Threat hunting is in flux. What started as a largely reactive skill became proactive and is progressing toward automation. Threat hunting is the practice of finding threats within the system. It sits between external attack surface management (EASM), and the security operations center (SOC). EASM seeks to thwart attacks by protecting the interface between the network and the internet. If it fails, and an attacker gets into the system, threat hunting seeks to find and monitor the traces left by the adversary so the attack can be neutralized before damage can be done. SOC engineers take new threat hunter data and build new detection rules for the SIEM.
Enterprises today are expected to have at least 6-8 detection tools, as detection is considered a standard investment and the first line of defense. Yet security leaders struggle to justify dedicating resources further down the alert lifecycle to their superiors. As a result, most organizations' security investments are asymmetrical, robust detection tools paired with an under-resourced SOC, their last line of defense.
CrowdStrike has teamed up with Meta to launch a new open-source suite of benchmarks to test the performance of AI models within an organization's security operations center (SOC). Dubbed , the suite is designed to help businesses sift through a growing mountain of AI-powered cybersecurity tools to help them hone in on one that's ideally suited for their needs. "Without clear benchmarks, it's difficult to know which systems, use cases, and performance standards deliver a true AI advantage against real-world attacks," CrowdStrike wrote in a press release.