Source: New Yorker Science & Technology (paywall)
A sophisticated attack on Hugging Face—the primary repository where researchers and companies download open-source AI models—shows that AI security threats have shifted from protecting proprietary models to compromising the shared infrastructure that trains them. The hack's significance lies not in what was stolen but in demonstrating that attackers can intercept, modify, or poison models at the source, potentially affecting thousands of downstream applications before detection. It exposes a structural weakness: most organizations assume the models they download are uncompromised, creating a single point of failure that's far more valuable to adversaries than targeting individual companies.