How Do AI Models Change Security Bug Priority?

Christina Cacioppo says AI models are far more persistent than people, so issues that look low severity on their own get chained into a real finding, and teams have to fix problems as fast as they find them.

Models will try nine quadrillion things where a person would give up after 9000. Some of what they surface are zero days people had not found before, or had not found in public. The bigger change is chaining 17 benign or only benign-ish issues into one real result. An OpenAI talk at RSA about Hugging Face showed the same pattern: persistence, then joining items a person would call low severity and plan to fix in 90 days. Someone would still wait 90 days and do other work first. Machines turn the order of that work on its head.

Saying every issue is critical does not tell a team what to do next. The working result is to fix stuff as fast as it is found, because the fight is with machines.