OWASP API Security Top 10… or should it be 4?

APIs power everything, but their rapid growth—and the rise of AI-native systems—has created new blind spots in security. This research challenges the traditional OWASP API Security Top 10, revealing that real-world API risk often centers around four core problem areas: improper authorization, business logic abuse, inadequate governance, and unchecked third-party services. It explores how organizations can move beyond checklists and vendor claims to achieve true, context-aware API protection. Readers will learn how to assess security tools effectively, identify hidden risk gaps, implement multi-tiered strategies for distributed environments, and adapt for  AI-native designs.

What you’ll Learn:

• ‍Focus beyond the Top 10: The OWASP API Security Top 10 is a useful reference—but not a complete roadmap. Real API risk often concentrates in four areas: improper authorization, business logic abuse, inadequate governance, and unchecked third-party services.‍
• Tool coverage is not equal: Many vendors claim full OWASP coverage, but few effectively mitigate these core risks without excessive manual intervention and additional engineering work.‍
• Automation is essential: Manual API security can’t keep pace with today’s dynamic, AI-driven environments—Agentic AI and automation are now necessities.‍
• Risk prioritization needs context: OWASP rankings don’t always align with your organization’s actual exposure; security teams must weigh likelihood and impact for their unique designs, not just risk frequency and anecdotal evidence.‍
• Comprehensive protection requires context awareness: Effective API security solutions combine discovery, behavioral analysis, and runtime defense across the full API lifecycle.

Who is this for?

Michael Isbitski This research is for application security engineers who make decisions around vendor tools and platforms used to catalog, test, and protect their organization’s APIs.  Intersections also occur with cloud security, API governance, and AI governance teams, where exposed APIs or the data flowing through API endpoints used by  AI systems is a concern.