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paperAugust 2026Unreviewed

CyberAGENTS: Structured Autonomy for Agentic Gamified Learning in Cybersecurity

Ivan Hornung, Deepthi Marasinghe Arachchige, Tharindu Kumarage, Garima Agrawal, Yuli Deng, Ying-Chih Chen, Huan Liu

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Abstract

Gamification is especially effective in learning domains requiring active problem-solving and iterative skill-building, such as cybersecurity education. Generative AI agents offer a path to delivering such experiences adaptively at scale, but introduce well-documented risks in educational settings: inconsistent behavior, hallucinated reasoning, and misalignment with pedagogical frameworks. Grounding these systems in learning science is therefore essential. We present \model, an agentic framework

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Agentic Threats

Cite

@misc{hornung2026cyberagents,
  title = {{CyberAGENTS: Structured Autonomy for Agentic Gamified Learning in Cybersecurity}},
  author = {Ivan Hornung and Deepthi Marasinghe Arachchige and Tharindu Kumarage and Garima Agrawal and Yuli Deng and Ying-Chih Chen and Huan Liu},
  year = {2026},
  month = aug,
  eprint = {2608.07965},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2608.07965}
}