Microsoft's Multi-Model Agentic Scanning Harness, or MDASH, is an AI security system designed to coordinate multiple models and agents for vulnerability discovery. The system has recorded an 88.45% score on the public CyberGym leaderboard, according to Microsoft's reported results, while separate evaluations identified Windows vulnerabilities and measured recall against historical Microsoft Security Response Center cases.
The important development is the agentic security pipeline itself, not an independently documented MAI-Cyber-1-Flash model. Microsoft's official MDASH security announcement describes a multi-model approach to automated security research. That framing matters for enterprises evaluating AI-assisted defense: the performance of an AI security workflow can depend on how models, tools, verification steps, and agents are orchestrated, rather than on one model alone.
Microsoft reported that MDASH found 16 CVEs during a Patch Tuesday evaluation. In a test driver containing 21 planted vulnerabilities, it found all 21 with zero false positives. The company also reported 96% recall against five years of MSRC cases for clfs.sys, plus 100% recall for tcpip.sys.
What Microsoft's MDASH results measure
