| Component | MLflow |
| Severity | high (CVSS 7.1) |
| CVSS vector | CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:L/A:N |
| Published (NVD) | 2026-08-17 |
| Last modified | 2026-09-18 |
| Affected versions | < 3.15.0 read from the advisory text: NVD has not published CPE data yet |
| Fixed in | 3.15.0 |
| Weakness | CWE-862 |
| CISA KEV | not listed |
NVD description
MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Prior to 3.15.0, CreateModelVersion accepts a run_id or model_id after _validate_source_run() or _validate_source_model() in mlflow/server/handlers.py verifies only path containment, allowing authenticated users to create a model version that references another user's artifact directory and read files through GET /model-versions/get-artifact without the required READ permission. This issue is fixed in version 3.15.0.
What to do
- Upgrade MLflow to
3.15.0or later. - Do not expose the component's API or UI to the internet without authentication in front of it.
Sources
- NVD: CVE-2026-69148
- https://github.com/mlflow/mlflow/commit/4bb7474771c3be808cd9e129defef9305f2869be
- https://github.com/mlflow/mlflow/pull/24293
- https://github.com/mlflow/mlflow/releases/tag/v3.15.0
- https://github.com/mlflow/mlflow/security/advisories/GHSA-gqch-g4w5-7qcw
Read more
Other MLflow CVEs
MLflow's dspy flavor, versions >= 2.0, applies the MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False security control only when the model_path ends...
MLflow's statsmodel flavor, versions 2.1.0 to 3.14.0, omits the MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False security control entirely in _load...
Code execution can occur in versions of the MLflow platform running version 0.0.1 or newer, enabling a maliciously crafted model artifact to...
MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. From 3.13.0 until 3.15.0, L...
MLflow is an open source AI engineering platform for agents, large language models, and machine learning models. Starting in 3.3.0 and prior...
MLflow's AI Gateway accepts an auth_config.api_base value when creating a gateway secret (mlflow/server/handlers.py, _create_gateway_secret)...