CVE-2026-88981 · Runtime
NO FIX YET · SEE WHAT TO DO
Kubeflow Pipelines before 2.18.0 lets an unauthenticated caller in the standalone, authorization-disabled setup make the shared ml-pipeline-ui pod connect to any reachable host and return the response data. Requests can also reveal an object-store access-key identifier when signed with the configured credentials.
first public Oct 28, 2026 · 1 source
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Teams running Kubeflow Pipelines before 2.18.0 in the standalone configuration with authorization disabled are exposed, because the shared ml-pipeline-ui pod can be made to fetch arbitrary endpoints. Multi-user deployments are stated to keep secret-backed metadata restricted to the server namespace, and deployments with authorization enabled are not described as exposed.
Not affected if authorization-enabled, multi-user-mode, version-2.18.0-or-later
Who cares kubeflow-pipelines, kubernetes, ml-platform, self-hosted
2.18.0 is affected.2.18.0.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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