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CVE-2026-22807 Detail

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.


Metrics

NVD enrichment efforts reference publicly available information to associate vector strings. CVSS information contributed by other sources is also displayed.
CVSS 4.0 Severity and Vector Strings:

NIST CVSS score
NIST: NVD
N/A
NVD assessment not yet provided.

References to Advisories, Solutions, and Tools

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URL Source(s) Tag(s)
https://github.com/vllm-project/vllm/commit/78d13ea9de4b1ce5e4d8a5af9738fea71fb024e5 GitHub, Inc.
https://github.com/vllm-project/vllm/pull/32194 GitHub, Inc.
https://github.com/vllm-project/vllm/releases/tag/v0.14.0 GitHub, Inc.
https://github.com/vllm-project/vllm/security/advisories/GHSA-2pc9-4j83-qjmr GitHub, Inc.

Weakness Enumeration

CWE-ID CWE Name Source
CWE-94 Improper Control of Generation of Code ('Code Injection') GitHub, Inc.  

Change History

1 change records found show changes

Quick Info

CVE Dictionary Entry:
CVE-2026-22807
NVD Published Date:
01/21/2026
NVD Last Modified:
01/21/2026
Source:
GitHub, Inc.