Instituto Nacional de ciberseguridad. Sección Incibe
Instituto Nacional de Ciberseguridad. Sección INCIBE-CERT

CVE-2025-66448

Gravedad CVSS v3.1:
ALTA
Tipo:
CWE-94 Control incorrecto de generación de código (Inyección de código)
Fecha de publicación:
01/12/2025
Última modificación:
01/12/2025

Descripción

*** Pendiente de traducción *** vLLM is an inference and serving engine for large language models (LLMs). Prior to 0.11.1, vllm has a critical remote code execution vector in a config class named Nemotron_Nano_VL_Config. When vllm loads a model config that contains an auto_map entry, the config class resolves that mapping with get_class_from_dynamic_module(...) and immediately instantiates the returned class. This fetches and executes Python from the remote repository referenced in the auto_map string. Crucially, this happens even when the caller explicitly sets trust_remote_code=False in vllm.transformers_utils.config.get_config. In practice, an attacker can publish a benign-looking frontend repo whose config.json points via auto_map to a separate malicious backend repo; loading the frontend will silently run the backend’s code on the victim host. This vulnerability is fixed in 0.11.1.