I’m pretty staunchly opposed to the use of generative AI—for me, it’s the one-two punch of dubiously sourced datasets and the argument that these models can replace the human creatives they so often rip off. That said, even I’m a little bit intrigued by AI’s application in cybersecurity.
Case in point, Microsoft recently shared that it is deploying AI to “identify [issues] faster, prioritize risk, and scale vulnerability discovery across the Windows codebase” as well as “reduce the time between discovery and customer protection.” Specifically, Microsoft Security leverages a multi-model agentic scanning harness—or MDASH, for short.
MDASH uses multiple different AI models, including “leading third-party AI vulnerability discovery models,” on dedicated Cloud infrastructure to scan for vulnerabilities within Windows.
The executive vice president of Windows + Devices, Pavan Davuluri, explains, “A scanner pipeline scans critical binaries and validates candidates using multi-model debate across multiple model families. Confirmed candidates then flow to a separate, Windows-specific prove pipeline that helps eliminate remaining false positives, so only the highest-confidence findings reach the engineering team.”