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Vulnerability Intelligence Report
vLLM: Dependency Confusion Vulnerability in vLLM Dockerfile

CVE-2026-54232

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.

No Active Exploit Signals
CVSS Base Score
8.8
HIGH
Exploitability:2.9
Impact Score:5.9
EPSS Probability:0.29%
Executive Threat Verdict
Evaluating...
Evaluating Threat Landscape...
Assessing known weaponization, exploitation telemetry, and federal advisories.
Attack Surface
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Authentication
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Weaponization
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SSVC Action
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Weaknesses (CWE)

CWE-427 ↗CWE-427: Uncontrolled Search Path Element

Affected Products & Versions

Vendor Product Affected Versions
vllm-project vllm < 0.22.1 (affected)

References & Technical Advisories

No reference links found.

Threat Intelligence Signals

EPSS Score
0.288%

Identity & Timeline

StatusPUBLISHED
Assigning AuthorityGitHub, Inc. · Vendor · USA
Reserved2026-06-12T16:25:43
Published2026-06-22T22:16:43
Last Updated2026-06-23T14:30:04

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