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High 8.6
Kubeflow Pipelines: Unauthenticated SSRF through artifact provider endpoints
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 …
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High 8.6
Kubeflow Pipelines: Unauthenticated server-side request forgery in the frontend http/https artifact source via decimal-IP bypass of the bucket validator
Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows. Prior to 2.18.0, the frontend GET /artifacts/get route accepts source=http or source=https with caller-controlled bucket and key values, and isAllowedResourceN…
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High 7.2
Kubeflow Pipelines: RBAC bypass on shared pipelines allows any authenticated user to delete or modify global pipelines
Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows. Prior to 2.16.1, the multi-user API server treats the empty namespace used by shared or global pipelines as an authorization exception for modification and del…
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High 7.5
Kubeflow Pipelines: Pipeline archive upload allows decompression bomb to exhaust server memory
Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows. Prior to 2.18.0, the API server decompressed uploaded pipeline archives without adequately bounding expanded data while locating or reading the pipeline file. …
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High 7.5
Kubeflow Pipelines: Run log streaming endpoint bypasses namespace authorization, exposing pod execution logs cross-tenant
Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows. Prior to 2.18.0, the API server's GET /apis/v1alpha1/runs/{run_id}/nodes/{node_id}/log handler retrieved logs without authorizing the caller against the select…
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High 7.5
Kubeflow: Unauthenticated path traversal to arbitrary file read on ml-pipeline-ui via the volume artifact source
Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows. Prior to 2.18.0, the volume artifact handler for GET /artifacts/get?source=volume did not confine a caller-supplied file path to the selected volume. A caller …