Insufficient Verification of Data Authenticity Affecting vllm-wheels package, versions *


Severity

Recommended
low

Based on default assessment until relevant scores are available.

Threat Intelligence

EPSS
0.15% (5th percentile)

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  • Snyk IDSNYK-MINIMOSLATEST-VLLMWHEELS-17314172
  • published12 Jun 2026
  • disclosed22 Jun 2026

Introduced: 12 Jun 2026

CVE-2026-47155  (opens in a new tab)
CWE-345  (opens in a new tab)

How to fix?

There is no fixed version for Minimos:latest vllm-wheels.

NVD Description

Note: Versions mentioned in the description apply only to the upstream vllm-wheels package and not the vllm-wheels package as distributed by Minimos. See How to fix? for Minimos:latest relevant fixed versions and status.

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.