Kubeflow Pipelines: Missing namespace authorization permits cross-tenant artifact reads
- Published
- Last modified
- Where the record stands: published, rejected by its publisher, or superseded by another id.What do these mean? →
- published
- Whether CISA lists it in its Known Exploited Vulnerabilities catalog: proof that attackers are using it.What do these mean? →
- Not listed in CISA KEV
- Fix
- Fixed in 2.17.0
- Whether working attack code is public (Exploit-DB, Metasploit, Nuclei or GitHub). Public code makes attacks easier.What do these mean? →
- None on Exploit-DB, Metasploit or GitHub
Summary
Kubeflow Pipelines, the machine learning workflow platform used in multi-user deployments, is affected up to the fixed release. An authenticated user can read another tenant's artifacts, such as datasets, models, and pipeline outputs, because the artifact routes do not verify namespace access.
Summarized by anthropic/claude-haiku-5.5. Verify details against the original sources.
Read the original description
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.
Timeline
- CVE published
- First seen by cve.now
Affected versions
- kubeflow pipelines
fixed in 2.17.0