CVE-2025-15379: CWE-77 Improper Neutralization of Special Elements used in a Command ('Command Injection') in mlflow mlflow/mlflow
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.
AI Analysis
Technical Summary
This vulnerability in MLflow (CVE-2025-15379) involves improper neutralization of special elements in a shell command, classified as CWE-77. Specifically, the _install_model_dependencies_to_env() function in MLflow's model serving container initialization reads dependency data from the python_env.yaml file of a model artifact and inserts it directly into a shell command without sanitization when env_manager=LOCAL is used. This allows an attacker who can supply a malicious model artifact to achieve arbitrary command execution on the system deploying the model. The flaw affects MLflow version 3.8.0 and was addressed in version 3.8.2.
Potential Impact
Successful exploitation allows an unauthenticated attacker to execute arbitrary commands on the host system running MLflow model serving with env_manager=LOCAL. This can lead to full system compromise, including complete loss of confidentiality, integrity, and availability of the affected system. The vulnerability has a CVSS v3 base score of 10.0, reflecting its critical impact and ease of exploitation over the network without privileges or user interaction.
Mitigation Recommendations
A fixed version of MLflow is available in version 3.8.2 that addresses this command injection vulnerability. Users should upgrade to MLflow 3.8.2 or later to remediate this issue. Until upgraded, avoid deploying models with env_manager=LOCAL using untrusted model artifacts. Patch status is confirmed fixed in version 3.8.2.
CVE-2025-15379: CWE-77 Improper Neutralization of Special Elements used in a Command ('Command Injection') in mlflow mlflow/mlflow
Description
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.
AI-Powered Analysis
Machine-generated threat intelligence
Technical Analysis
This vulnerability in MLflow (CVE-2025-15379) involves improper neutralization of special elements in a shell command, classified as CWE-77. Specifically, the _install_model_dependencies_to_env() function in MLflow's model serving container initialization reads dependency data from the python_env.yaml file of a model artifact and inserts it directly into a shell command without sanitization when env_manager=LOCAL is used. This allows an attacker who can supply a malicious model artifact to achieve arbitrary command execution on the system deploying the model. The flaw affects MLflow version 3.8.0 and was addressed in version 3.8.2.
Potential Impact
Successful exploitation allows an unauthenticated attacker to execute arbitrary commands on the host system running MLflow model serving with env_manager=LOCAL. This can lead to full system compromise, including complete loss of confidentiality, integrity, and availability of the affected system. The vulnerability has a CVSS v3 base score of 10.0, reflecting its critical impact and ease of exploitation over the network without privileges or user interaction.
Mitigation Recommendations
A fixed version of MLflow is available in version 3.8.2 that addresses this command injection vulnerability. Users should upgrade to MLflow 3.8.2 or later to remediate this issue. Until upgraded, avoid deploying models with env_manager=LOCAL using untrusted model artifacts. Patch status is confirmed fixed in version 3.8.2.
Technical Details
- Data Version
- 5.2
- Assigner Short Name
- @huntr_ai
- Date Reserved
- 2025-12-30T21:24:21.058Z
- Cvss Version
- 3.0
- State
- PUBLISHED
Threat ID: 69ca2868e6bfc5ba1de5eb91
Added to database: 3/30/2026, 7:38:16 AM
Last enriched: 4/6/2026, 10:47:25 AM
Last updated: 5/14/2026, 4:31:06 PM
Views: 1001
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