Mindgard DAST-AI (Dynamic Application Security Testing for AI)

Additional Info

CompanyMindgard
Websitemindgard.ai
Company size (employees)10 to 49
Headquarters RegionEurope

Overview

For organizations building or adopting AI, Mindgard offers the first and only Dynamic Application Security Testing for AI (DAST-AI) solution specifically designed to detect and remediate AI-specific vulnerabilities that are only detectable at runtime. It enables enterprises to secure their AI systems against emerging threats that traditional application security tools cannot address.

Unlike WAFs or source code scanners, Mindgard empowers security teams, penetration testers, and developers to continuously identify and mitigate vulnerabilities throughout the entire AI lifecycle. Once deployed, Mindgard’s DAST-AI provides ongoing protection as new threats emerge. It identifies risks that static code analysis or manual testing cannot detect, reducing testing times from months to minutes. Additionally, DAST-AI validates the effectiveness of guardrail and WAF solutions. Its extensive model coverage goes beyond LLMs to include image, audio, and multimodal systems.

Mindgard integrates seamlessly into existing CI/CD pipelines and all stages of the SDLC, requiring only an inference or API endpoint for model integration. It enables red teams to scale by deploying standard visibility and controls across their areas of responsibility. Test results can be mapped to threat models and integrated into existing security workflows, providing actionable and auditable AI security for compliance teams. The solution also supports MITRE and OWASP-compatible security posture reporting.

Founded in a leading UK university lab, Mindgard is backed by over a decade of rigorous AI security research and partnerships. Its PhD-led R&D team has developed threat intelligence covering thousands of unique AI attack scenarios, delivering timely, data-driven recommendations for effective remediation.

Key Capabilities / Features

Mindgard’s platform allows enterprises to secure their AI systems without slowing down innovation. It ensures organizations can test, monitor, and address risks effectively, making AI adoption safer and more reliable. DAST - AI delivers clear benefits by addressing the unique challenges of securing AI systems for enterprise security teams:


Uncovers hidden vulnerabilities: DAST AI identifies AI-specific risks like prompt injections, model theft, and data leaks, allowing organizations to address them before they become serious issues.


Saves time and effort: Automated AI security testing reduces manual work and minimizes the need for specialized expertise. Organizations can integrate DAST AI into their existing workflows, making security testing faster and more efficient.


Improves security visibility: Security teams gain detailed insights into AI risks across their organization. Penetration testers, security analysts, and developers can work together to address vulnerabilities effectively.


Simplifies compliance: Features like MITRE ATLAS Adviser help organizations meet regulatory and reporting requirements. By standardizing AI security testing, teams can simplify audits while maintaining visibility into AI risks.


Supports safe AI adoption: By identifying and remediating vulnerabilities, organizations can confidently adopt AI technologies without compromising sensitive data, intellectual property, or business reputation.


How we are different

Tech: Continuous & Comprehensive SaaS-Based AI Security Testing and Threat Intelligence
Built from the ground up to find and remediate AI-specific vulnerabilities. Customers deploy Mindgard’s DAST-AI once and benefit from ongoing protection as new threats surface. DAST-AI identifies risks that static code or manual testing cannot detect, reducing testing times from months to minutes. DAST-AI validates the efficacy of guardrail/WAF solutions. Extensive model coverage beyond LLMs, including image, audio, and multimodal.


Process: Integration into How You Work Today
Mindgard is designed to integrate smoothly into existing CI/CD Automation and all SDLC stages, requiring only an inference or API endpoint for model integration. The solution enables red teamers to scale themselves by deploying standard visibility/controls out across the teams they're responsible for. Map the test results into the context of your threat models in your existing security workflows.


People: Unmatched Academic and Research Roots and Branches
Founded in a leading UK university lab, Mindgard boasts over 10 years of rigorous research in AI security, with public and private partnerships that ensure access to the latest advancements and the most qualified talent in the field. Mindgard’s threat intelligence, developed with PhD-led R&D, covers thousands of unique AI attack scenarios, supporting timely and data-driven remediation recommendations.


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