CVE-2026-54232 | BDVDB-2026-342107 Detail
vllm-projectvllm
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.
Impact#
Per CVSS v3.1: confidentiality impact high, integrity impact high, availability impact high. Attack vector: network.
Weaknesses#
- CWE-427 Uncontrolled Search Path Element
References#
Exploit#
No public exploit known
History#
- Version 1Record published in the CVE List.
- Version 2Most recent update recorded in the CVE List.