RepoRadar - Spot hidden risks in AI-generated repos

Automatically monitor AI-built code repos for security gaps, license issues, and secret leaks

Problem

A developer scanned 70 public repos built with Lovable and manually read every finding, discovering that while RLS was fine, edge functions commonly had vulnerabilities. Many non-expert builders using AI app generators lack visibility into security or license risks, and existing scanners are either too heavy or not tuned for AI-generated patterns.

Solution

A lightweight GitHub App you authorize on selected repos. It runs static checks targeting common AI-code weaknesses—insecure defaults, edge functions missing auth, hardcoded secret patterns—and generates easy-to-read risk reports. It supports scheduled scans and alerts via email or Slack when new issues appear.

Users

Indie developers and small teams building apps with Lovable, Bolt, v0, and similar AI tools, especially startups without dedicated security staff.

MVP

Scan public GitHub repos only; ship 10 detection rules specific to AI-generated code; output Markdown reports and optionally open GitHub Issues; free tier for 5 repos, paid unlocks unlimited repos and scheduled scans.

Revenue

Freemium subscription: free tier limits repos and scan frequency; paid plan offers detailed reports, historical diff, and team features.

Why now

AI-generated code is exploding, but security tooling isn't tuned for this new pattern. An indie developer can win with simple static analysis and a rules engine—no heavy infrastructure needed.