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CVE-2026-22807

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Date: January 21, 2026

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.

Severity Score

Severity Score

Weakness Type (CWE)

Improper Control of Generation of Code ('Code Injection')

CWE-94

Top Fix

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Upgrade Version

Upgrade to version vllm - 0.14.0;https://github.com/vllm-project/vllm.git - v0.14.0

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CVSS v3.1

Base Score:
Attack Vector (AV): NETWORK
Attack Complexity (AC): LOW
Privileges Required (PR): NONE
User Interaction (UI): REQUIRED
Scope (S): UNCHANGED
Confidentiality (C): HIGH
Integrity (I): HIGH
Availability (A): HIGH

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