BinaryShield: Cross-Service Threat Intelligence in LLM Services using Privacy-Preserving Fingerprints

BinaryShield is the first privacy-preserving threat intelligence system that enables secure sharing of attack fingerprints across compliance boundaries for LLM services. The system addresses the critical security gap where organizations cannot share prompt injection attack intelligence between services due to privacy regulations, achieving an F1-score of 0.94 while providing 38x faster similarity search than dense embeddings.

• →BinaryShield enables secure sharing of LLM attack fingerprints across compliance boundaries without violating privacy regulations.
• →The system uses a unique pipeline combining PII redaction, semantic embedding, binary quantization, and randomized response mechanisms.
• →BinaryShield achieves superior performance with an F1-score of 0.94 compared to SimHash baseline at 0.77.
• →The solution provides 38x faster similarity search and storage reduction compared to dense embeddings.
• →Organizations currently face security blind spots as prompt injection attacks persist undetected across multiple LLM services due to compliance restrictions.