US Patent 11546369 Self-learning data collection of machine characteristics

Systems and methods are disclosed to implement a self-learning machine assessment system that automatically tunes what data is collected from remote machines. In embodiments, agents are deployed on remote machines to collect machine characteristics data according to collection rule sets, and to report the collected data to the machine assessment system. The machine assessment system assesses the remote machines using the collected data, and automatically determines, based on what data was or was not needed during the assessment, whether an agent's collection rule set should be changed. Any determined changes are sent back to the agent, causing the agent to update its scope of collection. The auto-tuning process may continue over multiple iterations until the agent's collection scope is stabilized. In embodiments, the assessment process may be used to analyze the remote machine to determine security vulnerabilities, and recommend possible actions to take to mitigate the vulnerabilities.