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CVE-2026-22807
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.
Affected Packages
https://github.com/vllm-project/vllm.git (GITHUB):
Affected version(s) >=v0.10.1 <v0.14.0
Fix Suggestion:
Update to version v0.14.0
vllm (PYTHON):
Affected version(s) >=0.10.1 <0.14.0
Fix Suggestion:
Update to version 0.14.0
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CVSS v4
Base Score:
8.7
Attack Vector
NETWORK
Attack Complexity
LOW
Attack Requirements
NONE
Privileges Required
NONE
User Interaction
PASSIVE
Vulnerable System Confidentiality
HIGH
Vulnerable System Integrity
HIGH
Vulnerable System Availability
HIGH
Subsequent System Confidentiality
NONE
Subsequent System Integrity
NONE
Subsequent System Availability
NONE
CVSS v3
Base Score:
8.8
Attack Vector
NETWORK
Attack Complexity
LOW
Privileges Required
NONE
User Interaction
REQUIRED
Scope
UNCHANGED
Confidentiality
HIGH
Integrity
HIGH
Availability
HIGH
Weakness Type (CWE)
Improper Control of Generation of Code ('Code Injection')
EPSS
Base Score:
0.02