AI-Driven Security as Code in Jenkins: Pioneering DevSecOps for 2025

Abstract

As we move toward an AI-first future, Security as Code (SaC) is becoming a cornerstone of modern DevSecOps—especially when integrated with automation platforms like Jenkins. By embedding automated security checks, real-time threat detection, and compliance enforcement directly into CI/CD pipelines, organizations can shift from reactive to proactive security. This enables consistent and secure software releases at scale.

Integrating SaC in Jenkins with AI-Powered Automation

This session explores practical strategies for implementing SaC within Jenkins pipelines using AI-driven automation. Key techniques include: - Static and dynamic analysis - Policy-as-Code (PaC) - Risk-based vulnerability prioritization

Enhancing Security with Machine Learning

Machine learning significantly augments SaC by enabling: - Intelligent threat detection - Contextual risk scoring - Adaptive policy enforcement These capabilities allow for more precise, real-time responses to security threats, reducing false positives and aligning enforcement with organizational risk tolerance.

Real-World Use Cases

Through real-world examples, we’ll demonstrate how integrating Jenkins and AI-powered SaC can: - Strengthen regulatory compliance - Improve incident response - Foster collaboration between development, security, and operations teams

Looking Ahead: Intelligent and Scalable DevSecOps

This talk offers a forward-looking perspective on building resilient, scalable, and intelligent DevSecOps practices. By embracing Security as Code in an AI-first environment, organizations can empower teams to deliver secure software faster—without compromising agility or innovation.