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Internal safety scores judge a prompt before any text is generated, and they are validated by how well they separate harmful prompts from benign ones, so Active Attention Probing is introduced, which supplies a fixed content independent measurement coordinate.
ActProbe, an internal-state-based framework for detecting and localizing poisoned segments in multi-source LLM inputs, is proposed and remains effective against defense-aware adaptive attacks and can protect black-box APIs through surrogate-based poisoned-segment removal.
AcMAS is proposed, an activation-based framework for malicious-behavior detection in MAS that significantly outperforms graph-based baselines against stealthy attacks, with generalization across diverse open-source LLM backbones, attack intensity, and MAS scale.
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