Mindgard

Mindgard is an offensive AI security company that provides continuous, automated red teaming and security testing for enterprise AI and generative AI systems. Spun out of more than a decade of AI security research at Lancaster University, the platform helps organizations discover shadow AI, map their AI attack surface, and validate risk before and after deployment. Mindgard's approach centers on agent-native reconnaissance, profiling models, agents, tools, and behaviors the way an attacker would prior to launching simulated attacks such as prompt injection, jailbreaks, data extraction, and model evasion. The product spans AI discovery and reconnaissance, red teaming, vulnerability assessment, model scanning, runtime protection, and governance reporting, integrating into CI/CD pipelines so testing runs continuously rather than as a one-off audit. It targets enterprise security teams and organizations deploying LLMs and open-source models that lack in-house adversarial AI expertise. The company's research team has published more than 100 public vulnerability disclosures across major AI systems, distinguishing Mindgard as a research-led vendor. It is designed for security teams that need attacker-perspective validation of AI risk at scale.