See why AI and security teams choose Mindgard ahead of Mend.io for visibility into their AI attack surface, measurement of AI risk and active defense of AI Systems.
See why AI and security teams choose Mindgard for attack‑driven testing, visibility across models and agents, and enterprise‑grade controls.
Map the AI attack surface to gain visibility into AI inventory and activity; reveal what attackers can find out about an organization’s AI.
Continuously red‑team models, agents, and apps across the AI lifecycle to measure risk. Assess how attackers can exploit your AI and validate fixes.
Actively defend AI. Enforce controls and policies to mitigate AI attacks at run-time. Stop attackers from breaching AI.
Below is a side-by-side comparison of Mindgard and Mend.io across key capabilities that matter to enterprise security and AI teams. Each category highlights how the two platforms approach visibility, testing, and control differently.
Feature
Winner
AI Risk Visibility
Surfaces high impact AI risks including architecture, integration and intellectual-property vulnerabilities across agents, applications and models. Provides deep, attacker-centric visibility into how AI systems behave under real adversarial pressure.
Surfaces AI components inside applications. Builds an AI bill of materials and flags risky models and dependencies in code.Surfaces AI components inside applications. Builds an AI bill of materials and flags risky models and dependencies in code.Surfaces AI components inside applications. Builds an AI bill of materials and flags risky models and dependencies in code.
Shadow AI Discovery
Surfaces a full AI asset inventory and hidden AI usage across the environment. Detects ungoverned model deployments, shadow agents, and unapproved data flows before they introduce risk.
Scans codebase and dependencies to identify AI elements, machine learning models and code generated by AI.
AI Risk Assessment
Continuous and automated AI red teaming across agents, models and applications. Identifies how attackers can exploit architectural, behavioral, and integration vulnerabilities.
Red-teams AI behavior specifically for your applications and hardens system prompts. Runs within CI/CD pipelines.
Behavioural Science
Models attacker behavior across human, linguistic, and system biases to surface vulnerabilities that static and score-based testing miss. Research-driven attack generation continuously evolves to reflect emerging AI threats.
Uses automated behavioral testing to detect unsafe model responses, prompt injection vulnerabilities, data leaks, and runtime manipulation by emulating adversarial user behavior. Focuses on application behavior rather than formal attacker behavioral science research.
AI Security R&D Talent
86% of staff on R&D team, 38% hold PhDs. Founded by Professor at Lancaster University. Research pipeline from the UK’s top AI security lab.
33% on R&D team; per People statistics on LinkedIn Sales Navigator.
Simplicity and Usability
Designed for both security engineers and AI builders, Mindgard delivers a clean, intuitive interface with clear risk visualizations, guided workflows, and one-click retesting—no steep learning curve required.
Brings together AI security, application security, and dependency management into one developer workflow. Brings AI findings into your AppSec process, enabling automated remediation and developer-centric prioritization.
AI Guardrails
Validates and continuously tests guardrail effectiveness through adversarial attacks. Focuses on measuring, stress-testing and improving guardrails rather than acting as a runtime guardrail itself.
Delivers runtime, in-application AI protection with behavior guardrails. Monitors AI in-production activity, enforces security policies and prevents unsafe behavior.
Attack-Driven Testing
Continuously red-teams models, agents, and applications through attack-driven testing that covers jailbreaks, data exfiltration, and prompt injection. Supports multi-turn adversarial chains with reproducible results to validate fixes.
Automated AI red teaming tests prompt injection, data leaks, jailbreaks, and other AI-native attacks on every build to validate application security prior to release.
Runtime Detection & Policy
Provides inline detection with granular enforcement controls (block/alert/enrich) for prompt injection, data leakage, and tool misuse.
Runtime monitoring and behavioral control between human users and AI systems. Detects unsafe use and enforces configurable security policies at runtime.
Enterprise Controls
Delivers enterprise-grade governance with granular permissions, policy enforcement, detailed audit trails, and full SAML/SSO, SCIM, and RBAC support. Aligns security testing with organizational compliance and reporting standards.
Includes centralized governance via AI-BOM, SBOM, proof of compliance, policy management, audit-friendly workflows, and consolidated security reporting to simplify compliance with regulations such as the EU AI Act and EU Cyber Resilience Act.
Integrations
Integrates seamlessly across developer and security workflows, including CI/CD pipelines, IDE hooks, SIEM, and ticketing systems. The first AI red teaming solution with a native Burp Suite integration, enabling red teams to extend attack-driven testing into familiar tooling.
Integrates into your existing AppSec and developer workflows including CI/CD pipelines, source code repositories, dependency management systems, and automated remediation platforms.
Deployment Options
Most flexible: SaaS, Private cloud, Customer‑managed. On-prem available for certain use cases.
Offers cloud, self-hosted (VPC), and on-premises deployment options.
Reporting & Scorecards
Provides comprehensive reporting that connects testing outcomes to business risk. Teams can assess how attackers could exploit their AI, validate defenses, and evidence compliance through detailed scorecards, trend analytics, and executive summaries.
Provides risk scoring and reporting for GenAI systems and MCP servers, including parameter breakdowns and certification status checks. Supports pass/fail dashboards for guardrail enforcement and tracks AI interaction trends.
Support & Partnership
Customers gain a dedicated success team backed by world-class AI security researchers. Mindgard provides hands-on guidance informed by active attack research, helping enterprises apply the latest insights to their own AI environments and continuously strengthen defenses.
Prompt Security’s CEO & Co-founder is a core member of the OWASP research team. Offers standard enterprise customer support.
Pricing Model
Contact sales for tailored pricing.
Contact sales for pricing.
Powered by the world's most effective attack library for AI, Mindgard enables red teams, security and developers to swiftly identify and remediate AI security vulnerabilities.
Don’t just take our word for it, see how offensive security teams rate the experience across platforms.
CEO at AI software company
Red teamer at F500 bank
G2 Review
Purpose-built features that surface AI security threats that really matter.
Extend offensive testing into familiar workflows. Mindgard’s native Burp Suite integration lets red teams chain AI-specific attacks, validate exploits, and report findings directly within their existing toolset.
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Turn findings into fixes with guided remediation workflows. Automatically reproduce vulnerabilities, validate patches, and document risk reduction for auditors and leadership
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Test beyond text with coverage for vision, audio, and multi-modal models to uncover cross-channel vulnerabilities that attackers can exploit.
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Plug into CI/CD pipelines, IDEs, SIEM, and ticketing systems to bring AI risk visibility and testing automation into every stage of development and security operations.
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The world’s most effective library of jailbreaks, data exfiltration methods, and prompt injection chains—curated from ongoing research and field testing to mirror the latest real-world threats.
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Align findings to emerging frameworks like OWASP Top 10 and MITRE ATLAS, translating technical vulnerabilities into compliance-ready evidence.
Learn More >View and learn more about Mindgard's features, data handling capabilities, or integration options.
Mindgard, the leading provider of AI security solutions, helps enterprises discover, assess, and defend their AI systems. Spun out from over a decade of AI security research at Lancaster University and headquartered in Boston and London, Mindgard combines AI red teaming with offensive security expertise and AI research to identify exploitable vulnerabilities in AI models, agents, and applications before attackers do.
