Codename MDASHMicrosoft
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Related Products
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About
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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About
Mindgard is the leader in AI red teaming, helping enterprises identify, assess, and mitigate real-world security risks across AI models, agents, and applications. Founded on pioneering research in AI security, Mindgard was built on the insight that traditional application security approaches cannot protect systems that are probabilistic, adaptive, and deeply embedded into business workflows.
As organizations deploy GenAI and agentic systems at scale, risk increasingly emerges from how AI behaves, what it connects to, and how attackers can manipulate those interactions. Mindgard addresses this challenge with an attacker-aligned approach that mirrors how real adversaries perform reconnaissance, map attack surfaces, exploit system behavior, and pivot through tools, data, and infrastructure. Rather than testing models in isolation, Mindgard evaluates full AI systems in context to surface vulnerabilities with real security impact.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
DevSecOps teams managing large polyglot repositories that need deeper vulnerability detection and AI-assisted remediation inside existing delivery pipelines
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Audience
Cybersecurity teams interested in a platform that uncovers cyber threats against Artificial Intelligence
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
Free
Test drive the Mindgard AI Security Labs platform in our controlled, sandbox environment — Zero commitments.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationMicrosoft
Founded: 1975
United States
learn.microsoft.com/en-us/security-exposure-management/ai-code-security-overview
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Company InformationMindgard
Founded: 2022
United Kindom
mindgard.ai/
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Categories |
Categories |
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Cybersecurity Features
AI / Machine Learning
Behavioral Analytics
Endpoint Management
Incident Management
IOC Verification
Tokenization
Vulnerability Scanning
Whitelisting / Blacklisting
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Integrations
MAI-Cyber-1-Flash
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