c1c20-7879-4050-87df-4d095fe5…
https://huntr.com/bounties/dc9c1c20-7879-4050-87df-4d095fe5ca75