Agent-native reconnaissance
Maps models, agents, tools, behaviors, guardrails, and connected infrastructure the way an attacker would, before attack execution.
Mindgard
ClaimMindgard is an AI security platform for discovering, assessing, red teaming, and protecting AI models, agents, and applications for enterprise AI systems.
MindgardOverview
Mindgard is an AI security platform for discovering, assessing, red teaming, and protecting AI models, agents, and applications. The site frames it as an attacker-aligned system that maps the AI attack surface, surfaces exploitable risk, and supports continuous analysis and runtime protection.
The product combines AI discovery and reconnaissance, assessment, red teaming, and defense into one workflow. It is positioned for teams that need to understand how AI systems behave, what they connect to, and where they can be exploited, including systems built on open source models or managed AI platforms.
Core capabilities
Shadow AI discovery and inventory reporting
Generates AI inventory risk reports that enumerate tool calls, identify shadow AI, and centralize findings for governance and executive reporting.
AI assessment and red teaming
Tests models, agents, and applications through realistic, multi-step scenarios using attacker-aligned datasets and attack libraries.
Control and prompt security validation
Checks guardrails, safety filters, and access controls against attack-style behavior, including prompt injection and unsafe tool use.
Risk reporting and remediation evidence
Produces unified reporting with validated findings and remediation guidance for security and governance workflows.
Operational deployment options
Supports deployment through CI/CD, Burp Suite, or a single click, with APIs and enterprise workflow integration support.
Common use cases
Map the AI attack surface
Security teams can build an inventory of models, agents, tool calls, and shadow AI to understand what is deployed and where exposure exists.
Run AI red teaming at scale
Red teams can run contextual, chained attacks to pressure-test AI systems and uncover vulnerabilities that matter in practice.
Document and report AI risk
Governance and risk teams can produce defensible reports for executive review, audits, and control validation based on unified findings.
Harden controls and prompts
App and platform teams can validate guardrails, access controls, and system prompts against prompt injection and unsafe tool use.
Protect AI in production
Operations teams can monitor deployed AI systems with runtime protection to identify and respond to attacks in real time.
Pros and Cons
Pros
- Covers the full workflow from discovery and assessment through red teaming and runtime protection.
- Focuses on attacker-style reconnaissance and exploitable risk rather than generic scan noise.
- Provides concrete outputs such as inventory risk reports, attack-surface mapping, and unified findings.
- Can be deployed through CI/CD, Burp Suite, or a single click.
- Built on long-running AI security research and references 100+ public disclosures.
Cons
- The pricing page text provided does not include public prices or plan details.
- Specific third-party integrations are not listed in the provided source text.
FAQ
What does Mindgard do?
Mindgard is used to discover, assess, and red team AI models, agents, and applications. Its pages describe reconnaissance, assessment, red teaming, and runtime protection as parts of the same platform.
How is Mindgard deployed or integrated?
The site says teams can deploy through CI/CD, Burp Suite, or a single click. It also describes APIs and enterprise workflow integrations, but does not list specific third-party vendors on the pages provided.
What kind of outputs does it produce?
Mindgard supports AI discovery and reconnaissance, AI assessment, AI red teaming, and runtime protection. The pages describe outputs such as AI inventory risk reports, attack-surface mapping, validated findings, and governance-aligned reporting.
How is Mindgard priced?
The pricing page does not show public plan prices in the provided text. The site instead presents a demo-led sales flow with a Book a Demo call to action.
Who is Mindgard for?
The product is positioned for enterprises and teams working on AI systems, agents, applications, and infrastructure. The pages mention open source models and managed AI platforms, but do not narrow the audience to one specific department.
Quick Facts
- Category
- AI security platform
- Primary focus
- Automated AI red teaming, assessment, reconnaissance, and runtime protection
- Deployment
- CI/CD, Burp Suite, or single-click deployment
- Pricing
- Demo-led; no public prices shown in the provided text
- Users
- Enterprises securing AI models, agents, applications, and infrastructure
- Source domain
- mindgard.ai