Advanced computational challenge system that uses mathematical problems and behavioral analysis to distinguish AI from humans with 92% accuracy
Uses computational challenges and behavioral analysis to classify users based on solution methodology and response patterns
Eigenvalue computation, matrix determinants, and prime factorization problems that reveal computational vs manual solving patterns
Tracks response times, mouse movements, typing patterns, and interaction behaviors to identify automated systems
Multi-dimensional analysis including solution accuracy, response timing, and behavioral data for 92% classification accuracy
Comprehensive analytics dashboard with CSV/JSON export, behavioral insights, and real-time classification metrics
JWT authentication, rate limiting, encryption, and comprehensive security scanning with production monitoring
High-performance async API with PostgreSQL storage, Redis caching, and AWS infrastructure deployment
Each challenge type targets specific computational capabilities and response patterns
2×2 to 5×5 matrices - Tests linear algebra knowledge and computational method detection
SHA256 puzzles with 2-5 leading zeros - Identifies automated systems and resource allocation patterns
3×3 to 6×6 matrices - Distinguishes manual calculation from automated solving methods
16-bit to 28-bit numbers - Evaluates algorithmic sophistication and computational resources
AI Classification Accuracy
Average AI Response Time
Challenge Types Available
Scalable Infrastructure
Get notified about updates, research findings, and new challenge types
For technical inquiries: contact@nohcaptcha.com