Cybersecurity superintelligence -- artificial intelligence exceeding the best human capability in both speed and strategic reasoning -- represents the next frontier in security. This paper documents the emergence of such capability through three major contributions that have pioneered the field of AI Security. First, PentestGPT (2023) established LLM-guided penetration testing, achieving 228.6% improvement over baseline models through an architecture that externalizes security expertise into natural language guidance. Second, Cybersecurity AI (CAI, 2025) demonstrated automated expert-level performance, operating 3,600x faster than humans while reducing costs 156-fold, validated through #1 rankings at international competitions including the $50,000 Neurogrid CTF prize. Third, Generative Cut-the-Rope (G-CTR, 2026) introduces a neurosymbolic architecture embedding game-theoretic reasoning into LLM-based agents: symbolic equilibrium computation augments neural inference, doubling success rates while reducing behavioral variance 5.2x and achieving 2:1 advantage over non-strategic AI in Attack & Defense scenarios. Together, these advances establish a clear progression from AI-guided humans to human-guided game-theoretic cybersecurity superintelligence.

翻译：网络安全超级智能——在速度和战略推理两方面均超越人类最佳能力的人工智能——代表了安全领域的下一个前沿。本文通过开创AI安全领域的三大贡献，记录了这种能力的涌现。首先，PentestGPT（2023）建立了LLM引导的渗透测试框架，通过将安全专业知识外化为自然语言指导的架构，实现了相对于基线模型228.6%的性能提升。其次，网络安全AI（CAI，2025）展示了自动化专家级性能，其运行速度比人类快3600倍，同时将成本降低156倍，并通过包括5万美元Neurogrid CTF竞赛冠军在内的国际赛事排名第一得到验证。第三，生成式剪绳算法（G-CTR，2026）提出了一种将博弈论推理嵌入基于LLM智能体的神经符号架构：符号均衡计算增强了神经推理，使成功率翻倍的同时将行为方差降低5.2倍，并在攻防场景中对非战略性AI形成2:1的优势。这些进展共同确立了从AI引导人类到人类引导的博弈论网络安全超级智能的清晰演进路径。