A data-driven hunting method is a type of threat hunting method that employs existing data collected from various sources, such as DNS and proxy logs, to generate and test hypotheses about potential threats. This method relies on data analysis and machine learning techniques to identify patterns and anomalies that indicate malicious activity. A data-driven hunting method can help discover unknown or emerging threats that may evade traditional detection methods. An entity-driven hunting method is a type of threat hunting method that focuses on specific entities, such as users, devices, or domains, that are suspected or known to be involved in malicious activity. A TTP-driven hunting method is a type of threat hunting method that leverages threat intelligence and knowledge of adversary tactics, techniques, and procedures (TTPs) to formulate and test hypotheses about potential threats. A hybrid hunting method is a type of threat hunting method that combines different approaches, such as data-driven, entity-driven, and TTP-driven methods, to achieve more comprehensive and effective results.