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.
| Vendor | Product | Version(s) | CPE |
|---|---|---|---|
< 0.22.1CPE matchmatch criteria | cpe:2.3:a:vllm:vllm:*:*:*:*:*:*:*:* |
CVSS version used by this source: 3.1
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
The average CVE in this peer group has 0.0 Twitter, 0.1 Reddit, 0.2 Bluesky, 0.1 Mastodon, and 0.2 GitHub mentions.
No media coverage found for this CVE.
The average CVE in this peer group has 0.3 InfoSec Media, 0.0 Vendor Blog, and 0.1 Security Researcher mentions.
Remediation records are not available for this CVE.