Cybersecurity is being transformed by the integration of Artificial Intelligence (AI) solutions, with many tools now incorporating Large Language Models (LLMs) to enhance their capabilities. This trend is evident in the development of chatbots, automation tools, and interfaces that utilize Model Context Protocol (MCP) to generate responses. However, a lesser-known aspect of AI is the creation of customized analytics interfaces, such as those used for web honeypot logs. The development of adaptive cyber analytics UIs can provide valuable insights into threat activity, particularly in the context of state-aligned operations, which require a distinct approach to threat modeling1. As Intel shifts from a criminal to a geopolitical threat model, the importance of bespoke analytics tools becomes increasingly clear. The ability to analyze and respond to complex threats in a timely manner is crucial, making the development of adaptive cyber analytics UIs a key priority for cybersecurity professionals.