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.
Affected products
lfprojects: mlflow
References3
- github.com/mlflow/mlflow/commit/1dcbb0c2fbd1f446c328830e601ca13… Patch
- huntr.com/bounties/648dc30b-76c7-4433-86b8-f43d926fd8d6 ExploitThird Party Advisory
- huntr.com/bounties/648dc30b-76c7-4433-86b8-f43d926fd8d6 ExploitThird Party Advisory
Metrics
- CVSS 3.1
-
7.8
HIGH
Score source: NVD
CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:H/I:H/A:H - EPSS — exploit probability
- 0% percentile: 9 · as of 14 November 2026
- CWE
- CWE-378
Could this be exploited in your environment?
A patch closes the known hole. A penetration test shows what an attacker can still reach — with proof.