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<p>This article discusses the combination of AI-based static and dynamic analysis in DevSecOps to ensure continuous security across the software development life cycle. Static analysis identifies security vulnerabilities in source code prior to execution, whereas dynamic analysis detects runtime threats. AI augments these processes by enhancing precision, minimizing false positives, and speeding up remediation. AI-based methods also facilitate automated vulnerability prioritization, secure coding enforcement, and self-healing capabilities. This paper further discusses AI’s role in CI/CD pipeline security, compliance monitoring, and advanced threat simulation. Through AI integration, organizations can achieve real-time threat detection, automated mitigation, and enhanced resilience in modern DevSecOps environments.</p>

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AI-Powered Static & Dynamic Analysis for Continuous Security in DevSecOps

  • 期刊论文

  • 发表日期：

    2025年9月25日

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  • Praveen Chaitanya Jakku

摘要

This article discusses the combination of AI-based static and dynamic analysis in DevSecOps to ensure continuous security across the software development life cycle. Static analysis identifies security vulnerabilities in source code prior to execution, whereas dynamic analysis detects runtime threats. AI augments these processes by enhancing precision, minimizing false positives, and speeding up remediation. AI-based methods also facilitate automated vulnerability prioritization, secure coding enforcement, and self-healing capabilities. This paper further discusses AI’s role in CI/CD pipeline security, compliance monitoring, and advanced threat simulation. Through AI integration, organizations can achieve real-time threat detection, automated mitigation, and enhanced resilience in modern DevSecOps environments.