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Search Results (6 CVEs found)
| CVE | Vendors | Products | Updated | CVSS v3.1 |
|---|---|---|---|---|
| CVE-2026-118761 | 1 Kubeflow | 1 Pipelines | 2026-10-29 | 7.5 High |
| 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 small ZIP or gzip-compressed tar archive can consume disproportionately large memory and exhaust API-server resources. Multipart pipeline and pipeline-version upload processing performs decompression before namespace authorization, so a reachable caller does not need a successful pipeline-create authorization decision. URL-import handlers authorize before fetching and decompressing a remote archive. The amount of expansion required to interrupt service depends on deployment resource limits and concurrent activity, and no specific archive is guaranteed to crash every deployment. This issue is fixed in version 2.18.0. | ||||
| CVE-2026-118758 | 1 Kubeflow | 1 Pipelines | 2026-10-29 | 7.5 High |
| 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 who can reach the route and identify an existing mounted volume can use path traversal to read files outside that volume when the artifact-serving process can read them. The frontend pod serves the request when artifact proxying is disabled, while the selected namespace's artifact-service pod serves it when proxying is enabled. A deployment with authentication disabled requires no application credentials; in multi-user deployments, the caller ordinarily must be authorized for the supplied namespace. This issue is fixed in version 2.18.0. | ||||
| CVE-2026-118759 | 1 Kubeflow | 1 Pipelines | 2026-10-29 | 7.5 High |
| 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 selected run. A caller who can reach the backend and knows a victim run ID and suitable pod or node identifier can read live or archived logs with the API server's permissions. For live logs, the caller-controlled node ID was also accepted as a pod name without verifying that the pod belonged to the requested run, allowing a known run ID to select the namespace of an unrelated pod and read its main container logs. The handler does not authenticate requests itself, although an external authentication gate or network policy can limit reachability. Exposed logs can contain sensitive workload data or credentials. This issue is fixed in version 2.18.0. | ||||
| CVE-2026-118760 | 1 Kubeflow | 1 Pipelines | 2026-10-29 | 6.5 Medium |
| Kubeflow Pipelines enables users to build and deploy portable, scalable machine learning workflows. From 0.5.1 until 2.17.0, the frontend artifact routes did not check whether an authenticated user was authorized to access the requested namespace. A user who can reach the frontend and knows an artifact location can select another tenant's namespace, or omit the namespace and reach an unguarded direct handler, to read artifact contents such as datasets, models, or pipeline outputs. The issue applies to multi-user deployments that rely on Kubeflow Pipelines authorization for tenant isolation. Authentication at ingress identifies the caller but does not authorize access to the selected artifact namespace. The issue does not establish arbitrary Kubernetes Secret disclosure, storage modification, or server-side code execution. This issue is fixed in version 2.17.0. | ||||
| CVE-2026-54745 | 1 Kubeflow | 1 Pipelines | 2026-08-31 | 10 Critical |
| 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/server/proxy-middleware.ts. The _routePathWithReferer() function accepts an arbitrary attacker-controlled HTTP or HTTPS target and passes its origin to createProxyMiddleware without a host allowlist or filtering for loopback, link-local, RFC1918, or cluster-local addresses. The route remains outside the authorization middleware when ENABLE_AUTHZ=true and is reachable through /apis/v1beta1/_proxy/, /apis/v2beta1/_proxy/, /pipeline/apis/v1beta1/_proxy/, and /pipeline/apis/v2beta1/_proxy/, including through a crafted Referer header. Requests can forward attacker-controlled methods, headers such as Authorization, Cookie, and X-Forwarded-For, and POST bodies to reachable internal services, while returning the upstream response to the unauthenticated client. This can expose cloud metadata credentials, Kubernetes or service APIs, and other cluster-internal endpoints to unauthorized read or modification. This issue is fixed in version 2.17.0. | ||||
| CVE-2024-9526 | 1 Kubeflow | 2 Kubeflow W Pipeline View, Pipelines | 2025-07-23 | 5.4 Medium |
| There exists a stored XSS Vulnerability in Kubeflow Pipeline View web UI. The Kubeflow Web UI allows to create new pipelines. When creating a new pipeline, it is possible to add a description. The description field allows html tags, which are not filtered properly. Leading to a stored XSS. We recommend upgrading past commit 930c35f1c543998e60e8d648ce93185c9b5dbe8d | ||||
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