AI-Augmented SAST and DAST Integration in CI/CD Pipelines
Keywords:
AI-Augmented Security, Static Application Security Testing (SAST), Dynamic Application Security Testing (DAST)Abstract
This work explores how CI/CD pipelines might include Dynamic Application Security Testing (DAST) and Static Application Security Testing (SAST) to essentially enhance application security. DAST discovers flaws in operational systems, which together provide a more complete security architecture; SAST provides thorough code analysis during development. Still, hand methods and generic instruments can lead to missing dangers and delayed reactions. Artificial intelligence appears at this junction. Artificial intelligence is changing the scalability and adaptability of security testing in real time by employing machine learning models and natural language processing to analyze code, predict hazards, and provide remedies. The Continuous Integration/Continuous Deployment (CI/CD) strategy of a mid-sized technology company combining AI-enhanced Static Application Security Testing (SAST) with Dynamic Application Security Testing (DAST) is presented in this paper. Without sacrificing deployment time, the results revealed a notable decline in false positives, quicker vulnerability triage, and better developer experience. We also show how they overcome the issues they encountered—including first integration difficulties and model changes. Emphasizing the actual advantages and challenges involved, the paper provides a reasonable method for adding sophisticated security testing into automated systems. Whether your role is security engineer, DevOps lead, or developer—this paper provides ideas on how artificial intelligence may improve application security to be more proactive, intelligent, and seamlessly incorporated into current software development and deployment processes.
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