CVE-2026-54232

CVSS 8.8 · YüksekNVD: Analyzed

Açıklama (NVD)

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.

Yayın: 23.06.2026 · Son değişiklik: 26.10.2026 · Zayıflık: CWE-427

CVSS 3.1 metrikleri

CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Saldırı vektörüAğ (uzaktan)
KarmaşıklıkDüşük
Gereken yetkiYok
Kullanıcı etkileşimiGerekli
KapsamDeğişmez
GizlilikYüksek
BütünlükYüksek
ErişilebilirlikYüksek

Hesaplanan temel puan: 8.8. CVSS hesaplayıcıda incele

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