Mindgard AI Security Risk Discovery & Assessment is a platform designed to identify and assess security risks in AI systems. The product provides continuous mapping of AI attack surfaces to discover shadow AI and evaluate risk exposure across AI deployments. The platform performs automated AI red teaming at scale, generating adversarial attacks and chained attack behaviors to test models, agents, and applications. It includes run-time artifact scanning capabilities to monitor AI systems in live production environments. Mindgard validates security controls by testing guardrails, safety filters, and access controls against attack techniques. The platform identifies control gaps and provides hardening guidance to strengthen defensive measures. The product generates unified reports with validated findings and governance-aligned documentation for stakeholders and auditors. It supports integration into CI/CD pipelines through GitHub Actions, enabling automated security testing as part of the development workflow. The platform tests for various attack vectors including character transformations and algorithmic evasion techniques that can bypass LLM guardrails. It provides structured, repeatable assessments that adapt to system changes over time.