Mindgard

Mindgard is an AI security platform designed to discover, assess, and defend AI systems and agents in production environments. Its primary function is to mitigate risks in critical applications through an automated red teaming approach, allowing companies to identify high-impact AI vulnerabilities before they are exploited by third parties. This tool is essential for cybersecurity teams, machine learning engineers, and developers who need to secure Large Language Models (LLMs), agentic workflows, and complex AI infrastructures.

Mindgard’s technology is built on over a decade of offensive security research conducted at Lancaster University. Unlike traditional security scans, it uses an agent-native reconnaissance approach that maps the attack surface just as a real adversary would, analyzing models, tools, and behaviors. The platform is powered by a proprietary knowledge base of over 150 public vulnerabilities detected in leading systems such as OpenAI Sora, Google Antigravity, and xAI Grok, enabling continuous and deep analysis of hidden behaviors and control paths that conventional software misses.

The tool's key capabilities are divided into four functional pillars:

• Discovery and Visibility: Identifies Shadow AI (unauthorized AI) and generates an AI-BOM (AI Bill of Materials) to understand all components and the infrastructure's risk exposure.
• Advanced Reconnaissance: Performs AI attack surface enumeration and psychometric profiling of agents to detect weaknesses in security barriers or guardrails.
• Automated Red Teaming: Executes offensive security tests and simulated attacks to verify regulatory compliance and generate risk compliance reports.
• Real-time Protection: Offers runtime defense and automated system hardening to stop attacks before they have a real impact on the company’s computers or servers.

Mindgard’s unique value lies in its ability to transform academic research into practical operational security. It integrates natively into existing workflows through APIs, CI/CD support, and tools like Burp Suite, allowing security assessments to be performed up to ten times faster than manual methods. By focusing on exploitable risks rather than just statistical noise, the platform helps organizations deploy AI applications securely, protecting them against soft elicitation techniques, prompt injections, and other emerging threats in the artificial intelligence ecosystem.