Safety vulnerability ID: 71586
The information on this page was manually curated by our Cybersecurity Intelligence Team.
A broken access control vulnerability exists in mlflow/mlflow affected versions, where low privilege users with only EDIT permissions on an experiment can delete any artifacts. This issue arises due to the lack of proper validation for DELETE requests by users with EDIT permissions, allowing them to perform unauthorized deletions of artifacts. The vulnerability specifically affects the handling of artifact deletions within the application, as demonstrated by the ability of a low privilege user to delete a directory inside an artifact using a DELETE request, despite the official documentation stating that users with EDIT permission can only read and update artifacts, not delete them.
Latest version: 2.19.0
MLflow is an open source platform for the complete machine learning lifecycle
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