Hugging Face Diffusers Flaws Could Let Model Repositories Execute Arbitrary Code
Summary
Three high-severity security flaws were found in Hugging Face's Diffusers library (a Python package for generating images, videos, and audio) that could allow attackers to execute arbitrary code (running any commands they want) when loading model repositories, bypassing the trust_remote_code safeguard (a security check meant to prevent unreviewed code from running). These vulnerabilities, collectively called FaceHugger, exploit a timing weakness in how the library downloads and checks models in two separate steps instead of one atomic operation (a single indivisible action).
Solution / Mitigation
The vulnerabilities were addressed in Diffusers version 0.38.0, released in early May 2026. If immediate patching is not an option, the project maintainers recommended: Only call from_pretrained with pretrained_model_name_or_path, custom_pipeline, and local snapshot directories from fully trusted sources that have been audited, and do not pass custom_pipeline= pointing to untrusted locations.
Classification
Affected Vendors
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Original source: https://thehackernews.com/2026/08/hugging-face-diffusers-flaws-could-let.html
First tracked: August 3, 2026 at 08:01 AM
Classified by LLM (prompt v3) · confidence: 95%