MLflow before 3.18.0 using the FileStore backend contains a path traversal vulnerability that allows unauthenticated remote attackers to write files outside the intended run directory by supplying a malicious model_id parameter to the log outputs API. Attackers can exploit the unvalidated model_id containing ../ sequences via the POST /api/3.0/mlflow/runs/outputs endpoint to create directories and write a meta.yaml file at arbitrary filesystem locations, limited only by the server account's permissions. FileStore was the default backend before 3.7.0 and is opt-in afterward through MLFLOW_ALLOW_FILE_STORE.
Attack Parameters
Attack Vector
Network
Can be exploited remotely
Attack Complexity
Low
Easy to exploit
Attack Requirements
Present
Additional conditions required
Privileges Required
None
No privileges needed
User Interaction
None
No user interaction needed
Impact Assessment
Confidentiality
None
No data leak
Integrity
Low
Partial data modification
Availability
None
No disruption
CVSS Vector v4.0
Weakness Type (CWE)
References 4
https://github.com/mlflow/mlflow/commit/ab5fc795eedc22348253cf687818cf2a16c15282
disclosure@vulncheck.com
https://github.com/mlflow/mlflow/pull/27131
disclosure@vulncheck.com
https://github.com/mlflow/mlflow/releases/tag/v3.18.0
disclosure@vulncheck.com
https://www.vulncheck.com/advisories/mlflow-path-traversal-via-model-id-in-log-…
disclosure@vulncheck.com