vLLM: Dependency Confusion Vulnerability in vLLM Dockerfile
21Vexday Risk Score
Sin señal de explotación. Ningún artefacto público de explotación conocido hasta ahora.
ssvc Trackcvss 8.8epss 0.6%
probabilidad de explotación
0.6%top 56% de las CVE
explotación observada
noninguna fuente lo reporta
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.
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
Productos afectados
vllm-project · vllm