How LLMs could help defenders write better and faster detection
Summary: Security researchers from across Cisco, including Darin Smith, Yuvi Meiyappan, Moazzam Khan and Ray McCormick, examined whether large language models could help defenders write more effective detection content and assist in the detection research process. Khan will present the paper's findings at the upcoming BSides Portland conference.
Bottom line: Detection research involves repeatedly emulating adversary behavior to test whether existing rules fire, a complex and time-consuming task - and the researchers are weighing whether LLMs can take on part of that load.
Read the original at Cisco Talos ↗
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