Mind the Gap: towards generalizable autonomous penetration testing via domain randomization and meta-reinforcement learning

Shicheng ZHOU; Jingju LIU; Yuliang LU; Jiahai YANG; Yue ZHANG; Jie CHEN

doi:10.1631/FITEE.2500100

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Mind the Gap: towards generalizable autonomous penetration testing via domain randomization and meta-reinforcement learning

Regular Papers | Updated：2026-01-12

- Mind the Gap: towards generalizable autonomous penetration testing via domain randomization and meta-reinforcement learning
  Enhanced Publication
- 注意差距：通过域随机化和元强化学习实现可泛化的自动化渗透测试
- “In the field of autonomous penetration testing, researchers have made significant progress. They established the GAP framework, which provides solutions to address the training environment dilemma and poor generalization ability, opening up a new direction for autonomous pentesting research.”
- Frontiers of Information Technology & Electronic Engineering Vol. 26, Issue 12, Pages: 2511-2528(2025)
- Affiliations：
  
  1.College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China
  2.Anhui Province Key Laboratory of Cyberspace Security Situation, Awareness and Evaluation, Hefei 230037, China
  3.Institute for Network Sciences and Cyberspace, Tsinghua University, Beijing 100084, China
  4.College of Computer Science and Technology, National University of Defense Technology, Changsha 410073, China
- Author bio：
  
  E-mail: zhoushicheng@nudt.edu.cn
  ‡ Corresponding authors
- Funds：
- DOI：10.1631/FITEE.2500100
  CLC： TP393
- Received：16 February 2025，
  
  Revised：2025-10-17，
  
  Published Online：12 December 2025，
  
  Published：2025-12
- Accepted：
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Shicheng ZHOU, Jingju LIU, Yuliang LU, et al. Mind the Gap: towards generalizable autonomous penetration testing via domain randomization and meta-reinforcement learning[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(12): 2511-2528.
DOI：

Shicheng ZHOU, Jingju LIU, Yuliang LU, et al. Mind the Gap: towards generalizable autonomous penetration testing via domain randomization and meta-reinforcement learning[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(12): 2511-2528. DOI： 10.1631/FITEE.2500100.

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Mind the Gap: towards generalizable autonomous penetration testing via domain randomization and meta-reinforcement learning

DOI：10.1631/FITEE.2500100