Enhancing Secure Software Development with AZTRM-D: An AI-Integrated Approach Combining DevSecOps, Risk Management, and Zero Trust

This paper introduces the Automated Zero Trust Risk Management with DevSecOps Integration (AZTRM-D) framework, a novel and comprehensive approach designed to intrinsically embed security throughout the entire Secure Software and System Development Lifecycle (S-SDLC). AZTRM-D strategically unifies established methodologies—DevSecOps practices, the NIST Risk Management Framework (RMF), and the Zero Trust (ZT) model—and significantly augments their capabilities through the pervasive application of Artificial Intelligence (AI). This integration shifts traditional, often fragmented, security paradigms towards a proactive, automated, and continuously adaptive security posture. AI serves as the foundational enabler, providing real-time threat intelligence, automating critical security controls, facilitating continuous vulnerability detection, and enabling dynamic policy enforcement from initial code development through operational deployment. By automating key security functions and providing continuous oversight, AZTRM-D enhances risk mitigation, reduces vulnerabilities, streamlines compliance, and significantly strengthens the overall security posture of software systems, thereby addressing the complexities of modern cyber threats and accelerating the delivery of secure software.