Mindgard AI Security Platform

What it does

Mindgard is an AI security platform that takes in AI systems to assess, including models, agents, applications, APIs, data sources and connected tools. It produces attacker-style reconnaissance findings, reproducible attack paths with evidence, prioritized vulnerability reports and remediation guidance, plus retest results after fixes.

Teams use it to run automated and expert-led red teaming before deployment and continuously as models, prompts, tools or permissions change. Its distinct approach starts with reconnaissance to map an AI system's behavior and attack surface, then plans and runs adaptive, multi-step attacks rather than fixed payload checklists. Findings can be routed into CI/CD pipelines, SIEM and ticketing systems.

Mindgard suits security, engineering and GRC teams responsible for AI systems in production or preproduction. Access is through a demo request and enterprise scoping; testing requires a controlled scope with defined environments, credentials and permitted actions, and architecture review with Mindgard's security team. It is not a self-serve tool, and red teaming does not replace guardrails or fully prove a system is secure.

What it can do

• AI asset discovery of models, agents, MCP/A2A servers and connected tools
• Attacker-led reconnaissance to profile guardrails, tools and behavior
• Automated and expert-led agentic red teaming including multi-step attack chains
• Evidence-backed findings with reproduction steps and attack path context
• Continuous reassessment and retesting of fixes as AI systems change
• Mapping findings to OWASP LLM Top 10, MITRE ATLAS, NIST AI RMF and EU AI Act

Works with

• CI/CD pipelines
• GitHub Actions
• Burp Suite
• SIEM platforms
• Ticketing systems
• APIs and IDE hooks

Before you choose

• Testing requires a defined scope, credentials and architecture review, so it is not immediately usable without enterprise onboarding.
• Guardrails are not a replacement; red teaming tests whether controls can be bypassed.
• Pricing is not published; cost depends on environment and requirements.

Listed under

• Security
• AI and agent security
• AI agents
• AI asset discovery
• AI security
• Compliance
• Enterprise
• Red teaming

Get started

Scope is agreed with Mindgard's security team before testing begins; the route to start is a demo request.

1. Book a demo and choose the AI system, environment (preproduction or production) and testing cadence.
2. Define controlled test scope: environments, credentials, permitted actions and operating limits.
3. Review endpoint, authentication, deployment and data-handling requirements with the Mindgard security team, then connect via APIs or CI/CD.

Mindgard states that pricing is based on each organization's environment and requirements. Buyers should request a quote through a demo to confirm cost, seat or usage terms.

Mindgard AI Security Platform doesn’t publish prices. You get a quote by contacting sales. See their pricing page ↗

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

• AI Security Software: Advanced AI Testing Tools - Mindgard ↗mindgard.ai
• Automated AI Red Teaming Platform - Mindgard ↗mindgard.io
• AI Runtime Threat Detection and Response ↗mindgard.io
• AI Reconnaissance & Shadow AI Discovery Tool - Mindgard ↗mindgard.io

Company website

mindgard.ai: product, pricing and policy pages

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Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.