Sift: How to Leverage the Power of AI/ML to Improve Threat Analysis
Summary: GreyNoise launched Sift, an application that applies AI/ML to the daily stream of HTTP payload data collected by its global sensor fleet, which sees roughly two million HTTP requests and tens of millions of events from other protocols every day. Sift surfaces potential attacks or suspicious activity along with contextual explanations of why the AI/ML flagged it, aimed at threat intelligence analysts and detection engineers.
Why it matters: Two million HTTP requests a day is far past what any analyst team can read by hand, so the triage decision increasingly rests on a model's judgment - and the explanations Sift attaches are what your analysts will have to trust when they act on a flag.
Read the original at GreyNoise Blog ↗
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