Microsoft has unveiled a new multi-model artificial intelligence (AI)-driven system called MDASH to facilitate vulnerability discovery and remediation at scale, adding that it's being tested by some customers as part of a limited private preview.
MDASH, short for multi-model agentic scanning harness, is designed as a model-agnostic system that uses bespoke AI agents for different vulnerability classes to autonomously discover, validate, and prove exploitable defects in complex codebases like Windows.
"Unlike single-model approaches, the harness orchestrates more than 100 specialized AI agents across an ensemble of frontier and distilled models to discover, debate, and prove exploitable bugs end-to-end," Taesoo Kim, vice president of agentic security at Microsoft, said.
MDASH is envisioned as a "structured pipeline" that ingests a codebase and produces validated, proven findings through a series of actions.
It starts with analyzing the source code to build a threat model and attack surface, running specialized "auditor" agents over candidate code paths to flag potential issues, running a second set of "debater" agents that validate the findings, grouping semantically equivalent findings, and then finally proving the existence of the vulnerabilities.
