vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.0, vLLM's revision pinning controls do not consistently apply to all artifacts loaded for a model. A deployment that supplies --revision or --code-revision can still load dynamic code, GGUF files, image processors, retrieval side weights, or same-repository subfolder weights/config from an unpinned/default revision. This is a supply-chain integrity issue for pinned vLLM deployments. Operators can believe they are serving a reviewed model revision while vLLM resolves behavior-affecting nested or sibling artifacts outside that reviewed revision. This vulnerability is fixed in 0.22.0.
References
| Link | Resource |
|---|---|
| https://github.com/vllm-project/vllm/commit/d26a28ab033697f55a1414b5b0435de7cd6045b6 | Patch |
| https://github.com/vllm-project/vllm/pull/42616 | Issue Tracking |
| https://github.com/vllm-project/vllm/security/advisories/GHSA-3ww4-5jv9-j5gm | Third Party Advisory |
| https://huntr.com/bounties/3f1e24c0-87d2-4f6c-a705-820f380879ac | Third Party Advisory |
Configurations
History
No history.
Information
Published : 2026-06-22 23:16
Updated : 2026-06-24 16:49
NVD link : CVE-2026-47155
Mitre link : CVE-2026-47155
CVE.ORG link : CVE-2026-47155
JSON object : View
Products Affected
vllm
- vllm
CWE
CWE-345
Insufficient Verification of Data Authenticity
