Announcing The Static Application Security Testing Solutions Forrester Wave™ And Buyer’s Guide — AI Brings Opportunity To SAST Solutions

2026-01-05 · Source: Featured Blogs - Forrester · Field: Technology & Digital — Cybersecurity & Data Privacy, Software Development & Engineering, Artificial Intelligence & Machine Learning · Depth: Intermediate, short

Summary

The Forrester Wave™: Static Application Security Testing Solutions, Q3 2025, evaluates 10 leading SAST vendors: Black Duck Software, Checkmarx, GitHub, GitLab, HCLSoftware, Mend.io, OpenText, Snyk, Sonar, and Veracode. This research assesses vendors on 16 current-offering and seven strategy criteria, based on questionnaires, executive briefings, and customer interviews. The SAST market has matured, intensifying competition and driving vendors to focus on efficiency, integration, and expanded offerings. Key trends include integrating AI SAST agents for faster code analysis, prioritizing AI-driven remediation with fix options, and evolving SAST to secure AI applications and agents, including identifying OWASP Top 10 LLM flaws. The market also sees low entry barriers for new AI-powered SAST solutions and a crowded landscape with diverse players.

Key takeaway

For security leaders evaluating SAST solutions, prioritize vendors demonstrating strong AI integration for both scan speed and automated remediation, especially those addressing AI application security. Your decision should weigh not only technical capabilities but also vendor commitment to customer support and roadmap inclusion, as customer loyalty and satisfaction remain high in this mature market, indicating long-term partnership value.

Key insights

SAST solutions are maturing, integrating AI for speed and remediation, and adapting to secure AI-generated code and applications.

Principles

• SAST market maturity drives efficiency and integration focus.
• AI accelerates SAST scanning and automates remediation.
• Customer relationships and loyalty remain critical for SAST vendors.

Method

Forrester evaluated 10 SAST vendors using questionnaires, executive briefings, and customer interviews, scoring 16 current-offering and seven strategy criteria.

In practice

• Integrate AI SAST agents for rapid code security.
• Utilize AI for flaw prioritization and automated remediation.
• Address OWASP Top 10 LLM flaws with SAST and DAST.

Topics

• Static Application Security Testing
• AI-Generated Code Security
• Large Language Models
• Application Security Posture Management

Best for: CTO, VP of Engineering/Data, Product Manager, Security Engineer, Software Engineer, AI Product Manager

Related on AIssential

• AI Is Building Your Attack Surface. Are You Testing It? — AI-driven development creates new, amplified attack surfaces requiring advanced, correlated dynamic security testing.
• Can Open-Source LLM Agents Replace Static Application Security Testing Tools? An Empirical Assessment — Current open-source LLM agents are not effective replacements for specialized SAST tools in realistic cybersecurity scenarios.
• AI Is Speeding Up Vulnerability Discovery. Most Security Teams Aren’t Built to Keep Up — AI-driven vulnerability discovery makes rapid remediation, not detection, the critical cybersecurity challenge.
• From Discovery to Defense: Why AI Red Teaming Is the Next Step After AI-SPM — Modern application security requires converging advanced static analysis with dynamic testing and AI-driven pentesting to address emergent runtime vulnerabilities.
• AI Threat Readiness Pillar 3: Perform AI Code Analysis Natively in Wiz — AI-driven development necessitates a layered, context-aware code security approach for rapid vulnerability detection and remediation.
• Announcing The Forrester Wave™: Workforce Identity Security Platforms, Q2 2026 — Workforce identity security is evolving into a comprehensive control plane, integrating AI-driven intelligence and agentic AI support.

Open in AIssential →

Editorial summary, takeaway, and curation by AIssential. Original article published by Featured Blogs - Forrester.