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Mindgard

Mindgard is an attack-led AI security platform that continuously red-teams AI agents and systems, finds and validates high-impact AI vulnerabilities, and adds runtime protection, built on Lancaster University research.

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Introduction

Mindgard tests AI agents and systems against evolving attacks, finding, validating and fixing high-impact AI vulnerabilities. Its modules include AI recon, red teaming, assessment, runtime protection, offensive security, threat response and governance and compliance.

The company grew out of more than a decade of AI security research at Lancaster University and says its technology has identified more than 150 publicly disclosed vulnerabilities in prominent AI systems, including issues in Google’s Antigravity IDE. It integrates via APIs and CI/CD.

Before buying an AI security platform, list the AI systems you actually run, such as chatbots, internal agents and model APIs, and the attacks you care about most, like prompt injection or data leakage. Then ask Mindgard to demonstrate red-team results against one of those systems, not a generic demo.

Features

  1. Continuous AI red teaming: Against evolving attacks.
  2. AI recon: Map your AI attack surface.
  3. Runtime protection: Defend live systems.
  4. CI/CD support: Test before release.
  5. Governance: Policy compliance.

Pros

  1. Research depth: Academic and disclosure record.

Cons

  1. Enterprise focus: No public pricing.
  1. Register AI endpoints or agents.
  2. Run red-team assessments in CI.
  3. Add runtime protection for production.

Resources:

Pricing

Prices were not listed on the website when checked on 11 November 2026; contact the vendor for plans.

  1. Enterprises deploying LLM apps and agents.

Conclusion

Mindgard is a research-led AI red-teaming platform.

Compare it with open-source scanners like garak for coverage.

On CheckOps, Mindgard is filed under the Security testing and Production monitoring & observability stages. Related tools listed here include garak, PyRIT, DeepTeam, Lakera, Promptfoo and Giskard. Which one fits best depends mostly on your stack, your team’s size and skills, and whether you prefer to run tools yourself or pay for a managed service. This page reflects the official website, documentation and repository as they stood on 11 November 2026.

Alternatives

Other tools on CheckOps that cover similar ground. Open a page, or compare one with Mindgard side by side.