Abstract: Techniques for using supervised machine learning to train risk models used to analyze group data for security risks are discussed herein. A system can receive a user input identifying risk values associated with categories or attributes of a group having access to computing resources. The system can use the risk model to generate a risk score for the group. The risk score can be used to further analyze aspects of the group or provide recommendations to reduce or eliminate security risks.

Abstract: Methods and systems for generating and using a dynamic asset inventory are disclosed. According to an implementation, a dynamic inventory can be generated by a function included in a security agent that provides security for a network environment. First computing asset information can be collected from first data sources, and the first computing asset information can be supplemented with second computing asset information. The supplemented computing asset information can be used to generate log files for computing assets. The log files can be used to generate an asset search index that supports rapid search of the dynamic asset inventory.