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LiaisonAgent: An Multi-Agent Framework for Autonomous Risk Investigation and Governance

arXiv – CS AI|Chuanming Tang, Ling Qing, Shifeng Chen||3 views
🤖AI Summary

Researchers introduce LiaisonAgent, an autonomous multi-agent cybersecurity system built on the QWQ-32B reasoning model that automates risk investigation and governance for Security Operations Centers. The system achieves 97.8% success rate in tool-calling and 95% accuracy in risk judgment while reducing manual investigation overhead by 92.7%.

Key Takeaways
  • LiaisonAgent uses multiple specialized AI agents to bridge technical risk detection with business-level governance decisions.
  • The system achieved 97.8% tool-calling success rate and 95% risk judgment accuracy in experimental evaluations.
  • Manual investigation overhead was reduced by 92.7% compared to traditional SOC approaches.
  • The framework demonstrates resilience against adversarial prompt injections and out-of-distribution scenarios.
  • The system combines deterministic compliance workflows with autonomous reasoning using the ReAct paradigm.
Read Original →via arXiv – CS AI
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