Audience
Security and engineering teams that need to detect, validate, prioritize, and automatically fix vulnerabilities across software repositories with agentic AI
About Codename MDASH
Codename MDASH is an agentic code scanner in Microsoft Defender that uses a multi-model AI system to detect, validate, and remediate vulnerabilities with greater depth than traditional static analysis. It extends Defender CLI with a multistage pipeline in which specialized agents collaborate across four stages. Prepare ranks files by risk using call-graph analysis and code-complexity metrics, prioritizing functions most likely to contain vulnerabilities. Scan sends ranked code to more than 100 expert agents, including injection, memory-safety, and auth-bypass auditors, with each agent focused on a specific vulnerability class. Validate combines taint analysis, type resolution through Language Server Protocol servers, and multi-model agentic debate to refine confidence and reduce false positives. Dedup consolidates overlapping results into a final set of unique actionable findings.
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Integrations
Company Information
Microsoft
Founded: 1975
United States
learn.microsoft.com/en-us/security-exposure-management/ai-code-security-overview
Videos and Screen Captures
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Product Details
Platforms Supported
Cloud
Training
Documentation
Support
Online
Codename MDASH Frequently Asked Questions
Q: What kinds of users and organization types does Codename MDASH work with?
Codename MDASH works with these users and organization types: Mid Size Business, Small Business, Enterprise, Freelance, Nonprofit, Government, and Startup.
Q: What languages does Codename MDASH support in their product?
Codename MDASH supports these languages: English.
Q: What kind of support options does Codename MDASH offer?
Codename MDASH offers support via online.
Q: What other applications or services does Codename MDASH integrate with?
Codename MDASH integrates with: MAI-Cyber-1-Flash.
Q: What type of training does Codename MDASH provide?
Codename MDASH provides training in the form of documentation.
