| Component | vLLM |
| Severity | high (CVSS 8.8) |
| CVSS vector | CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H |
| Published (NVD) | 2026-06-22 |
| Last modified | 2026-06-24 |
| Affected versions | vllm < 0.22.1 |
| Fixed in | 0.22.1 |
| Weakness | CWE-427 |
| CISA KEV | not listed |
NVD 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.
What to do
- Upgrade vLLM to
0.22.1or later. - Do not expose the component's API or UI to the internet without authentication in front of it.
Sources
Read more
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