Security as Code Using Agentic AI: Efficiency in Ensuring Software Development Lifecycle Security
This paper presents a framework for automating software development security using a Security as Code approach enhanced with a multi-agent artificial intelligence system. The research addresses the limitations of traditional DevSecOps practices by deploying specialized AI agents to perform static code analysis, generate and enforce security policies, and monitor system behavior. The architecture integrates security throughout the CI/CD pipeline and runtime, enabling autonomous decision-making, adaptability to threats, and reduced developer overhead.