There is none. We don't understand LLMs well enough to be able to conduct a full fault analysis like this. We can't trace the thoughts of an LLM the way we can

There is none. We don't understand LLMs well enough to be able to conduct a full fault analysis like this. We can't trace the thoughts of an LLM the way we can trace code execution - the best mechanistic interpretability has to offer is being able to get glimpses occasionally. The reasoning traces help, but they're still incomplete. Is it pattern-matching? Is it acting on its own internal goals? Is it acting out fictional tropes? Were the circumstances of the test scenarios intentionally designed to be extreme? Would this behavior have happened in a real world deployment, under the right circumstances? The answer is "yes", to all of the above. LLMs are like that.