AI Meets Cryptography 1: What AI Found in Cloudflare's Circl

1. Could you expand on this? "That human-in-the-loop step still matters a lot, because AI candidate findings are cheap while trustworthy reports are not." Roughly how many candidate reports did the LLMs create vs the eventual 7 true vulnerabilities?

2. As I was reading "CP-ABE access-control break via AND-share bug" I thought "why wasn't this caught with a test?", which was going to be my question but clicking through to the commit (thanks for that too btw) I see there was a regression test added: https://github.com/cloudflare/circl/commit/def2fd35b8535b0b8... but I'm wondering why there isn't a test further up the stack that is simply checking "can't decrypt if the required attribute isn't present"? Seems similar to those situations where nobody thought to test an auth system for "user can't log in when they present the wrong password"!! Perhaps I'm missing some subtlety though.

3. This is probably a dumb question, but I wasn't sure (even after reading the linked article on zkao) exactly what zkao actually is. One description seems to be "a system for continuously running an LLM audit pass on a codebase". But that can't be right because this article talks about running it on the LLM-found vulnerability reports. Is it an LLM? (but better than the frontier LLMs?) Anyway, bit confused and would appreciate some clarity.

Wow.

I mean I know djb managed at some point to coax an x86 CPU floating point unit to perform weird integer operations to speed up some of his algorithms, but I would never have expected people to use floats the "intended way" to implement crypto algorithms.