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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
Related Resources (7)
Severity Score
Weakness Type (CWE)
Improper Control of Generation of Code ('Code Injection')
CWE-94Top Fix
Upgrade Version
Upgrade to version vllm - 0.14.0;https://github.com/vllm-project/vllm.git - v0.14.0
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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