AI in Security Testing & Vulnerability Detection — Smarter Defenses for Modern Software AI in Security Testing & Vulnerability Detection — Smarter Defenses for Modern Software Software vulnerabilities are a moving target. Attackers automate their discovery; defenders must automate detection and response. In this article we walk through how AI augments security testing — from static code analysis and fuzzing to continuous, AI-driven penetration testing — supported by research, case studies and practical guidance for teams adopting these approaches. 1. The security testing problem: scale, speed and blind spots Software grows faster than our ability to test it. The modern application stack includes thousands of open-source libraries, dozens of services, and deployment pipelines that ship multiple times per day...
Bugged But Happy is a software testing blog that shares real-world QA insights, ETL testing tips, SQL query guides, automation tools like Selenium, PySpark, and RPA, plus fun stories from the tester’s life. Whether you're a beginner or experienced tester, this blog helps you grow, debug smarter, and stay updated—while enjoying the journey. Because every bug teaches us something new!