MLflow vulnerable to arbitrary file read on unauthenticated servers via prompt model version source
High-risk advisory
CVE-2026-116690
Summary
MLflow vulnerable to arbitrary file read on unauthenticated servers via prompt model version source
Why it matters
GitHub has published a reviewed security advisory for mlflow. Prioritize it with other application dependency updates, especially because EPSS places it in the 46% percentile.
Operator check
Check whether mlflow is present in application dependency manifests, lockfiles, or build images. Review the GitHub advisory and upgrade to a patched version where available. EPSS probability: 0.6%; percentile: 46%.
Sources
PatchBrief uses public sources. It does not scan environments, verify exposure, or replace vendor guidance.