
A newly disclosed vulnerability in Hugging Face Transformers could allow malicious AI model repositories to place attacker-controlled Python files on a user's system before the user approves remote code execution. Tracked as CVE-2026-80047, the issue affects Hugging Face Transformers versions 4.49.0 through 5.8.1.
The flaw lies in the library's custom generation-loading process. It can allow remote Python code to be written to the local Hugging Face module cache without authorization. Hugging Face Transformers is widely used to train, deploy, and run machine learning models for natural language processing, computer vision, audio, video, and multimodal AI tasks.
Because the framework is commonly integrated into developer workstations, research environments, cloud notebooks, and production ML pipelines, the vulnerability could expose a broad range of users to untrusted content from model repositories. The issue occurs in GenerativePreTrainedModel. load_custom_generate(), which is used to load custom text-generation logic from model repositories.
When a user attempts to load a…
➪ Continue reading the full article on cybersecuritynews.com









