The Convergence Trend

The distinction between SAST and IAST continues blurring as technologies evolve. Hybrid analysis approaches combine static analysis with runtime information for improved accuracy. SAST tools incorporate runtime configuration data to reduce false positives. IAST solutions add static analysis capabilities for comprehensive coverage. This convergence promises to deliver the benefits of both approaches while mitigating their individual limitations.

Machine learning accelerates this convergence. ML models trained on both static code patterns and runtime behaviors can predict vulnerabilities more accurately than either approach alone. Correlation engines that combine SAST and IAST findings provide higher confidence results. Automated tuning systems learn from false positives to improve future analysis. These advances point toward unified platforms that seamlessly blend static and interactive analysis.

The future of application security testing likely transcends the SAST versus IAST debate. Integrated platforms will automatically apply the most appropriate analysis technique for each situation. Developers will receive unified security feedback regardless of underlying detection methods. Until this vision materializes, understanding SAST and IAST's distinct values enables organizations to build comprehensive security testing strategies that leverage both approaches effectively. The goal isn't choosing between static and interactive analysis but rather orchestrating them to provide continuous security assurance throughout the application lifecycle.## How to Choose Between SAST, DAST, and IAST

Selecting the right application security testing tools represents one of the most critical decisions in building an effective security program. The choice between SAST, DAST, and IAST—or more likely, the decision of how to combine them—impacts everything from developer productivity to security posture. This chapter provides a comprehensive framework for making these decisions, considering technical requirements, organizational factors, and practical constraints that influence successful implementations.