Insights from the Leon van Zyl episode “Claude Code: Build an AI Agent That Finds Vulnerabilities”, published April 18, 2026.
In "Claude Code: Build an AI Agent That Finds Vulnerabilities" (Leon van Zyl, April 2026), instead of relying on black-box security tools, developers can build modular AI agents using reusable skills to audit codebases. By grounding LLM agents in established standards like the OWASP Top 10, teams can consistently…
In "Claude Code: Build an AI Agent That Finds Vulnerabilities", Reusable instruction sets that define how an AI agent should perform a specific task. They matter because they enable portability across different projects and coding agents, ensuring consistent logic and standards. This changes the listener's workflow…
In "Claude Code: Build an AI Agent That Finds Vulnerabilities", A standard awareness document representing the most critical security risks to web applications. It serves as the grounding framework for the AI scanner, providing a consensus-based checklist for what the model should look for. It changes the approach…
In "Claude Code: Build an AI Agent That Finds Vulnerabilities", Specialized agents triggered by a main coordinator to perform focused tasks like security audits. They allow for complex applications to be built by delegating specific domains of expertise to refined sub-modules. This modularity reduces the error rate…
Instead of relying on black-box security tools, developers can build modular AI agents using reusable skills to audit codebases. By grounding LLM agents in established standards like the OWASP Top 10, teams can consistently identify critical vulnerabilities such as SQL injection and broken access control in real-time.
Topics: AI Security, Coding Agents, OWASP, Automated Auditing