Abstract. Prompt injection attacks pose a critical threat to large language model (LLM) deployments, enabling adversaries to override system instructions, exfiltrate data, and bypass safety controls. We present a multi-path ensemble system that combines three complementary detection strategies: (1) centroid-based embedding similarity against curated attack pattern clusters, (2) trajectory analysis