CyberEvolver: Structured Self-Evolution for Cybersecurity Agents On the Fly
LLM-based agents are increasingly used for cybersecurity tasks, but most existing systems rely on fixed, human-designed scaffolds that struggle to adapt across diverse targets and failure modes. We introduce \textsc{CyberEvolver}, a self-evolving cybersecurity agent framework that iteratively revises its own scaffold based on experience from failed execution attempts. Self-evolution in cybersecurity is challenging because the space of possible scaffold changes is largely unstructured, execution feedback is sparse and often obscured by the environment, and low-diversity updates can cause errors to compound over repeated iterations. \textsc{CyberEvolver} addresses these challenges with a fo...
| Authors | Yihe Fan, Changyi Li, Lichen Xu et al. |
|---|---|
| Primary category | cs.CR |
| Published | 25 May 2026 |
| Last updated at source | 16 June 2026 |
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