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🔒 PII & Data-Leak Scanner
Get severity-ranked file and line findings without sending data to an external service.
$15
🔒 PII & Data-Leak Scanner
Example session with this skill installed
Scan the SQL, CSV, JSON, and log files under tests/fixtures and tmp/logs for likely PII. Do not write files or reproduce matched personal-data values in the report.
- Read your context and instructions
- Compiled the pii & data-leak
PII Data Leak Scanner Report
Files scanned: 4
Findings: 15
[HIGH] PII002 - tmp/app.log:1
Email-looking value found.
Evidence: <redacted-email>
Remediation: Replace real-looking PII with synthetic or anonymized values.
[CRITICAL] PII004 - tmp/app.log:1
Credit-card-like number found.
Evidence: <redacted-card>
Remediation: Replace real-looking PII with synthetic or anonymized values.
[HIGH] PII001 - fixtures/profile.json:3
PII-indicating JSON key found.
Evidence: phone
Remediation: Rename, tokenize, hash, or remove PII keys from shared fixtures.
Connects securely to your tools. The creator never sees your data.
About this skill
Catch personal data before code or logs are shared
Scan local SQL, CSV, JSON, seed, fixture, and log files for PII-indicating column or key names and email-, SSN-, card-, and phone-like values. Get severity-ranked file and line findings without sending data to an external service.
Keep detected values out of the report
The v1.1 scanner replaces matched email-, SSN-, card-, and phone-like values with redacted placeholders and limits structural evidence to the matched key or column name. Reports preserve the location, rule, and remediation without copying nearby record content.
Run locally and read-only
The bundled scanner uses only the Python 3 standard library. It requires no third-party package, network access, API key, environment variable, database connection, secret read, or file write.
Know what it can and cannot conclude
The scanner uses regex and keyword heuristics, so false positives and false negatives are possible. It covers common PII indicators and US-style SSN, card, and phone patterns; it is not a DLP system, legal advice, or proof of GDPR, CCPA, or SOC 2 compliance.
Review evidence before remediation
Confirm whether a match is real personal data, synthetic test data, an expected schema field, or a harmless format match. The included checklist helps reviewers document context, minimization, retention, access, and the next human decision.
How to use
- 1
Connect your agent to the Agensi MCP
Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup
- 2
Sign in to Agensi
Your agent shows a sign-in link. Sign in and click Allow.
- 3
Ask for what you need
Your agent loads this skill and uses it on your task. It always asks before any payment.
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