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CybORG: A Gym for the Development of Autonomous Cyber Agents

arXiv 2108.09118 ↗First posted 20 Aug 2021cs.CRcited by 58

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Abstract (arXiv)

Autonomous Cyber Operations (ACO) involves the development of blue team (defender) and red team (attacker) decision-making agents in adversarial scenarios. To support the application of machine learning algorithms to solve this problem, and to encourage researchers in this field to attend to problems in the ACO setting, we introduce CybORG, a work-in-progress gym for ACO research. CybORG features a simulation and emulation environment with a common interface to facilitate the rapid training of autonomous agents that can then be tested on real-world systems. Initial testing demonstrates the feasibility of this approach.

Key facts. Cited by 58 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Aug 2021.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 4; 2023: 12; 2024: 14; 2025: 9; 2026: 17.

58 papers.

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  1. 2022Developing Optimal Causal Cyber-Defence Agents via Cyber Security Simulationcited by 37
  2. 2022Beyond CAGE: Investigating Generalization of Learned Autonomous Network Defense Policiescited by 22
  3. 2023NASimEmu: Network Attack Simulator & Emulator for Training Agents Generalizing to Novel Scenarioscited by 20
  4. 2024Depending on yourself when you should: Mentoring LLM with RL agents to become the master in cybersecurity gamescited by 20
  5. 2023Automated Cyber Defence: A Reviewcited by 19
  6. 2021Intrusion Prevention through Optimal Stoppingcited by 18
  7. 2023Inroads into Autonomous Network Defence using Explained Reinforcement Learningcited by 17
  8. 2023Out of the Cage: How Stochastic Parrots Win in Cyber Security Environmentscited by 17
  9. 2024Autonomous Network Defence using Reinforcement Learningcited by 14
  10. 2025Large Language Models are Autonomous Cyber Defenderscited by 14
  11. 2023Learning Near-Optimal Intrusion Responses Against Dynamic Attackerscited by 13
  12. 2023Learning Cyber Defence Tactics from Scratch with Multi-Agent Reinforcement Learningcited by 12
38 more
  1. 2024Optimal Defender Strategies for CAGE-2 using Causal Modeling and Tree Searchcited by 12
  2. 2024CybORG++: An Enhanced Gym for the Development of Autonomous Cyber Agentscited by 11
  3. 2024Entity-based Reinforcement Learning for Autonomous Cyber Defencecited by 11
  4. 2025Incident Response Planning Using a Lightweight Large Language Model with Reduced Hallucinationcited by 10
  5. 2023Canaries and Whistles: Resilient Drone Communication Networks with (or without) Deep Reinforcement Learningcited by 9
  6. 2023A Multiagent CyberBattleSim for RL Cyber Operation Agentscited by 8
  7. 2024Structural Generalization in Autonomous Cyber Incident Response with Message-Passing Neural Networks and Reinforcement Learningcited by 7
  8. 2022Learning Security Strategies through Game Play and Optimal Stoppingcited by 5
  9. 2024SoK: On the Offensive Potential of AIcited by 5
  10. 2026CSLE: A Reinforcement Learning Platform for Autonomous Security Managementcited by 5
  11. 2021Modelling Direct Messaging Networks with Multiple Recipients for Cyber Deceptioncited by 4
  12. 2024Designing Robust Cyber-Defense Agents with Evolving Behavior Treescited by 4
  13. 2023SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learningcited by 3
  14. 2023Enabling A Network AI Gym for Autonomous Cyber Agentscited by 3
  15. 2023Training Automated Defense Strategies Using Graph-based Cyber Attack Simulationscited by 3
  16. 2024The Path To Autonomous Cyber Defensecited by 3
  17. 2024Evaluation of Reinforcement Learning for Autonomous Penetration Testing using A3C, Q-learning and DQNcited by 3
  18. 2024Out-of-Distribution Detection for Neurosymbolic Autonomous Cyber Agentscited by 3
  19. 2025Learning Optimal Defender Strategies for CAGE-2 using a POMDP Modelcited by 3
  20. 2026Beyond Rewards in Reinforcement Learning for Cyber Defencecited by 3
  21. 2026Building Better Environments for Autonomous Cyber Defencecited by 3
  22. 2022Deception for Cyber Defence: Challenges and Opportunitiescited by 2
  23. 2024Multi-Agent Reinforcement Learning for Maritime Operational Technology Cyber Securitycited by 2
  24. 2024Multi-Agent Actor-Critics in Autonomous Cyber Defensecited by 2
  25. 2025Learning Robust Penetration Testing Policies under Partial Observability: A systematic evaluationcited by 2
  26. 2023Unified Emulation-Simulation Training Environment for Autonomous Cyber Agentscited by 1
  27. 2025Quantitative Resilience Modeling for Autonomous Cyber Defensecited by 1
  28. 2025Training RL Agents for Multi-Objective Network Defense Taskscited by 1
  29. 2025Towards a Generalisable Cyber Defence Agent for Real-World Computer Networkscited by 1
  30. 2026Context, Reasoning, and Hierarchy: A Cost-Performance Study of Compound LLM Agent Design in an Adversarial POMDPcited by 1
  31. 2026FORGE: Self-Evolving Agent Memory With No Weight Updates via Population Broadcastcited by 1
  32. 2024Explore Reinforced: Equilibrium Approximation with Reinforcement Learningcited by 0
  33. 2025An Organizationally-Oriented Approach to Enhancing Explainability and Control in Multi-Agent Reinforcement Learningcited by 0
  34. 2025PoolFlip: A Multi-Agent Reinforcement Learning Security Environment for Cyber Defensecited by 0
  35. 2026NASimJax: A GPU-Accelerated Policy Learning Framework for Penetration Testingcited by 0
  36. 2026Learning Communication Between Heterogeneous Agents in Multi-Agent Reinforcement Learning for Autonomous Cyber Defencecited by 0
  37. 2026Closing the Sim-to-Real Gap: An Evaluation Framework for Autonomous Cyber Defense Configuration of Commercial EDRcited by 0
  38. 2026Shielded Analysis: Certification and Characterization of Defensibility in Systems under Adversarial Interactioncited by 0

50 most cited of 58 All 58 (JSON)