Vulnerability details

CVE-2026-54232

vllm-project vLLM

vLLM: Dependency Confusion Vulnerability in vLLM Dockerfile

CVSS 3.1
8.8High

Official 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.

CVSS scores

ScoreVersionSourceVector
8.8High 3.1 CVEProject cvelistV5 (CNA) (GitHub_M) CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Affected products

VendorProductVersionsSource
vllm-project vLLM < 0.22.1 CVEProject cvelistV5 (CNA)

References and advisories

1
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Details

Published
2026-06-23
Last updated
2026-06-23
State
Published
Assigner (CNA)
GitHub_M

Exploit prediction (EPSS)

0.56%
Probability of exploitation in 30 days
46.9%
Percentile (among all CVEs)

SSVC assessment (CISA)

Automatable
No
Exploitation
None
Technical impact
Total

Weaknesses (CWE)

  • CWE-427
    Uncontrolled Search Path Element