CVE-2023-37264
Linuxfoundation Tekton Pipelines ≥ 0.35.0
Raw vector
CVSS:3.1/AV:N/AC:H/PR:L/UI:R/S:U/C:L/I:L/A:NSummary
CVE-2023-37264 is a low-severity Insufficient Verification of Data Authenticity (CWE-345) vulnerability in Linuxfoundation Tekton Pipelines. Its CVSS base score is 3.7 (Low).
Operationally, ranked at the 30th percentile by exploit likelihood (below the median); it is not currently listed in the CISA KEV catalog; a public proof-of-concept is referenced.
OWASP Top 10 for Web (2025)
EU & UK References
- 🇪🇺 ENISA EUVD: EUVD-2023-2156
Vulnerability Data
Tekton Pipelines project provides k8s-style resources for declaring CI/CD-style pipelines. Starting in version 0.35.0, pipelines do not validate child UIDs, which means that a user that has access to create TaskRuns can create their own Tasks that the Pipelines controller…
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will accept as the child Task. While the software stores and validates the PipelineRun's (api version, kind, name, uid) in the child Run's OwnerReference, it only store (api version, kind, name) in the ChildStatusReference. This means that if a client had access to create TaskRuns on a cluster, they could create a child TaskRun for a pipeline with the same name + owner reference, and the Pipeline controller picks it up as if it was the original TaskRun. This is problematic since it can let users modify the config of Pipelines at runtime, which violates SLSA L2 Service Generated / Non-falsifiable requirements. This issue can be used to trick the Pipeline controller into associating unrelated Runs to the Pipeline, feeding its data through the rest of the Pipeline. This requires access to create TaskRuns, so impact may vary depending on one Tekton setup. If users already have unrestricted access to create any Task/PipelineRun, this does not grant any additional capabilities. As of time of publication, there are no known patches for this issue.
- CWE(s)
Related Threats
CVEs Like This One
Affected Assets
Mitigating Controls
Control response
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- 8 hardening rules · 5 OS baselines
V3.5.5
Likely Mitigating Controls AI
Per-CVE control mapping for this CVE has not run yet; the list below is derived from the weakness types (CWEs) cited in the NVD entry.
Directly requires independent verification of matching output before adverse decisions, mitigating insufficient authenticity checks on data from external sources.
Use of approved PKI certificates provides verifiable data authenticity and origin for communications and artifacts.
Mandates provision of authenticity and integrity artifacts that enable verification of name/address resolution data.
Requires explicit verification of data authenticity from authoritative sources, preventing acceptance of unauthenticated resolution responses.
Control requires verification of data authenticity/integrity (e.g., checksums) after aggregation/packing, directly reducing exploitation of insufficient verification before transmission.
Time synchronization supports reliable freshness verification when checking data authenticity across systems or components.
Mandates verification of data authenticity for software, firmware, and information.
Provenance documentation and monitoring directly enables verification of authenticity for components and data throughout their history.
Mitigating Controls (NIST CSF 2.0) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→CSF cross-walk (authority under review) — links open the control.
CWE-345 directly impairs RC.RP-05's verification of restored-asset integrity/authenticity, largely defeating the outcome while still leaving other restoration-confirmation steps partially viable.
Mitigating Controls (ISO/IEC 27001:2022 Annex A) AI
Derived directly from the weakness types (CWEs) cited in the NVD entry via our AI-authored CWE→ISO cross-walk (authority under review) — links open the control.
Security testing can detect missing or weak data authenticity verification.
Network controls can enforce authenticated channels, reducing risk of accepting unauthentic data.
Secure network services often include authenticity checks for data exchanged over those services.
Cryptographic mechanisms directly verify data origin and integrity, preventing acceptance of unauthentic data.
Secure SDLC incorporates authenticity verification requirements throughout development.
Application security requirements can mandate data authenticity verification mechanisms.