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    🔒 PII & Data-Leak Scanner

    by JustHandled Labs

    2

    The PII Data Leak Scanner is a specialized audit tool designed to identify sensitive Personal Identifiable Information (PII) within your codebase and data artifacts.

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    See it in action

    You say

    Scan our database seed files and the recent logs in the /tmp folder for any potential PII leaks or sensitive data.

    Your agent does

    PII Scan Results

    • CRITICAL: seeds/users.sql:12 - Found SSN-pattern (xxx-xx-xxxx)
    • HIGH: tmp/app.log:142 - Potential email address exposure (admin@company.com)
    • MEDIUM: fixtures/orders.json - Sensitive column name "credit_card_last_four" detected.

    See remediation-snippets.md for fixes.

    What you get

    Audit database seed files for real customer data before committing code.Scan server logs for accidental PII logging during local development.Verify that fixture files are properly anonymized for integration tests.Generate a PII audit report for sensitive JSON and CSV data exports.

    About this skill

    What it does

    The PII Data Leak Scanner is a specialized audit tool designed to identify sensitive Personal Identifiable Information (PII) within your codebase and data artifacts. It performs heuristic scans across SQL schemas, CSV datasets, JSON files, seed data, fixtures, and application logs to detect accidental exposure of emails, SSNs, credit card numbers, and sensitive column names.

    Why use this skill

    Prompting a standard AI to "find PII" often leads to inconsistent results and missed patterns. This skill provides a structured, developer-focused workflow using a dedicated Python scanner and an industry-standard audit checklist. It ensures that before you push code to a public repo or share a database dump, you have an evidence-based report citing exact filenames and line numbers for remediation.

    Supported tools

    • File Formats: .sql, .csv, .json, .log
    • Frameworks: Optimized for Rails/Django/Node seed and fixture directories
    • Standard Library: Pure Python implementation with no external dependencies required

    What the output looks like

    You receive a structured Markdown report categorized by severity (Critical to Info). Each finding includes the file path, line number, the specific evidence found (e.g., a regex match for a phone number), the potential impact, and a templated remediation step you can apply immediately.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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    3 installs

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    Trust & safety

    Security scanned

    Verified clean 1 month ago

    Installs3
    Listed1 month ago

    Creator

    JustHandled Labs builds focused agent skills for the work nobody wants to do by hand. Each one is a single repeatable job done well: catching the security and data mistakes that quietly ship, keeping docs and tests honest, gating the commands an agent is about to run, sharpening writing, and handling the founder chores around launches, outreach, and brand setup. Not generic AI productivity. Specific workflows that are easy to run, review, and repeat. Maintained by H.J. Westerfield, with a background in communications, editing, project coordination, customer support, and practical AI systems. Tools for people who want useful automation without theatrical complexity.

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