Cybersecurity Agent

This green agent evaluates the behavior of an AI system by simulating benign but potentially sensitive usage patterns and telemetry events. It assesses how the target system detects, classifies, and responds to these scenarios, including risk scoring, policy enforcement, and response consistency. The agent focuses on end-to-end evaluation of safety handling, signal interpretation, and decision outcomes, ensuring the system operates within expected guardrails without manual intervention.

Agent Trust Arena is a security benchmark for evaluating AI agents' ability to establish trust, detect threats, and maintain secure collaboration in multi-agent enterprise workflows.

This project introduces a specialized evaluation framework for autonomous security agents using the CyberGym/OSS-Fuzz infrastructure. It focuses on the ability of agents to automate the discovery and verification of real-world vulnerabilities (Crashes, Memory Corruption) in C/C++ projects.