Vulnerability details

CVE-2026-22807

Red Hat AI Inference ServerRed Hat Enterprise Linux AI 3vllm-project vLLM

vLLM affected by RCE via auto_map dynamic module loading during model initialization

CVSS 3.1
8.8High

Official description

vLLM is an inference and serving engine for large language models (LLMs). Starting in version 0.10.1 and prior to version 0.14.0, vLLM loads Hugging Face `auto_map` dynamic modules during model resolution without gating on `trust_remote_code`, allowing attacker-controlled Python code in a model repo/path to execute at server startup. An attacker who can influence the model repo/path (local directory or remote Hugging Face repo) can achieve arbitrary code execution on the vLLM host during model load. This happens before any request handling and does not require API access. Version 0.14.0 fixes the issue.

CVSS scores

ScoreVersionSourceVector
8.8High 3.1 CVEProject cvelistV5 (CNA) (GitHub_M) CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H
8.8High 3.1 CVEProject cvelistV5 (CNA) (redhat-SADP) CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:H/I:H/A:H

Affected products

VendorProductVersionsSource
Red Hat Red Hat AI Inference Server All CVEProject cvelistV5 (CNA)
Red Hat Red Hat Enterprise Linux AI (RHEL AI) 3 All CVEProject cvelistV5 (CNA)
Red Hat Red Hat Enterprise Linux AI (RHEL AI) 3 All CVEProject cvelistV5 (CNA)
Red Hat Red Hat Enterprise Linux AI (RHEL AI) 3 All CVEProject cvelistV5 (CNA)
Red Hat Red Hat Enterprise Linux AI (RHEL AI) 3 All CVEProject cvelistV5 (CNA)
vllm-project vLLM >= 0.10.1, < 0.14.0 CVEProject cvelistV5 (CNA)

References and advisories

17
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Details

Published
2026-01-22
Last updated
2026-07-21
State
Published
Assigner (CNA)
GitHub_M

Exploit prediction (EPSS)

0.98%
Probability of exploitation in 30 days
62.3%
Percentile (among all CVEs)

SSVC assessment (CISA)

Automatable
No
Exploitation
None
Technical impact
Total

Weaknesses (CWE)

  • CWE-94
    Improper Control of Generation of Code ('Code Injection')