PVDetector: Detecting Prompt Injection Attacks on Purpose-Specific LLM Agents via Policy-Violation Concept Analysis

Jul 15, 2026

Researchers introduce PVDetector, a training-free framework for detecting prompt injection attacks on purpose-specific large language model (LLM) agents. By analyzing hidden-state alignment with policy-violation concepts, PVDetector identifies attacks with less than 1% false negative rate and minimal computational overhead, outperforming existing input-output pattern-based detectors.

Why it matters: As LLMs are increasingly used for specialized tasks with unique restrictions, PVDetector provides an efficient and effective defense against prompt injection attacks by leveraging the model's internal representations of policy violations.

Full story at: arXiv Cryptography and Security ↗