AfterDeleteBench: Auditing Post-Deletion Information Persistence in LLM Agents
Benchmark demonstrates that deleting records from LLM agent memory does not erase derived information such as summaries, exposing a practical GDPR right-to-erasure gap for enterprises deploying persistent-memory agents.
Summary written by editorial AI · Source link below
arXiv:2610.31366v1 Announce Type: new Abstract: Many LLM agents maintain external persistent memory and derive additional state from past interactions, such as summaries. Deleting an original memory record therefore need not remove information carried by its descendants. We introduce AfterDeleteBench, a controlled behavioral audit for this failure mode in fixed-weight LLM agents. For each synthetic secret, we compare an exposed-then-deleted agent with an otherwise matched agent that was never e
Editorial Analysis
Enterprises using LLM agents with persistent memory risk non-compliance with GDPR erasure obligations if derived data survives deletion of source records.
Map all derived-data pathways in your LLM agent memory systems and verify that deletion cascades to summaries and inferred state.
LLM agents may retain personal data in derived form even after source deletion, creating a tangible GDPR erasure compliance risk.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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