All my code was written by AI — how do I trust it?

Updated

AI-generated code has a 45-62% security-bug rate. Trust it to work, not to be safe.

You shipped your SaaS. Most of the code came from Cursor + Claude. You read maybe 30% of it. The rest works, so you left it. You're starting to wonder if you should have looked more closely.

What happens next

  1. The realistic bug rate

    Multiple independent studies in 2025-2026 find that 45-62% of AI-generated code contains at least one security bug when the prompt is neutral. With explicit security cues, the rate drops to 8-20%.

  2. The three most common classes

    1) Missing authorization on API endpoints. 2) Leaked secrets in client bundle. 3) Missing input validation leading to SQL injection or XSS.

  3. What to do

    Run a scanner that specifically understands AI-generated-code patterns. Not a pattern-matching SAST — a tool that verifies the bug exists by reproducing it.

Without Securie

You manually re-read your AI-generated code looking for bugs. You don't know what you're looking for. You hope for the best.

With Securie

Securie is built for fast-moving production codebases, including AI-assisted apps. Once your repo is enabled, it reviews every AI-generated or human-written commit the way a senior security engineer would, focuses on real exploitable bugs, and opens fixes as pull-request comments.

Exactly what to do right now

  1. Read /blog/why-ai-generated-code-is-unsafe-by-default
  2. Run securityheaders.com on your live URL
  3. Run trufflehog or gitleaks on the repo Cursor / Lovable / Bolt is writing to
  4. Request Securie access at /scan
  5. Review every AI suggestion with security in mind until Securie is enabled on the repo