See why AI and security teams choose Mindgard over Robust Intelligence (acquired by Cisco Systems) 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 Robust Intelligence 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. Works across agents, applications and models.
Focuses primarily on model-level validation and policy checks. Limited visibility into agents, apps, or the broader AI ecosystem.
Shadow AI Discovery
Surfaces AI asset inventory and hidden AI usage. Detects ungoverned model deployments and unapproved data flows.
No Shadow AI discovery capabilities; does not inventory or track unapproved AI usage.
AI Risk Assessment
Continuous and automated AI red teaming across agents, models and applications. Assess how attackers can exploit AI.
Focused on pre-deployment “AI Firewall” scanning and guardrail evaluation. Lacks adversarial or exploit-based testing.
Behavioural Science
Models attacker behavior across human, linguistic, and system biases to surface vulnerabilities that static testing misses.
No behavioral or social-engineering–based testing capabilities.
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.
60% 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.
Focused on enterprise policy controls; setup and configuration can be complex for red-team workflows.
AI Guardrails
Nascent capabilities
Core “AI Firewall” provides guardrail enforcement and input/output filtering.
Attack-Driven Testing
Continuously red-teams models, agents, and applications through attack-driven testing—covering jailbreaks, data exfiltration, and prompt injection. Supports multi-turn adversarial chains with reproducible results to validate fixes.
Does not conduct attack-driven testing. Focuses on static scanning, dataset validation, and compliance-style testing.
Runtime Detection & Policy
Provides inline detection and enforcement for prompt injection, data leakage, and tool abuse with configurable block/alert/enrich options.
Enforces guardrail policies at runtime but limited to rule-based filtering without adaptive threat detection.
Enterprise Controls
Delivers enterprise-grade governance with granular permissions, policy enforcement, and detailed audit trails. Supports SAML/SSO, SCIM provisioning, and RBAC to align security testing with organizational compliance standards.
Offers mature enterprise integrations and identity controls through Cisco’s broader security ecosystem, including SSO, RBAC, and centralized policy management.
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 with common ML pipelines and data-science platforms but lacks red-team or offensive-security tool integrations.
Deployment Options
Most flexible: SaaS, Private cloud, Customer‑managed. On-prem available for certain use cases.
Robust Intelligence is being integrated into Cisco Systems product and sales lines.
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.
Offers standard dashboards and guardrail compliance summaries; lacks attacker-centric or trend-based metrics.
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.
Standard enterprise support with customer success coverage; limited collaboration on emerging threat research. G2 reviews show mixed feedback on Cisco Systems support, with some users praising its responsiveness, while others report long wait times and issues with specialized support.
Pricing Model
Contact sales for tailored pricing.
Cisco Systems pricing is complex because of integrations and opacity of partner channel networks.
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
Security Lead at F500 Pharma
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.
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