CyberArena: Benchmarking AI Agents in Live Symmetric Attack-and-Defense Combat
AI agents are demonstrating increasingly strong offensive and defensive cybersecurity capabilities in the real world. Current benchmarks mostly evaluate agents in isolation against static targets. Real cyber operations, however, are dynamic and coupled: security postures constantly change as attackers and defenders adapt to each other in real time. Static benchmarks quickly saturate and miss an agent's ability to attack and defend simultaneously under live pressure. To address this gap, we present CyberArena, a dynamic, symmetric adversarial benchmark built around multi-round attack-and-defense combat. In isolated sandboxes, two agents compete under identical rules, acting concurrently as...
| Authors | Bangya Liu, Jianhong Tu, Yueyang Pan et al. |
|---|---|
| Primary category | cs.CR |
| Published | 13 October 2026 |
| Last updated at source | 13 October 2026 |
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