From Concept to Deployment: An AI Assistant for Generating and Configuring Cyber Range Scenarios

This paper introduces an AI Assistant (AIA) designed to streamline the creation and deployment of cyber range scenarios for cybersecurity training. As organizations confront an evolving threat landscape, hands-on training in environments that accurately simulate real-world scenarios has become critical to building resilient security teams. However, developing customized scenarios that reflect varied IT and OT infrastructures remains time-consuming and resource-intensive. The proposed AIA addresses this challenge by leveraging Large Language Models (specifically Llama-3.1-8B-instruct [1], which we will refer to as Llama 3.1) to generate tailored training scenarios through a conversational interface. The system accepts high-level requirements from scenario designers and produces comprehensive outputs including storylines, network topologies, and configuration files compatible with deployment tools like Terraform and Ansible. Key innovations include an interactive development process allowing iterative refinement, support for varying difficulty levels, and vendor-agnostic implementation that works across different cyber range infrastructures. Finally, the AIA follows a human-in-the-loop approach, serving as a collaborative partner that handles technical complexities while allowing designers to focus on educational objectives and demonstrates significant potential for reducing scenario development time while maintaining educational effectiveness and technical accuracy.