- Monday, Apr 6th, 2026
| TITLE | Multi-Agent Cybersecurity Red-Teaming Automation System |
|---|---|
| ABSTRACT | As attacks against network, host, and application layers grow increasingly intricate, there is a pressing requirement for automated red-teaming tools capable of faithfully replicating genuine compromise scenarios. While progress in offensive automation has improved specific tasks like reconnaissance, vulnerability detection, and isolated exploits, contemporary systems rarely deliver fully verified, end-to-end attack chains. Historic approaches often face a trade-off, forcing a choice between frameworks that coordinate agents with restricted roles and planning tools that map out attack paths without actually deploying payloads. Consequently, the reliable automation of post-exploitation actions, privilege escalation, evidence collection, and final reporting remains largely unresolved. This study investigates the current landscape of multi-agent red-teaming and breach-and attack simulations, evaluating their range, execution depth, and validation protocols. The analysis highlights a critical deficiency in systems that attempt to pair live exploitation with centralized planning while ensuring the preservation of verifiable proof-of-compromise. Furthermore, the paper details how orchestration rooted in actual execution allows planning logic to integrate with practical offensive tools, enabling reproducible, full spectrum assessments across diverse target environments. Ultimately, the results underscore the necessity of shifting research away from theoretical attack modelling toward validated, tool-centric automation that accurately mirrors real-world adversary behaviour. |
| AUTHOR | Vaibhav Chikkamath Master of Computer Applications, CMR Institute of Technology, Bengaluru, India |
| VOLUME | 13 |
| DOI | DOI: 10.15680/IJARETY.2026.1302030 |
| 30_Multi-Agent Cybersecurity Red-Teaming Automation System.pdf | |
| KEYWORDS | |
| References | [1] F. Shen, Z. Liu, R. Wu, X. Hu, H. Zhu, and K. Chen, "PentestAgent: Incorporating LLM Agents to Automated Penetration Testing," arXiv preprint arXiv:2411.05185, 2024. [2] R. David and V. Gervais, "MAPTA: Multi-Agent Penetration Testing AI for the Web," arXiv preprint arXiv:2508.20816, 2025. [3] C. Guo, H. Li, Y. Zhang, and L. Chen, "VulnBot: Autonomous Penetration Testing for a Multi-Agent Collaborative Framework," arXiv preprint arXiv:2501.13411, 2025. |
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