CVE-2026-5241— Hugging Face Transformers 安全漏洞

Policy Bypass in LightGlue Nested Config Resolution in huggingface/transformers

A vulnerability in the LightGlue model loading path of huggingface/transformers version 5.2.0 allows an attacker-controlled model repository to execute arbitrary code during model initialization. The issue arises because the `trust_remote_code` parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path. Specifically, when loading a LightGlue model using `AutoModel.from_pretrained()` with `trust_remote_code=False`, the `LightGlueConfig` reads the `trust_remote_code` value from the untrusted `config.json` file and propagates it into nested `AutoConfig.from_pretrained()` calls. This results in the execution of attacker-provided Python modules, even when the victim explicitly disables remote code execution. The vulnerability poses a high risk for environments such as API inference servers, research notebooks, CI/CD pipelines, and model evaluation workers, potentially leading to credential theft, lateral movement, or persistence/backdoor deployment.

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从非可信控制范围包含功能例程

Hugging Face Transformers 安全漏洞

Hugging Face Transformers是Hugging Face开源的一个用于定义最先进机器学习模型的框架，涵盖文本、视觉、音频和多模态模型，可用于推理和训练。 Hugging Face Transformers 5.2.0版本存在安全漏洞，该漏洞源于LightGlue模型加载路径中trust_remote_code参数被覆盖，可能导致远程代码执行。

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