AI-Powered Web Vulnerability Scanner: Build It From Scratch

  Every web application has security headers, cookies, TLS configurations, and CORS policies that need to be correct. Most teams find out they're wrong only after a penetration test — or worse, after an incident.   This book shows you how to build a scanner that catches these issues automatically.   You'll create a Python CLI tool that uses Hurl (declarative HTTP testing) to assert security properties, SSLyze to validate TLS protocol versions, and AI to generate specific remediation for every failure it finds. The output: structured JSON reports, visual HTML dashboards, and AI-generated security posture assessments.   **What you'll build:**   - 9 declarative Hurl security test files (headers, cookies, CORS, HSTS, CSP, CSRF, redirects, TLS) - A preprocessor that handles domain substitution and authentication - An output parser with built-in remediation guidance for every test - A TLS scanner validating SSL 2.0/3.0 disabled and TLS 1.2/1.3 enabled - An AI analyzer that generates context-specific fixes using Ollama, OpenAI, or Bedrock - An HTML reporter with dark-themed visual dashboards - Docker multi-architecture deployment - CI/CD pipeline with GitHub Actions   **Who this is for:**   - Developers who want security checks before deploying - DevSecOps engineers building CI/CD security gates - Penetration testers who need quick baseline assessments - Security students learning web vulnerability concepts hands-on - Platform teams enforcing security standards across services   Every failure includes: what was expected, what was received, why it matters, how to fix it, and a documentation link. AI adds domain-specific code examples on top.