Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows. Prior to 2.18.0, the frontend artifact download path for source=s3 or source=minio accepts providerInfo.Params.endpoint, and the archived pod-log path accepts S3-compatible endpoint metadata from workflow status, without requiring those endpoints to match operator-controlled storage configuration. In the shipped authorization-disabled standalone configuration, an unauthenticated caller can make the shared ml-pipeline-ui pod connect to arbitrary reachable hosts and return response data; requests may also reveal an access-key identifier when signed with configured object-store credentials. Multi-user secret-backed metadata remains restricted to the server namespace. This issue is fixed in version 2.18.0.
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