Map your AI attack surface, measure and validate your risk, actively defend your AI.
Map your AI attack surface, measure and validate your risk, actively defend your AI.
Join others Red Teaming their AI
AI introduces risks that traditional security tools cannot detect, leaving organizations unable to find, measure, or secure their AI. Security teams struggle with a lack of visibility into AI activity and its attack surfaces. Difficulty reproducing agentic AI behavior creates uncertainty and compliance challenges. Ultimately, an inability to enforce AI controls heights the risk of compromise.
of organizations have adopted GenAI in critical business processes.
of enterprises with AI systems have already reported security breaches.
of organizations are actively working to mitigate AI risk.
Mindgard delivers AI detection and response through attack-driven defense, giving enterprises the ability to map their AI attack surface, measure and validate AI risk, and actively defend their AI.
AI Security Lab at Lancaster University founded in 2016. Mindgard commercial solution launch in 2022.
Mindgard’s threat intelligence, developed with PhD-led R&D, covers thousands of unique AI attack scenarios.
Integrates into existing CI/CD automation and all SDLC stages, requiring only an inference or API endpoint for model integration.
Organizations big and small, from the world’s biggest purchasers of software to fast growing AI-native companies.
Works with the AI models and guardrails you build, buy and use. Extensive coverage beyond LLMs, including image, audio, and multi-modal. Whether you are using open source, internally developed, 3rd party purchased, or popular LLMs like OpenAI, Claude, Bard, we’ve got you covered.
Whether you're just getting started with AI Security Testing or looking to deepen your expertise, our engaging content is here to support you every step of the way.
View and learn more about Mindgard's features, data handling capabilities, or integration options.
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