Combining Long-Term Memory and LLMs Comes at a High Cost: From Prompt Injection to Persistent Compromise
Researchers show that LLM long-term memory turns a single prompt injection into a persistent compromise — a qualitative escalation enterprises must address before deploying agentic AI at scale.
Summary written by editorial AI · Source link below
arXiv:2610.28810v1 Announce Type: new Abstract: The widespread adoption of generative artificial intelligence in recent years has brought a parallel rise in prompt injection and jailbreak attacks. By embedding malicious instructions, these exploits manipulate language models to bypass intended behavior and operational boundaries. In traditional chatbots, such attacks are confined to a single session because state memory is not preserved across conversations. However, persistent memory features
Editorial Analysis
Enterprises deploying agentic AI with memory features face a new persistence mechanism for prompt injection; without mitigation, a single malicious input could corrupt future outputs indefinitely.
Require memory-layer threat modelling and injection-detection guardrails before any agentic LLM system moves to production.
AI systems with persistent memory can be permanently compromised by a single malicious input — a risk that must be addressed before scaling agentic AI deployments.
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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