Secure AI systems against emerging threats traditional tools miss
Mindgard automatically tests AI systems for security vulnerabilities like prompt injection and data extraction through automated red teaming. It helps enterprises safely deploy generative AI and large language models by identifying risks during runtime. The platform integrates with existing security systems to provide continuous protection across the AI development lifecycle.
Simulates AI attacks to find vulnerabilities automatically
Largest collection of GenAI attack scenarios
Detects threats that only appear during AI operation
Works with LLMs, image models, and neural networks
Connects to existing security monitoring systems
Combines 10+ years of academic research with the largest AI attack library for runtime-specific threat detection
Yes, supports LLMs, image models, NLP systems, and multi-modal AI
GDPR compliant with ISO 27001 certification expected in 2025, uses own platform for security testing
This tool is best for:
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Recent data shows that Mindgard has 42.6K monthly visits (-3.8% decrease from the previous month), 44.0% bounce rate, and average 1.81 pages per visit.
Traffic is primarily driven by 6 different sources, with users from 5 countries worldwide, led by United States contributing 24% of total traffic. SEO performance is shown by 5 tracked keywords, with "mindgard" being the top-performing keyword with 1.0K monthly searches. See below for more info.
Monthly Visits
42.6K
Pages per Visit
1.81
Bounce Rate
44.0%
Average Time on Site
16s
| SEO Keyword | Volume | CPC |
|---|---|---|
| mindgard | 1.0K | $4.00 |
| red teaming ai speaker critical | 300 | - |
| mindgard attack methods | 90 | - |
| ai penetration testing | 1.2K | $1.55 |
| ai pentest | 750 | - |
| Source | Traffic Share |
|---|---|
| Direct | 42% |
| Search | 38% |
| Social | 6% |
| Referrals | 12% |
| Paid Referrals | 1% |
| Country Name | Traffic Share |
|---|---|
 | 24% |
 | 9% |
 | 7% |
 | 5% |
 | 5% |
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