7.0
HIGH CVSS 3.0
CVE-2026-4137
Incomplete Fix for CVE-2025-10279: Insecure Temporary Directory Permissions in mlflow/mlflow
Description

In mlflow/mlflow versions prior to 3.11.0, the `get_or_create_nfs_tmp_dir()` function in `mlflow/utils/file_utils.py` creates temporary directories with world-writable permissions (0o777), and the `_create_model_downloading_tmp_dir()` function in `mlflow/pyfunc/__init__.py` creates directories with group-writable permissions (0o770). These insecure permissions allow local attackers to tamper with model artifacts, such as cloudpickle-serialized Python objects, and achieve arbitrary code execution when the tampered artifacts are deserialized via `cloudpickle.load()`. This vulnerability is particularly critical in environments with shared NFS mounts, such as Databricks, where NFS is enabled by default. The issue is a continuation of the vulnerability class addressed in CVE-2025-10279, which was only partially fixed.

INFO

Published Date :

May 18, 2026, 9:16 p.m.

Last Modified :

May 18, 2026, 9:16 p.m.

Remotely Exploit :

No
Affected Products

The following products are affected by CVE-2026-4137 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.

No affected product recoded yet

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 3.0 HIGH [email protected]
Solution
Update MLflow to version 3.11.0 or later to fix insecure temporary directory permissions.
  • Update MLflow to version 3.11.0 or newer.
  • Review and tighten permissions on temporary directories.
  • Ensure NFS mount points have secure configurations.
  • Avoid deserializing untrusted Python objects.
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-2026-4137.

URL Resource
https://github.com/mlflow/mlflow/commit/1dcbb0c2fbd1f446c328830e601ca13a28219b8a
https://huntr.com/bounties/648dc30b-76c7-4433-86b8-f43d926fd8d6
CWE - Common Weakness Enumeration

While CVE identifies specific instances of vulnerabilities, CWE categorizes the common flaws or weaknesses that can lead to vulnerabilities. CVE-2026-4137 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-2026-4137 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-2026-4137 vulnerability anywhere in the article.

The following table lists the changes that have been made to the CVE-2026-4137 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]

    May. 18, 2026

    Action Type Old Value New Value
    Added Description In mlflow/mlflow versions prior to 3.11.0, the `get_or_create_nfs_tmp_dir()` function in `mlflow/utils/file_utils.py` creates temporary directories with world-writable permissions (0o777), and the `_create_model_downloading_tmp_dir()` function in `mlflow/pyfunc/__init__.py` creates directories with group-writable permissions (0o770). These insecure permissions allow local attackers to tamper with model artifacts, such as cloudpickle-serialized Python objects, and achieve arbitrary code execution when the tampered artifacts are deserialized via `cloudpickle.load()`. This vulnerability is particularly critical in environments with shared NFS mounts, such as Databricks, where NFS is enabled by default. The issue is a continuation of the vulnerability class addressed in CVE-2025-10279, which was only partially fixed.
    Added CVSS V3 AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H
    Added CWE CWE-378
    Added Reference https://github.com/mlflow/mlflow/commit/1dcbb0c2fbd1f446c328830e601ca13a28219b8a
    Added Reference https://huntr.com/bounties/648dc30b-76c7-4433-86b8-f43d926fd8d6
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.