Are You Reading the Right Thing? Rethinking Internal Signals for Prompt-Injection Detection

Sarthak Gupta, Priyanka Tembey

Several recent studies propose detecting prompt injections from a language model's internal state. However, these methods do not measure a single security property. Residual-stream probes, attention scores, role projections, exposure probes, and concept readouts may capture injection presence, recognition, information routing, or behavioral influence. It is therefore unclear what differences in prompt-injection detection performance reveal about the internal signals these methods read. We study how five representation-reading methods vary under a common structured indirect prompt-injection setup on Qwen3.6-35B-A3B and Gemma-4-26B-A4B-it. We evaluate each method by how well it distinguishes injected prompts from benign controls. We then further analyze each detection method's ability to detect attacks in cases where they are successful and in cases where they are not. This helps us better assess what properties each detection method might rely on. Methods trained to detect injection presence or attack-related concepts generally separate unsuccessful injections more strongly from benign inputs, whereas attention diversion, exposure, and role-confusion-based methods separate…