AI Secured

Mindgard is an automated AI security testing platform offering red team-like assessment and continuous security testing across the AI software development life cycle. It targets AI-driven products and systems (including Generative AI, LLMs, NLP, audio, image, and multi-modal assets) to identify and remediate risks that traditional application security tools often miss. Mindgard emphasizes runtime detection of AI-specific threats, supports integration into existing CI/CD and SIEM workflows, and provides an extensive, research-backed attack library to help organizations harden their AI assets before and after deployment.

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Key Capabilities

• Automated AI red teaming: simulate realistic attacker scenarios to uncover AI-specific vulnerabilities without manual intervention.
• Runtime risk detection: continuous security testing that identifies issues that only appear when models are deployed.
• Model and stack agnostic: supports a wide range of AI models and toolchains (open source, private, third-party, and popular LLMs such as ChatGPT).
• Broad coverage: addresses risks across image, audio, NLP, and multi-modal systems, not just text-based models.
• CI/CD and SecOps integration: plugs into existing development and operations workflows and SIEM systems.
• Threat intelligence and attack library: large catalog of AI attack vectors (e.g., jailbreaking, prompt injection, extraction, evasion, inversion, poisoning).
• GDPR compliant with ongoing security certifications: GDPR-compliant data handling with anticipated ISO 27001 certification.
• Scales from small to enterprise deployments: designed for organizations of varied sizes and industries.

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How Mindgard Works

1. Integrates into your AI SDLC and requires only an inference or API endpoint for model integration.
2. Leverages a large, PhD-led threat library to autonomously simulate AI attacks across models and pipelines.
3. Performs automated red teaming and continuous testing, delivering actionable findings and remediation guidance.
4. Outputs can feed into existing reporting and SIEM systems for ongoing risk management.
5. Supports testing across diverse AI assets, including Generative AI, LLMs, NLP, audio, image, and multi-modal models.

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Use Cases

• Proactive AI security testing during development and deployment.
• Continuous monitoring of AI models in production for new vulnerabilities.
• Validation of guardrails, prompts, and model behavior against adversarial inputs.
• Compliance-focused security assessments for regulated industries leveraging AI.

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Safety and Compliance Considerations

• Designed to help organizations identify and mitigate AI-specific risks while maintaining responsible disclosure and remediation practices.
• GDPR-compliant data handling; aiming for ISO 27001 certification in early 2025.

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How to Get Started

• Book a demo to see Mindgard in action and discuss how it can fit into your AI security strategy.
• Explore integration options with your existing CI/CD pipelines and SIEM platforms.
• Leverage Mindgard’s AI attack library to benchmark and improve your security posture over time.

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Why Mindgard Stands Out

Mindgard positions itself as a dedicated AI security testing solution that bridges a gap left by traditional AppSec tools by focusing on runtime AI risks, model agility, and automation across the AI lifecycle. It emphasizes continuous testing, broad model support, and an extensive, research-driven attack library.

Core Features

• Automated AI red teaming across the AI lifecycle (development, deployment, and production)
• Continuous security testing with runtime risk detection
• Neural network agnostic: supports Generative AI, LLMs, NLP, audio, image, and multi-modal models
• CI/CD and SIEM integrations for streamlined security operations
• Large attack library covering jailbreaking, extraction, evasion, inversion, poisoning, prompt injection, and more
• GDPR-compliant data handling with anticipated ISO 27001 certification
• Scalable for organizations of any size and industry
• Expert threat research backing and ongoing updates to the attack catalog