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Description
Codename MDASH represents an advanced code scanning tool integrated within Microsoft Defender, leveraging a multi-modal AI framework to uncover, verify, and address vulnerabilities with a level of insight that surpasses conventional static analysis methods. This system enhances the Defender CLI by introducing a multistage process where specialized agents work collaboratively through four distinct phases. Initially, the preparation stage organizes ranked files based on risk, utilizing call-graph analysis and evaluating code complexity to identify functions with the highest likelihood of containing vulnerabilities. The scanning phase then transmits this prioritized code to over 100 specialized agents, including those focused on injection flaws, memory safety issues, and authentication bypasses, ensuring each agent targets a specific category of vulnerability. Following this, the validation phase employs taint analysis, type resolution through Language Server Protocol servers, and a debate among multi-model agents to improve confidence levels and minimize false positives. Finally, the deduplication step merges overlapping findings into a comprehensive set of unique and actionable results, enhancing the overall efficiency of vulnerability management processes. This innovative approach signifies a new era in threat detection and remediation within software development.
Description
Mindgard, the leading cybersecurity platform for AI, specialises in securing AI/ML models, encompassing LLMs and GenAI for both in-house and third-party solutions. Rooted in the academic prowess of Lancaster University and launched in 2022, Mindgard has rapidly become a key player in the field by tackling the complex vulnerabilities associated with AI technologies. Our flagship service, Mindgard AI Security Labs, reflects our dedication to innovation, automating AI security testing and threat assessments to identify and remedy adversarial threats that traditional methods might miss due to their complexity.
Our platform is supported by the largest, commercially available AI threat library, enabling organizations to proactively protect their AI assets across their entire lifecycle. Mindgard seamlessly integrates with existing security ecosystem platforms, enabling Security Operations Centers (SOCs) to rapidly onboard AI/ML solutions and manage AI-specific vulnerabilities and hence risk.
API Access
Has API
API Access
Has API
Integrations
MAI-Cyber-1-Flash
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
Test drive the Mindgard AI Security Labs platform in our controlled, sandbox environment — Zero commitments.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Microsoft
Founded
1975
Country
United States
Website
learn.microsoft.com/en-us/security-exposure-management/ai-code-security-overview
Vendor Details
Company Name
Mindgard
Founded
2022
Country
United Kindom
Website
mindgard.ai/
Product Features
Product Features
Cybersecurity
AI / Machine Learning
Behavioral Analytics
Endpoint Management
IOC Verification
Incident Management
Tokenization
Vulnerability Scanning
Whitelisting / Blacklisting