9.8
CRITICAL CVSS 3.1
CVE-2026-116692
MLflow: Remote code execution on unauthenticated MLflow servers via third-party scorer deserialization importing caller-placed artifact modules
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.

INFO

Published Date :

Oct. 27, 2026, 9:18 p.m.

Last Modified :

Oct. 27, 2026, 9:18 p.m.

Remotely Exploit :

Yes !
Affected Products

The following products are affected by CVE-2026-116692 vulnerability. Even if cvefeed.io is aware of the exact versions of the products that are affected, the information is not represented in the table below.

ID Vendor Product Action
1 Lfprojects mlflow
CVSS Scores
The Common Vulnerability Scoring System is a standardized framework for assessing the severity of vulnerabilities in software and systems. We collect and displays CVSS scores from various sources for each CVE.
Score Version Severity Vector Exploitability Score Impact Score Source
CVSS 3.1 CRITICAL MITRE-CVE
CVSS 3.1 CRITICAL [email protected]
Solution
Update MLflow to version 3.17.0 or later to address the third-party scorer deserialization vulnerability.
  • Update MLflow to version 3.17.0 or later.
  • Ensure MLflow artifact endpoints are not publicly writable.
  • Restrict write access to the allowed scorer package.
References to Advisories, Solutions, and Tools

Here, you will find a curated list of external links that provide in-depth information, practical solutions, and valuable tools related to CVE-2026-116692.

URL Resource
https://github.com/mlflow/mlflow/commit/a732443e695c3c677680c54320efc394c81654ab
https://github.com/mlflow/mlflow/pull/25906
https://github.com/mlflow/mlflow/releases/tag/v3.17.0
https://github.com/mlflow/mlflow/security/advisories/GHSA-26p8-2jq9-3vq9
CWE - Common Weakness Enumeration

While CVE identifies specific instances of vulnerabilities, CWE categorizes the common flaws or weaknesses that can lead to vulnerabilities. CVE-2026-116692 is associated with the following CWEs:

Common Attack Pattern Enumeration and Classification (CAPEC)

Common Attack Pattern Enumeration and Classification (CAPEC) stores attack patterns, which are descriptions of the common attributes and approaches employed by adversaries to exploit the CVE-2026-116692 weaknesses.

We scan GitHub repositories to detect new proof-of-concept exploits. Following list is a collection of public exploits and proof-of-concepts, which have been published on GitHub (sorted by the most recently updated).

Results are limited to the first 15 repositories due to potential performance issues.

The following list is the news that have been mention CVE-2026-116692 vulnerability anywhere in the article.

The following table lists the changes that have been made to the CVE-2026-116692 vulnerability over time.

Vulnerability history details can be useful for understanding the evolution of a vulnerability, and for identifying the most recent changes that may impact the vulnerability's severity, exploitability, or other characteristics.

  • New CVE Received by [email protected]

    Oct. 27, 2026

    Action Type Old Value New Value
    Added 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.
    Added CVSS V3.1 AV:N/AC:L/PR:N/UI:N/S:U/C:H/I:H/A:H
    Added CWE CWE-94
    Added CWE CWE-470
    Added Affected New affected value received. <a href="https://github.com/CVEProject/cvelistV5/blob/main/cves/2026/116xxx/CVE-2026-116692.json">CVE-2026-116692</a>
    Added Reference https://github.com/mlflow/mlflow/commit/a732443e695c3c677680c54320efc394c81654ab
    Added Reference https://github.com/mlflow/mlflow/pull/25906
    Added Reference https://github.com/mlflow/mlflow/releases/tag/v3.17.0
    Added Reference https://github.com/mlflow/mlflow/security/advisories/GHSA-26p8-2jq9-3vq9
EPSS is a daily estimate of the probability of exploitation activity being observed over the next 30 days. Following chart shows the EPSS score history of the vulnerability.