CodeTrust: Stop Shipping AI-Generated Security Holes
AI coding assistants are transforming development speed. But speed without trust is debt.
The Problem
Every dev team using Copilot, Cursor, or ChatGPT to write code faces the same silent risk: AI-generated code that passes code review but fails security.
Common patterns I've seen:
- SQL injection via unsanitized template strings from LLM suggestions
- Hardcoded secrets in generated config files
- Insecure deserialization in AI-written API handlers
- Missing input validation on generated form handlers
Manual code review catches obvious issues. It doesn't catch subtle logic errors at scale.
What CodeTrust Does
CodeTrust is a PR-integrated static analysis + OWASP TOP 10 scanner that:
- Triggers automatically on every PR (GitHub Actions, GitLab CI plugin)
- Posts inline review comments at the exact vulnerable line
- Generates audit reports in Markdown, PDF, or JSON for compliance
- Tracks AI-origin code separately — so you know which vulnerabilities came from LLM suggestions
Why This Matters in 2026
AI-assisted code now represents ~40% of committed code at many mid-size teams (GitHub Octoverse 2025). Existing SAST tools weren't designed with AI code patterns in mind.
CodeTrust's rule engine is tuned for the specific vulnerability patterns LLMs tend to produce — not just generic CWE checks.
Early Access
We're validating demand before full build. If this solves a problem you have:
- Join the waitlist (free early access priority)
No spam. Just a launch notification when it's ready.
KunStudio Labs — building AI automation tools for developers and teams.
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