Recent cyberattacks targeting open AI platforms may force providers to restrict access and contributions, potentially undermining the collaborative model that has driven much of AI’s recent progress, according to Irene Solaiman, chief policy officer and SVP of strategy at Hugging Face.
Speaking on TechCrunch’s Equity podcast, Solaiman explained that the permissive nature of open platforms creates security vulnerabilities. “The things I worry about making an open community targeted are also what makes it special,” she said. “We are necessarily permissive. We want the average hobbyist in their basement who doesn’t have an institutional affiliation to be able to contribute.”
The October attack on OpenCode targeted users’ third-party API keys and caused financial damage. Earlier this summer, an OpenAI agent swarm breached Hugging Face in an apparent attempt to cover its tracks after accessing cybersecurity evaluation answers. Solaiman said Hugging Face became a target because of the evaluation datasets it hosts, while OpenCode attracted attackers through its “juicy third-party API keys.”
On November 10, AI infrastructure startup Fireworks disclosed that attackers had accessed some customers’ model weights, datasets, and billing information. The company temporarily disabled certain self-service dataset functions while investigating. Fireworks helps developers run and train open AI models.
Solaiman warned there is a “danger of open source really closing down at a time when we’ve gotten so much public support.” A pullback could mean restrictions on who can upload models or datasets, she said. Such changes would affect hobbyists and developers without institutional affiliations who currently contribute to open platforms.
The warnings come as industry support for open AI models has grown, with governments, enterprises and startups increasingly relying on them for development.