mlflow-skinny@3.1.1

Affected versions of this package are vulnerable to Missing Authorization via the _before_request handler in the trace API endpoints. An authenticated attacker can bypass access controls by sending trace read, search, delete, update, linking, or assessment requests for experiments they do not have permission to access. This lets the attacker read sensitive trace data, delete audit history, and modify traces or related assessments, breaking trace access isolation for users running MLflow with authentication enabled.

Notes

• Affected deployments are specifically those with MLflow authentication enabled; without that auth layer, the experiment-level authorization checks this bug bypasses are not applied.
• The gap covers both the stable and v3 trace routes, including parameterized trace subpaths such as trace tags, info, and assessment operations, not just the top-level list/read/delete endpoints.

Upgrade mlflow-skinny to version 3.13.0rc0 or higher.

Affected versions of this package are vulnerable to Use of Weak Hash in the mlflow.data.digest_utils function. An attacker can compromise data integrity or cause unexpected behavior by exploiting the use of a weak hash algorithm during dataset digest computation.

There is no fixed version for mlflow-skinny.

Affected versions of this package are vulnerable to Insertion of Sensitive Information Into Sent Data via the api_key field in gateway secrets, which accepts environment variable references that are resolved against server-side credentials. An attacker can obtain sensitive environment credentials by configuring secrets to reference environment variables, causing these values to be sent to attacker-controlled endpoints in authentication headers.

Note:

This is only exploitable if the deployment is using basic-auth with low-privileged authenticated users or is a default deployment without basic-auth.

Upgrade mlflow-skinny to version 3.11.0rc1 or higher.

Affected versions of this package are vulnerable to Missing Authorization in the /mlflow-artifacts/mpu/* endpoints in --serve-artifacts mode. An attacker can gain unauthorized access to and overwrite artifacts belonging to other users by manipulating artifact_path and path(filename) arguments. This may result in cross-user data modification, model supply chain compromise, and arbitrary code execution when affected models are loaded.

Upgrade mlflow-skinny to version 3.10.0 or higher.

Affected versions of this package are vulnerable to Access Control Bypass via the SearchModelVersions REST API endpoint and the mlflowSearchModelVersions GraphQL query. An attacker can access sensitive information, including model names, version descriptions, source URIs, tags, and other metadata, by sending authenticated requests that bypass intended authorization checks.

Note:

This is only exploitable if basic authentication is enabled and per-model authorization is expected in a multi-tenant environment.

Upgrade mlflow-skinny to version 3.10.0 or higher.

Affected versions of this package are vulnerable to Creation of Temporary File With Insecure Permissions via the get_or_create_nfs_tmp_dir() and _create_model_downloading_tmp_dir() functions. An attacker can modify model artifacts by exploiting these permissions, potentially leading to arbitrary code execution when the tampered artifacts are deserialized. This is only exploitable if the environment uses shared NFS mounts with default configurations that allow local users to access these directories.

Note:

This issue is due to an incomplete fix for CVE-2025-10279.

Upgrade mlflow-skinny to version 3.11.0rc1 or higher.

Affected versions of this package are vulnerable to Creation of Temporary File With Insecure Permissions in the get_or_create_tmp_dir() function in file_utils.py. This enables an attacker who can write to /tmp to cause the execution of arbitrary .py files during environment setup.

Upgrade mlflow-skinny to version 3.4.0rc0 or higher.

Affected versions of this package are vulnerable to Arbitrary File Write via Archive Extraction (Zip Slip) via the extract_archive_to_dir function. An attacker can overwrite arbitrary files or gain elevated privileges by supplying a crafted tar.gz file containing malicious paths during extraction. This may allow escape from the intended sandbox directory in multi-tenant or shared cluster environments.

Upgrade mlflow-skinny to version 3.9.0rc0 or higher.

Affected versions of this package are vulnerable to Directory Traversal in the extraction process of tar archives due to improper validation of archive entry paths. An attacker can overwrite arbitrary files on the filesystem by supplying a crafted tar.gz file containing directory traversal sequences or absolute paths.

Upgrade mlflow-skinny to version 3.9.0rc0 or higher.

Affected versions of this package are vulnerable to Command Injection via the --container parameter. An attacker can execute unauthorized commands by supplying specially crafted input that is not properly sanitized.

Note:

This is only exploitable if the attacker has shell access to the system.

Upgrade mlflow-skinny to version 3.8.0rc0 or higher.

Affected versions of this package are vulnerable to Directory Traversal via the '_find_run_rootfunction in theFileStoretracking component. An attacker can access arbitrary files on the server by planting a maliciousmeta.yaml` in an artifact folder to redirect artifact URI resolution to sensitive directories.

Upgrade mlflow-skinny to version 3.8.0rc0 or higher.

Affected versions of this package are vulnerable to Use of Default Credentials in the basic_auth.ini file. An attacker can gain unauthorized administrative access and execute arbitrary code if the default admin credentials have not been changed.

Note:

The patch in version 3.13.0rc0 does not modify the default behaviour of create_app but adds a user warning to allow user change the admin password early on.

Upgrade mlflow-skinny to version 3.13.0rc0 or higher.

Affected versions of this package are vulnerable to Authentication Bypass by Primary Weakness via the _find_fastapi_validator function. An attacker can gain unauthorized access to sensitive API endpoints by sending requests to non-/gateway/ paths when the server is started with authentication enabled and served via uvicorn. This allows actions such as submitting jobs, reading job results, canceling running jobs, and injecting arbitrary trace data without authentication.

Note:

This is only exploitable if the server is started with the --app-name basic-auth flag and served via uvicorn (ASGI).

Upgrade mlflow-skinny to version 3.10.0 or higher.

Affected versions of this package are vulnerable to Directory Traversal via the _create_model_version function. An attacker can access arbitrary files on the server's filesystem by including the mlflow.prompt.is_prompt tag in a CreateModelVersion request, which bypasses source path validation and allows storage of arbitrary local filesystem paths as the model version source. The get_model_version_artifact_handler function subsequently serves files from these paths without verifying the prompt status, enabling unauthorized disclosure of sensitive information.

Upgrade mlflow-skinny to version 3.10.0 or higher.

Affected versions of this package are vulnerable to Server-side Request Forgery (SSRF) in _validate_webhook_url(), in validate.py. The _create_webhook function accepts a user-controlled url parameter without validation. An attacker can cause the backend to send HTTP requests to internal services, cloud metadata endpoints, or arbitrary external servers.

Upgrade mlflow-skinny to version 3.10.0 or higher.

Affected versions of this package are vulnerable to Cross-site Scripting (XSS) via unsafe parsing of YAML-based MLmodel artifacts in the web interface. An attacker can execute arbitrary scripts in the context of another user's browser session by uploading a crafted MLmodel file containing malicious payloads, which are triggered when the artifact is viewed in the UI. This can lead to actions such as session hijacking or performing unauthorized operations on behalf of the victim.

Upgrade mlflow-skinny to version 3.11.0rc1 or higher.

Affected versions of this package are vulnerable to Missing Authorization due to missing access-control validation in the AJAX endpoint used for downloading saved model artifacts. An attacker can gain unauthorized access to model artifacts by directly querying this endpoint without proper permissions.

Upgrade mlflow-skinny to version 3.11.0rc1 or higher.

Affected versions of this package are vulnerable to Missing Authentication for Critical Function via the FastAPI endpoints under /ajax-api/3.0/jobs/* when the basic-auth app is enabled. An attacker can gain unauthorized access to submit, read, search, and cancel jobs by sending network requests without credentials, potentially leading to remote code execution, data exposure, or denial of service.

Note:

This is only exploitable if job execution is enabled (MLFLOW_SERVER_ENABLE_JOB_EXECUTION=true) and at least one job function is allowlisted.

Upgrade mlflow-skinny to version 3.10.0 or higher.

Affected versions of this package are vulnerable to Command Injection when serving models with enable_mlserver=True due to unsanitized input being embedded into a shell command. An attacker can execute arbitrary commands by supplying specially crafted model URIs containing shell metacharacters.

Upgrade mlflow-skinny to version 3.9.0rc0 or higher.