Hugging Face Deepfake Tests Raise New Risks for AI Procurement
Seven of nine image-editing tools tested on Hugging Face produced sexualized alterations of a woman’s photograph after receiving a straightforward prompt. The July 28 findings expose an enterprise governance gap: A public AI platform, model publisher, application developer and inference provider may all be different parties. The research does not show that every Hugging Face model is unsafe, and Hugging Face did not develop all the tools examined. It shows why approving a familiar platform is not the same as reviewing the individual model, application and safeguards an organization plans to deploy. Simple prompts exposed missing safeguards The European nonprofit AI Forensics tested nine image-editing Spaces that it described as among the platform’s leading tools. Seven generated a topless alteration while retaining the subject’s facial identity and positioning. The researchers said they used a direct prompt and did not try to bypass safety controls. AI Forensics also created decoy Spaces that recorded requests without producing images. They received more than 1,000 requests over seven days, 73% of which the researchers classified as sexual. Of those …
