Protecting against inference theft

The article discusses the growing threat of inference theft in AI, where attackers exploit exposed AI endpoints to run up significant costs for operators. It emphasizes the need for robust verification and analysis on every AI request to mitigate risks, as traditional rate limits and authentication methods are insufficient against sophisticated attacks. The piece highlights the economic motivations behind such attacks and the technical methods employed by attackers to resell stolen inference resources.