Microsoft recently introduced codename MDASH, a groundbreaking multi-model agentic scanning harness designed to automate the discovery and fixing of software vulnerabilities. This advanced system utilizes over 100 specialized AI agents to analyze code, outperforming single-model approaches by debating findings and proving exploitability with high accuracy. In a recent deployment, the tool successfully identified 16 security flaws within the Windows networking and authentication stacks, including several critical remote code execution vulnerabilities. Beyond finding new bugs, MDASH has demonstrated an elite 88.45% success rate on the public CyberGym benchmark and high recall against historical security cases. By orchestrating an ensemble of different AI models, Microsoft aims to provide a durable defense platform that scales with enterprise needs and improves as underlying AI technology evolves. This shift represents a transition from experimental AI research to a production-grade cybersecurity pipeline used for real-world system protection.
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