Secure AI Coding with Cursor & StackHawk

AI tools like Cursor can generate complete applications in hours, but this speed creates a hidden problem: AI-generated code often looks secure but harbors vulnerabilities that only surface in production.

Traditional development includes natural security checkpoints—code reviews, architecture discussions, testing phases. When AI generates a complete REST API in minutes, these gates get bypassed. You end up with applications that work perfectly in development but contain authorization flaws, business logic vulnerabilities, and data exposure risks.

The solution isn’t slowing down—it’s making security testing as automated as code generation. You need runtime security testing integrated directly into your AI development workflow.

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Securing Cursor Apps with StackHawk: A Developer’s Guide

This guide outlines the essential best practices for integrating StackHawk with AI tools like Cursor, focusing on automation and efficient security testing workflows.

How to use this blog post

Point cursor at this blog post and it should give it context to help you scan a web application that you’ve been developing in cursor. Here’s an idea of a prompt:

I want to do a security scan of my application using StackHawk, read the context from the blog post @https://www.stackhawk.com/blog/secure-ai-coding-with-cursor/ and then help me to scan and secure my application.

Core Best Practices

1. AI Configuration Rules

When working with AI assistants, define clear rules for your project. Here are the recommended patterns. These rules can be added right into your project’s cursor rules.

{
  "name": "StackHawk Main Config",
  "description": "Rules specific to stackhawk.yml",
  "patterns": [
    "stackhawk.yml",
    "*.sarif"
  ],
  "prompts": [
    "Validate stackhawk.yml using 'hawk validate config stackhawk.yml' before committing.",
    "Use 'filePath' for local OpenAPI files, not 'path'.",
    "Reference documentation via prompts, e.g., 'Update stackhawk.yml using @https://docs.stackhawk.com/hawkscan/scan-discovery/'.",
    "Installation should reference documentation on @https://docs.stackhawk.com/download.html",
    "In order to output sarif you need to use the SARIF_ARTIFACT: true environment variable",
    "Whenever you change authentication run the authentication validation using hawk validate auth",
    "If you don't know what use hawkscan --help to understand how the commands work"
  ]
}

2. Documentation References

Always reference official documentation in your prompts using the @ syntax. This ensures AI tools have the correct context:

• Installation: @https://docs.stackhawk.com/download.html
• CLI Usage: @https://docs.stackhawk.com/stackhawk-cli/
• Authentication: @https://docs.stackhawk.com/hawkscan/authenticated-scanning.html
• Scan Discovery: @https://docs.stackhawk.com/hawkscan/scan-discovery/

3. SARIF Output for AI Analysis

Configure StackHawk to output results in SARIF format for better AI integration. This will give the AI the complete context to be able to fix security vulnerabilities.

Set the environment variable:

export SARIF_ARTIFACT=true

This enables AI tools to:

• Parse and analyze security findings
• Generate detailed reports
• Track issues across scans
• Integrate with CI/CD pipelines

Essential Commands

# Validate configuration

hawk validate config stackhawk.yml

# Validate authentication

hawk validate auth

# Run scan with SARIF output

hawk scan --sarif-artifact

Quick Reference

1. Always use stackhawk.yml for configuration
2. Use absolute paths for OpenAPI specifications
3. Validate configuration before scanning
4. Enable SARIF output for AI analysis
5. Reference documentation in prompts using @ syntax

The Future of Secure AI Development

As AI development tools become more powerful, the organizations that succeed will master the integration of speed and security early. The workflow in this guide—where security testing is as automated as code generation—sets the foundation for what’s coming next.

By integrating StackHawk into your Cursor workflows now, you’re building the technical patterns that will scale as AI tools evolve. Start with these practices, then adapt as your AI development workflow grows more sophisticated.

More related readings

If you’ve been following Brad’s journey into vibe coding, you’ve already seen how cursor can transform application development with AI-powered assistance. But with great coding velocity comes great security responsibility. This post builds on Brad’s foundational work to show you how StackHawk fits into your AI-accelerated development workflow—because as your code generation speeds up, your security testing needs to keep pace.

Haven’t read Brad’s exploration yet? Check out his original post to understand the vibe coding foundation we’re building upon.

https://feld.com/archives/2025/05/vibecoding-prompts/