Mindgard – AI Security Platform
Mindgard’s AI Security Platform combines academic research and offensive security expertise to help enterprises discover, assess, and defend AI systems. The platform operates as an autonomous red teamer that continuously…
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| Pricing | Not provided |
| Deployment | Not specified |
| Support | Not specified |
| Compliance | SOC 2 Type II |
| AI/model discovery & inventory | Yes |
| Red teaming & adversarial testing | Yes |
| Guardrails & policy enforcement | Yes |
| Continuous monitoring & drift detection | Not stated |
| Compliance & audit reporting | Yes |
| Agent & MCP security | Yes |
| Risk assessment & scoring | Yes |
Mindgard’s AI Security Platform combines academic research and offensive security expertise to help enterprises discover, assess, and defend AI systems. The platform operates as an autonomous red teamer that continuously maps, plans, and executes agentic attack workflows to reveal exploitable vulnerabilities across models, agents, tools, APIs, and connected data sources. Mindgard automates recon and intelligence gathering to identify instructions, tools, and shadow AI behaviors that increase attack surface exposure, then leverages those findings to design targeted attack chains and run adversarial evaluations. The platform supports continuous risk mapping and assessment, validation of defenses, and runtime threat detection and response that applies context-driven guardrails and hardens system prompts. Reports and remediation guidance integrate into existing development and security workflows, providing clear visibility for engineering, security teams, and auditors. Spun out of university research and compliant with enterprise expectations, Mindgard focuses on high-impact exploit discovery and prioritized remediation to reduce real-world AI risk across development and production environments.
Capabilities
| Asset Discovery (models, agents, MCP/A2A servers, shadow AI) | |
| Automated Reconnaissance and Behavioral Analysis | |
| Agentic Red Teaming (autonomous attacker emulation) | |
| Attack Chain Design and Exploitation Testing | |
| Runtime Detection & Response (context-driven guardrails) | |
| AI Security Posture Management (continuous mapping & assessment) | |
| Risk Assessment and Prioritization | |
| Model & Artifact Scanning | |
| Governance and Compliance Reporting | |
| Integrations into CI/CD, ticketing systems, and security tooling | |
| Remediation Guidance and Hardening of System Prompts |
Integrations
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Reviews
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