Kubeflow vulnerabilities
We track 11 vulnerabilities in Kubeflow products across 5 products. 11 are rated high or critical, and none are known to be exploited. The most recent was published on November 5, 2026.
Latest Kubeflow vulnerabilities
- 7.2 High severity
pipelines: Improper Authorization
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 dele
- 8.6 High severity
pipelines: Server-Side Request Forgery
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 S
- 8.6 High severity
pipelines: Server-Side Request Forgery
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 isAllowedResourceNa
- 9.6 Critical severity
pipelines: Authorization Bypass Through User-Controlled Key
Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows. Prior to 2.18.0, the multi-user HTTP endpoints POST /apis/v2beta1/pipelines/upload and POST /apis/v2beta1/pipelines/upload_version call canUploadVersionedPipeli
- 7.5 High severity
pipelines: Improper Handling of Highly Compressed Data (Data Amplification)
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. A
- 7.5 High severity
pipelines: Exposure of Sensitive Information to an Unauthorized Actor
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 selecte
- 7.5 High severity
pipelines: Improper Limitation of a Pathname to a Restricted Directory
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 w
- 7.1 High severity
Model Registry: Server-Side Request Forgery
Kubeflow Model Registry through 0.3.17 contains a server-side request forgery vulnerability that allows namespace users to steal the controller ServiceAccount token via the modelregistry.kubeflow.org/url annotation. Attackers can create an InferenceService poi
- 10.0 Critical severity
pipelines: Improper Access Control
Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows. Prior to 2.17.0, the Kubeflow Pipelines frontend exposes an unauthenticated server-side request forgery vulnerability through the /_proxy/ route in frontend/ser
- 8.0 High severity
community-distribution: Incorrect Privilege Assignment
Kubeflow Community Distribution helps users to install Kubeflow Platform in popular Kubernetes clusters. Prior to version 26.03-rc.1, a Kubeflow setup based on the official manifests or most other packaged Kubeflow distributions is vulnerable to authorization
- 7.5 High severity
kubeflow/kubeflow: Inefficient Regular Expression Complexity
kubeflow/kubeflow is vulnerable to a Regular Expression Denial of Service (ReDoS) attack due to inefficient regular expression complexity in its email validation mechanism. An attacker can remotely exploit this vulnerability without authentication by providing