Description

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.

Weaknesses 1

Affected Products 1

References 2

• github.com https://github.com/huggingface/transformers/commit/676559d5022b74aaa0cee1cee0842b7f27c5320e
  Patch
• huntr.com https://huntr.com/bounties/ceb3ce1a-4c45-497a-b25e-cb9a7685e619
  ExploitThird Party Advisory

Remediation

• github.com https://github.com/huggingface/transformers/commit/676559d5022b74aaa0cee1cee0842b7f27c5320e
  Patch