Automated Code Security Analysis in DevSecOps Pipelines using NLP
Abstract
Modern software development sometimes creates security flaws that might be dangerous if not detected and fixed. DevSecOps handles this by emphasizing security throughout software development. NLP can automate DevSecOps pipeline security vulnerability discovery and analysis to enhance code security. By comprehending context and intent, NLP can scan massive code, detect semantic patterns, and find flaws. This paper evaluates the strengths, cons, and future of NLP in automated code security analysis in DevSecOps pipelines. This article uses case examples to demonstrate how NLP-driven technology may enhance vulnerability discovery and software application security.
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