Mindgard
Automated AI red-teaming platform that discovers, tests, and defends AI models and agents against security threats.
What it does
Mindgard is an AI security platform that acts as an automated red teamer. Born from a decade of Lancaster University research, it discovers shadow AI, maps the AI attack surface, runs attacker-style reconnaissance and red-teaming against models and agents, and provides runtime protection to find and fix exploitable vulnerabilities.
How to use: Mindgard integrates into existing CI/CD automation and all SDLC stages, requiring only an inference or API endpoint for model integration. Users can book a demo to learn how to use the platform to secure their AI systems.
Core features
Automated AI red teaming
AI discovery and attack-surface mapping
Agent-native reconnaissance
Exploitable-risk detection and reporting
Runtime AI protection and response
CI/CD, Burp Suite, and API integrations
Best for
→Testing AI systems against evolving attacks
→Finding vulnerabilities in models and agents
→Securing agentic workflows in production
→AI governance and compliance reporting
Toolspool rankingby monthly traffic