TrinityGuard: A Unified Framework for Safeguarding Multi-Agent Systems

Published in arXiv, 2026

TrinityGuard introduces a unified safeguarding framework for multi-agent AI systems, addressing safety vulnerabilities arising from agent interactions. The framework employs three complementary layers of protection—input sanitization, cross-agent verification, and output auditing—to ensure robust and trustworthy multi-agent coordination.