CVE-2026-4137: lfprojects mlflow
Vulnerability summary
CVE-2026-4137 is a high (CVSS 7.8) vulnerability in lfprojects mlflow. EPSS estimates a 0.16% chance of exploitation in the next 30 days, higher than 5% of scored vulnerabilities. 1 public exploit is recorded.
Timeline
- 18-05-2026PublishedVulnerability first disclosed.
- 19-05-2026Last modifiedVulnerability information updated.
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.
CVSS metrics
4 scores · 3 sources · 2 versions- OSV · PypiEcosystem advisory · calculated7.0HighCVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H
- NVDNIST7.0HighCVSS:3.0/AV:L/AC:H/PR:L/UI:N/S:U/C:H/I:H/A:H
EPSS trend
Probability
0.16%
Chance of exploitation in the next 30 days
Percentile
5%
Versus all other CVEs
30-day change
-0.03 pp
From 0.19% on 20-09-2026
Known exploited
Compare KEV catalogsNot in any of the 3 tracked catalogs.
Public exploits
1 foundExploit Reference (huntr.com)
Maturity: unknown
Weaknesses
CWE · root causeAffected systems
Chainguard1 product
- mlflow< 3.16.0-r0
Lfprojects1 product
- mlflow< 3.11.0
Mlflow1 product
- mlflow/mlflow≥ unspecified, < 3.11.0
PyPI1 product
- mlflow≥ 1.26.0, < 3.11.0 | < 3.11.0
Wolfi1 product
- mlflow< 3.16.0-r0
5 vendors · 5 products
References
9 links- github.com/mlflow/mlflowPACKAGE
- pypi.org/project/mlflowPACKAGE