Where Cyber Agents Struggle: Bottleneck Analysis of Multi-Stage LLM Agents
Multi-stage LLM-based cyber agents may complete attack workflows while remaining brittle, costly, or reliant on incorrect interpretations of execution evidence. Success rates alone obscure inefficiency, adaptation through retries, and recognition of success or failure. We present an end-to-end diagnostic study of an Autonomous Adversary system with orchestrator, executor, and validator LLMs in enterprise-like lateral-movement scenarios. Six frontier models are evaluated across two scenarios and three modes: expert-defined, self-scaffolded, and fully autonomous. We assess validator consistency and evidence grounding; introduce a subtask-conditioned, cost-aware score for abnormal token use,...
| Authors | Saeedeh Lohrasbi, Mohammad Mamun, Ahmed Yehia et al. |
|---|---|
| Primary category | cs.CR |
| Published | 23 September 2026 |
| Last updated at source | 23 September 2026 |
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