The project developed a framework and process to translate industrial control system features to a machine-readable format for use with automated cyber tools. This research also examined other current and evolving standards for usability with diverse grid architectures that represent a set of variable conditions to establish the foundation for determining where future research should focus and to support improvements to industry standards and architecture designs for machine-learning cyber defense solutions. This project’s success can serve as the foundation for prioritizing the next research steps to realize automated threat response, improving the timeliness and fidelity of cyber incident consequence models, and enriching national capabilities to share actionable threat intelligence at machine speed.