Automated detection of web-app logic bugs with AI-driven fuzzing and video proof

Automated detection of web-app logic bugs with AI-driven fuzzing and video proof targets a $8.0B = 8,000,000 businesses with web apps × $1,000 average annual spend on app security total addressable market with medium saturation and a year-over-year growth rate of 12% YoY (source: industry analyst reports and growth in application security testing and SaaS security tooling).

Key trends driving demand: AI-assisted security tooling — AI models enable more effective, context-aware reconnaissance and exploit generation, making automated logic testing feasible.; Shift-left security — developers are integrating security into CI/CD which increases demand for developer-friendly, automated scanners that reduce friction.; Demand for reproducible evidence — security and dev teams prefer findings with clear PoCs to accelerate fixes, creating value for tools that attach video repros and automated remediation hints..