Two baselines that cover parts of this:
LongMemEval ( [2410.10813] LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory ) tests “information extraction, multi-session reasoning, temporal reasoning, knowledge updates, and abstention”, and splits memory into “indexing, retrieval, and reading”. That split answers whether to score retrieval and the final answer separately: I think you should, since an invented memory can come from either stage.
For revoked consent, TOFU ( [2401.06121] TOFU: A Task of Fictitious Unlearning for LLMs ) is the nearest setup: “200 diverse synthetic author profiles” with a “forget set that serves as the target for unlearning”. You can treat a revoked fact as forget-set data and check that it never comes back in answers; not only that, but it is gone from the store. One suggestion from my side: score abstention on questions the system should not know, together with accuracy on ones it should. Otherwise, a system that refuses everything looks perfect on invented memories.