PIIRadar – find PII in systems where it shouldn't be

Scans and monitors whether sensitive user data leaks into logs, analytics, and other unintended systems

Problem

One developer asked what's hardest about keeping PII out of unnecessary systems, and another product asks what your AI tools are really doing on your machine. Small teams know PII shouldn't flow everywhere, but lack a low-cost, continuously running discovery and blocking tool, relying instead on manual audits or post-breach fixes.

Solution

Scan code repos, log files, database exports, and analytics events locally or in CI for emails, phone numbers, national IDs, addresses, and other PII patterns. Flag where they appear in unintended systems and generate fix suggestions. Support scheduled rescans and alerts for newly introduced leaks.

Users

Small-team CTOs, backend developers, security leads, AI app developers

MVP

Local scanning of code repos, log directories, and .env files; built-in common PII regex and validation rules; leak report grouped by system with fix suggestions; GitHub Action example; no real-time traffic interception.

Revenue

Free local scanning; subscription unlocks scheduled monitoring, team sharing, and alert integrations (Slack/email); per-repo or scan-volume billing for teams.

Why now

AI apps complicate data flows and expand PII exposure, but enterprise DLP is too heavy and expensive; indie devs can build an affordable small-team version with pattern matching and light scanning.