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High · 8.8 CVE-2026-54232 EUVD-2026-38405GHSA-jrf6-vqxq-pjv2PYSEC-2026-227

vLLM: Dependency Confusion Vulnerability in vLLM Dockerfile

Published Jun 22, 2026 · Updated Jun 23, 2026 · Assigned by GitHub_M

Description

vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.22.1, the vLLM Dockerfile is vulnerable to a dependency confusion attack through the flashinfer-jit-cache package. The package is installed from a custom index (flashinfer.ai/whl/) using --extra-index-url, but the package name was not registered on PyPI, and UV_INDEX_STRATEGY="unsafe-best-match" is set globally. An attacker who registers flashinfer-jit-cache on PyPI with version 0.6.11.post2 can execute arbitrary code as root during the Docker build and backdoor every resulting container image, enabling exfiltration of all user prompts, API credentials, and model data from production vLLM deployments This vulnerability is fixed in 0.22.1.

Affected products

VendorProductAffectedFixed
vllm-project vllm < 0.22.1 —

Affected packages

EcosystemPackageAffectedFixedRecord
PyPI vllm < 0.22.1 0.22.1 PYSEC-2026-227

Advisories 1

References