Combining Long-Term Memory and LLMs Comes at a High Cost: From Prompt Injection to Persistent Compromise
However, persistent memory features in modern conversational interfaces enable cross-session attack propagation, establishing a threat vector known as memory injection.
ProofPaper ↗
Key points
- The widespread adoption of generative artificial intelligence in recent years has brought a parallel rise in prompt injection and jailbreak attacks.
- In traditional chatbots, such attacks are confined to a single session because state memory is not preserved across conversations.
- While existing literature focuses on violations tailored to specific platform features, we present a general threat model.
- We also show that memory injections can exploit multiple attack vectors, including personal memories, projects, skills, organization instructions, and Model Context Protocol (MCP)-connected resources.
Sources (1)
- [1]Combining Long-Term Memory and LLMs Comes at a High Cost: From Prompt Injection to Persistent CompromisearXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 20, 06:33 PM
However, persistent memory features in modern conversational interfaces enable cross-session attack propagation, establishing a threat vector known as memory injection.
The widespread adoption of generative artificial intelligence in recent years has brought a parallel rise in prompt injection and jailbreak attacks.
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