CVE-2026-47155
Medium · 6.5CVSS
6.5
EPSS
0.2%
Published
Jun 22, 2026
CISA due date
—
The record
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.
Affected packages
| Ecosystem | Package | Introduced | Fixed |
|---|
Related vulnerabilities
- CVE-2026-102682 Pipecat is an open-source Python framework for building real-time voice and multimodal… CWE-345
- CVE-2026-104850 MCP TypeScript SDK is the official TypeScript SDK for Model Context Protocol servers and… CWE-345
- CVE-2026-102275 PyJWT is a Python implementation of JSON Web Token standards. CWE-345
- CVE-2026-102267 PyJWT is a Python implementation of JSON Web Token standards. CWE-345
- CVE-2026-19941 An inapplicable NSEC record may be accepted by a `named` resolver as proof that no… CWE-345
- CVE-2026-77955 In NLnet Labs Unbound 1.13.2 up to and including 1.26.1, a vulnerability in ZONEMD… CWE-345
- CVE-2026-89251 AVideo through commit c3edcc274c389816d434acadac07ee78eaf330c1 fails to validate ad… CWE-345
- CVE-2026-86809 The Persian Elementor WordPress plugin from 2.7.10 before 2.8.2 does not verify that the… CWE-345