Vulnerability · Published Oct 27, 2026 · Assigned by GitHub_M

CVE-2026-116692MLflow: Remote code execution on unauthenticated MLflow servers via third-party scorer deserialization importing caller-placed artifact modules

Critical 9.8

In plain English

A critical-severity code injection in mlflow from mlflow. Proof-of-concept exploit code is public. The chance it is exploited in the next 30 days is estimated at 0.7% (higher than 53% of all known vulnerabilities). Ready-made attack tooling exists: public proof-of-concept code. Fixed versions are available - upgrade the affected package.

Severity (CVSS 3.1)9.8Critical
Exploit odds (30 days)0.7%top 46.5% of all CVEs
Exploited in the wildNo reportsCISA SSVC: poc
Attack tooling1Public PoC

Official description

MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.12.0rc0 until 3.17.0, third-party scorer deserialization in mlflow/genai/scorers/base.py accepts request-selected descendants of THIRD_PARTY_SCORER_ALLOWED_MODULES rather than requiring an exact allowed module. A caller can use MLflow artifact endpoints to place a Python module beneath a writable allowed package and submit its module and class through /ajax-api/3.0/mlflow/scorer/invoke. Scorer.model_validate_json() imports the module and constructs the class before trace processing. Authentication-disabled deployments permit this code execution without credentials, while basic-auth deployments require a principal capable of creating an experiment and run and uploading artifacts. In either configuration, the allowed scorer package must be writable by the server process. This issue is fixed in version 3.17.0.

Affected packages & fixed versions

EcosystemPackageFixed inAdvisory
PyPImlflow3.17.0GHSA-26p8-2jq9-3vq9

Affected products (as reported)

VendorProductVersions
mlflow mlflow >= 3.12.0rc0, < 3.17.0

Weakness: CWE-94, CWE-470 · Vector: CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H

References