One Turn Too Late: Response-Aware Defense Against Hidden Malicious Intent in Multi-Turn Dialogue

Hidden malicious intent in multi-turn dialogue poses a growing threat to deployed large language models (LLMs). Rather than exposing a harmful objective in a single prompt, increasingly capable attackers can distribute their intent across multiple benign-looking turns. Recent studies show that even modern commercial models with advanced guardrails remain vulnerable to such attacks despite advances in safety alignment and external guardrails. In this work, we address this challenge by detecting t

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ethics.ai (7 May 2026), “One Turn Too Late: Response-Aware Defense Against Hidden Malicious Intent in Multi-Turn Dialogue,” evidence record 4869, https://ethics.ai/record/4869 (originally published by arXiv).

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