Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows

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 isAllowedResourceName permits an all-digit decimal host that the URL parser converts to an IPv4 address. The default ALLOWED_ARTIFACT_DOMAIN_REGEX and authorization-disabled standalone configuration allow an unauthenticated caller to fetch internal HTTP resources and receive their response body. In the authenticated multi-user configuration, the same destination-validation defect is reachable by a low-privilege tenant with a valid identity and authorized namespace. Cloud credential disclosure depends on reachable metadata services and attached roles, and the issue does not establish IMDSv2 bypass or credential access when metadata is blocked. This issue is fixed in version 2.18.0.