CVE-2025-15379

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.

What this means for your business

It affects Lfprojects Mlflow. It matters if your company, or a supplier that handles your data, runs it.
Code showing how to exploit it has been published, but real attacks have not been confirmed.
An attacker can use it remotely, over a network, without a login, and without anyone at your company clicking anything.
FIRST's prediction model gives it a 2% chance of attack attempts being seen in the next 30 days, ranking above 82% of all known flaws.

What to do

1Check whether your company or your suppliers run Lfprojects Mlflow, and which version. The affected versions are listed further down this page.
2If you do, apply the vendor's fix. A patch or vendor advisory has been published.

Not sure if your company is exposed?

Fastnexa’s certified penetration testers can check whether attackers could use this flaw, or others like it, against your websites, apps and network. The full test is free for our first 10 founding clients until 31 December 2026.

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Scoring

CVSS: 10.0 (v3.1)
Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:C/C:H/I:H/A:H
Weakness: CWE-77
Assigned by: security@huntr.dev

Dates

Published: 2026-03-30
Last modified: 2026-09-04
Sources: NVD

Affected products

Lfprojects Mlflow3.8.0 - 3.8.1

As listed in the NVD configuration data. Not a statement about your estate.