This blog post discusses the concept of contextual integrity in large language models (LLMs), specifically focusing on the risks of revealing sensitive information due to persistent memory from past interactions. The author reviews the benchmark CIMemories, which evaluates LLMs' ability to control information flow based on task context. The findings indicate significant privacy violations in current models, suggesting a need for improved contextually aware reasoning capabilities rather than mere better prompting techniques.