CVEPublished 2026-06-22Modified 2026-06-241 article on news4 live referencesNVD data

CVE-2026-54232Vllm · Vllm

Vulnerability data via NVD (ingested)

CVSS v3.1
8.8
HIGH
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
EPSS percentile
20
Exploit Prediction Scoring System · top 80% of all CVEs
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.

Timeline
Published 2026-06-22
Modified 2026-06-24

External references

Search for exposed instances

Shodan + Censys queries derived from NVD's CPE data. The vuln tag catches assets Shodan has explicitly linked to this CVE; the product / banner fingerprints find exposed instances even when the vuln tag was never applied (which is common).

More intel sources (5)

Known PoCs on GitHub

No public proof-of-concept repositories found for CVE-2026-54232 on GitHub.