MLflow: Unauthenticated access to certain FastAPI routes
MLflow
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- Severity
- High, CVSS 8.6
- CVSS vector
- CVSS:3.0/AV:N/AC:L/PR:N/UI:N/S:U/C:L/I:H/A:L
- Record
- CVE-2026-2652
- Affects
- MLflow
- Known exploited
- Not listed in the CISA Known Exploited Vulnerabilities catalog
- Published
- Record first published by the source
- May 15, 2026
- Source last modified
- June 17, 2026
Description
A vulnerability in mlflow/mlflow versions 3.9.0 and earlier allows unauthenticated access to certain FastAPI routes when the server is started with authentication enabled (--app-name basic-auth) and served via uvicorn (ASGI). The FastAPI permission middleware only enforces authentication on /gateway/ routes, leaving other routes such as the Job API (/ajax-api/3.0/jobs/*) and the OpenTelemetry trace ingestion API (/v1/traces) unprotected. This allows unauthenticated remote attackers to submit jobs, read job results, cancel running jobs, and inject arbitrary trace data into experiments. The issue arises from an architectural mismatch between Flask and FastAPI authentication mechanisms, where the _find_fastapi_validator() function fails to handle non-/gateway/ paths, resulting in a complete authentication bypass. This vulnerability is fixed in version 3.10.0.
Description quoted from the NVD record.
Who is affected
MLflow, made by LF Projects, is a platform for tracking and managing machine learning work and models. This flaw affects versions 3.9.0 and earlier when the MLflow server has its built-in password login turned on and runs on the uvicorn web server. In that setup, the login protects only one part of the product. Other features stay open, such as the feature that runs jobs and the feature that collects tracing data about experiments. Anyone who can reach the server could submit jobs, read job results, cancel running jobs and add false tracing data to experiments, all without logging in. This flaw is rated High.
What to do
- The person who installed or runs MLflow for your organization should check which version is in use, and whether its built-in password login is turned on with the uvicorn web server.
- Update MLflow to version
3.10.0or later, which fixes this flaw. Do this for any installation running version 3.9.0 or earlier. - If an IT provider or vendor runs MLflow for your organization, send them this advisory and ask when the update will be done.
- Check the vendor advisory linked on this page for any further details about the fix.
Analysis written from the source record as of June 17, 2026 and reviewed before publishing.