Working with AI coding agents doesn't mean abandoning security practices. It means adapting them. The speed of AI-assisted development is a superpower, but it requires adjusting how you think about security review and validation.
Review What Matters
You can't review every line of AI-generated code with the same intensity you'd apply to hand-written code. There's too much of it. Instead, focus your attention on high-risk areas: authentication and authorization logic, input handling, database queries, API integrations, and anything that touches sensitive data.
These are the places where security mistakes have the biggest impact. A formatting issue in a UI component is low stakes; an authorization bypass in an admin endpoint is not.
Be Specific About Security
AI agents respond to instructions. If you ask for a login form, you'll get a login form. If you ask for a secure login form that prevents brute force attacks, rate limits requests, and logs failed attempts, you'll get something more robust.
Include security requirements in your prompts. Mention specific concerns you have. The more context you provide about security expectations, the more likely the generated code will meet them.
The OWASP Secure Coding Practices Quick Reference provides a checklist of security considerations to keep in mind.
Use Automated Guardrails
Don't rely solely on your own review capacity. ACSM tools can provide automated security checks as code is generated, catching common issues before you ever see them. Hooks can enforce that security reviews happen on every generation.
These tools don't replace human judgment. They augment it. They catch the obvious issues so you can focus your attention on the subtle ones.
Getting Started with Guardrails
Setting up security guardrails for AI coding is straightforward with the right tools. Sign up for a Corridor account to get automated security analysis integrated directly into your AI coding workflow. Corridor works with popular tools like Cursor and Claude Code, providing real-time feedback as code is generated.
Trust but Verify
Treat AI-generated code with appropriate skepticism. It might work correctly and still be insecure. It might pass tests and still have vulnerabilities. The fact that an AI wrote it doesn't make it more or less trustworthy than human-written code. Apply the same standards either way.