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AI agent vulnerability · Transformers

CVE-2026-5241: huggingface/transformers: Arbitrary Code Execution During Model Initialization in the LightGlue Model Loading Path

highCVSS 3.0 8.0GHSA-fgcw-684q-jj6r

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 trustremotecode parameter, intended to prevent remote code execution, is overridden by untrusted serialized configuration data in a nested code path.

Published Jun 3, 2026 · Updated Jul 21, 2026

Affected packages

transformers

Ecosystem
PyPI
Affected
< 5.5.0
Fixed in
5.5.0
Check
pip show transformers

Advisory details

From the GitHub Advisory Database (CC BY 4.0).

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.

References

How this page is made: the data panel comes from the GitHub Advisory Database, CISA’s KEV catalog, the NVD and FIRST EPSS, and updates twice a day. No analysis has been written for this entry yet. Methodology

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