Microsoft and Wiz mind-meld agents catch more than 90% of bugs
Microsoft and Wiz have developed AI-driven bug-hunting agents that demonstrate high success rates in identifying software vulnerabilities. By utilizing specialized models for specific security tasks, these systems have outperformed general-purpose AI models in automated code analysis.
Why it matters
The success of these agentic systems marks a significant advancement in cybersecurity, potentially automating the detection and remediation of zero-day exploits.
Secret to their success: Using the right model for the right security job
Two agentic bug-hunting systems from Microsoft and Google-owned Wiz show that when it comes to finding and remediating software vulnerabilities, at least two models’ minds work better than one - and Wiz tells us it’s adding a third.
Wiz on Monday said Project Atlas, its bug-hunting AI agent, bested Anthropic’s Mythos Preview and OpenAI’s GPT-5.5 Cyber with its vulnerability-analysis skills, achieving a 90.9 percent success rate on CyberGym, and uncovering more than 200 zero-day security holes in widely used open-source code.
Meanwhile, Microsoft boasted its MDASH bug-hunting harness scored a 95.95 percent success rate on CyberGym, also beating Mythos, Gemini and GPT on the same benchmark for evaluating how well AI systems find real vulnerabilities in the code.
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