4M Models Scanned: Protect AI + Hugging Face 6 Months In

Hugging Face and Protect AI partnered in October 2024 to enhance machine learning (ML) model security through Guardian’s scanning technology for the community of developers who explore and use models from the Hugging Face Hub. The partnership has been a natural fit from the start—Hugging Face is on a mission to democratize the use of open source AI, with a commitment to safety and security; and Protect AI is building the guardrails to make open source models safe for all.

4 new threat detection modules launched

Since October, Protect AI has significantly expanded Guardian's detection capabilities, improving existing threat detection capabilities and launching four new detection modules:

1. PAIT-ARV-100: Archive slip can write to file system at load time
2. PAIT-JOBLIB-101: Joblib model suspicious code execution detected at model load time
3. PAIT-TF-200: TensorFlow SavedModel contains architectural backdoor
4. PAIT-LMAFL-300: Llamafile can execute malicious code during inference

With these updates, Guardian covers more model file formats and detects additional sophisticated obfuscation techniques, including the high severity CVE-2025-1550 vulnerability in Keras. Through enhanced detection tooling, Hugging Face users receive critical security information via inline alerts on the platform and gain access to comprehensive vulnerability reports on Insights DB. Clearly labeled findings are available on each model page, empowering users to make more informed decisions about which models to integrate into their projects.

Figure 1: Protect AI’s inline alerts on Hugging Face

By the numbers

As of April 1, 2025, Protect AI has successfully scanned 4.47 million unique model versions in 1.41 million repositories on the Hugging Face Hub.

To date, Protect AI has identified a total of 352,000 unsafe/suspicious issues across 51,700 models. In just the last 30 days, Protect AI has served 226 million requests from Hugging Face at a 7.94 ms response time.

Figure 2: huntr’s bug bounty program