OpenAnt: LLM-Powered Vulnerability Discovery through Code Decomposition, Adversarial Verification, and Dynamic Testing

Automated vulnerability discovery in large codebases remains challenging: traditional static analysis produces high false-positive rates, while dynamic approaches such as fuzzing require substantial infrastructure and often target narrow classes of bugs. Recent advances in large language models...

Strategic Heterogeneous Multi-Agent Architecture for Cost-Effective Code Vulnerability Detection

Automated code vulnerability detection is critical for software security, yet existing approaches face a fundamental trade-off between detection accuracy and computational cost. We propose a heterogeneous multi-agent architecture inspired by game-theoretic principles, combining cloud-based LLM...