Bug 2491585 (CVE-2026-54232)

Summary: CVE-2026-54232 vllm: flashinfer-jit-cache: vLLM: Arbitrary code execution via dependency confusion during Docker build
Product: [Other] Security Response Reporter: OSIDB Bzimport <bzimport>
Component: vulnerabilityAssignee: Product Security <prodsec-ir-bot>
Status: NEW --- QA Contact:
Severity: medium Docs Contact:
Priority: medium    
Version: unspecifiedCC: alinfoot, bbrownin, dtrifiro, jkoehler, lphiri, rbryant, weaton
Target Milestone: ---Keywords: Security
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Hardware: All   
OS: Linux   
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A flaw was found in vLLM, an inference and serving engine for large language models (LLMs). This vulnerability, a dependency confusion attack, allows a remote attacker to execute arbitrary code with root privileges during the Docker build process. By exploiting this, an attacker can compromise the resulting container image, leading to the exfiltration of sensitive information like user prompts, API credentials, and model data from production vLLM deployments.
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Description OSIDB Bzimport 2026-06-22 23:01:32 UTC 
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.