askill
privacy-review

privacy-reviewSafety 100Repository

Automated privacy review for git repositories. Scans for sensitive data exposure including API keys, passwords, database credentials, and tokens. Use before pushing to public repositories or sharing code. Trigger by running 'python privacy_scan.py' on a git repository.

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1.2k downloads
Updated 1/31/2026

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SKILL.md

Privacy Review

Overview

Automated privacy security review for git repositories. Detects sensitive data exposure in committed files and repository configuration.

When to use:

  • Before pushing code to public repositories (GitHub, GitLab)
  • When sharing code with external parties
  • Before opening pull requests
  • Periodic security audits

Checks Performed

1. Sensitive Files in Commits

Scans git history for committed files with sensitive extensions:

  • .env, .env.local - Environment configuration
  • .pem, .p12 - Private keys and certificates
  • *_secrets.* - Secret configuration
  • *_credentials.* - API credentials

2. Secrets in Committed Code

Pattern-based scanning for sensitive patterns in source files:

  • Database URLs with credentials (postgresql://user:pass@host)
  • API keys (sk-, AKIA, Bearer)
  • Secret tokens and assignments
  • Authorization headers

3. .gitignore Protection

Verifies that .env and other sensitive files are properly ignored.

4. Local .env File

Checks if local .env exists with real credentials (not committed).

Quick Start

# Scan current directory
python privacy_scan.py

# Scan specific repository
python privacy_scan.py --repo-path /path/to/repo

# Quiet mode (show only issues)
python privacy_scan.py --quiet

Report Format

The tool generates a structured report with:

======================================================================
PRIVACY REVIEW REPORT
======================================================================

πŸ“ CHECK 1: Sensitive Files in Git
----------------------------------------------------------------------
βœ… No sensitive files committed

πŸ” CHECK 2: Secrets in Committed Code
----------------------------------------------------------------------
❌ FOUND potential secrets:
   - API key assignment: OPENAI_API_KEY="sk-abc123xyz..." (line 42)

πŸ›‘οΈ  CHECK 3: .gitignore Protection
----------------------------------------------------------------------
βœ… .env is protected by .gitignore

πŸ“„ CHECK 4: Local .env File
----------------------------------------------------------------------
⚠️  WARNING: .env exists with real credentials
   Status: .env file exists locally but is NOT committed

======================================================================
SUMMARY
======================================================================
❌ Found 2 privacy concern(s)

Recommendations:
  - Replace secrets with environment variable references
  - Rotate any exposed credentials
  - Ensure .env remains in .gitignore

======================================================================

Remediation Guide

Removing Secrets from History

If secrets are found in committed files:

# Remove specific file from all branches
git filter-branch --force --index-filter \
  'git rm --cached --ignore-unmatch file-with-secrets.py' HEAD

# Push cleaned history (requires force)
git push origin --force

Replacing Secrets with Environment Variables

Before:

DATABASE_URL="postgresql://user:password@host:5432/db"
API_KEY="sk-abc123xyz..."

After:

import os

DATABASE_URL = os.getenv("DATABASE_URL")
API_KEY = os.getenv("API_KEY")

Create .env.example:

DATABASE_URL=postgresql://user:password@localhost:5432/db
API_KEY=your-api-key-here

Common Mistakes

❌ Don't Commit

  • .env files with real credentials
  • API keys in configuration files
  • Database URLs with passwords
  • Private keys (.pem, .key)
  • Hardcoded secrets in code

βœ… Do Instead

  • Use os.getenv() for configuration
  • Commit .env.example with placeholders
  • Reference secrets from environment
  • Use secret management services
  • Document required variables in README

Patterns Detected

See PATTERNS.md for complete list of sensitive patterns:

  • Database URLs with credentials
  • API keys (OpenAI, AWS, etc.)
  • Authentication tokens
  • Configuration files with extensions

Best Practices

Code Level

  • All secrets use environment variables
  • Validation at startup (fail if secrets missing)
  • No secrets in logs or print statements

Repository Level

  • .env always in .gitignore
  • Enable secret scanning in CI/CD
  • Require review for sensitive changes
  • Audit git history periodically

Workflow Level

  • Automate pre-commit hooks for secret detection
  • Fail builds on secret detection
  • Rotate credentials regularly
  • Use short-lived tokens when possible

Troubleshooting

False Positives

The tool may flag:

  • Example values in .env.example (safe)
  • Test URLs with localhost or 127.0.0.1 (usually safe)
  • Documentation mentioning patterns (not actual secrets)

Review these manually before taking action.

Files Not Scanned

Binary files and large assets are skipped:

  • Images (.png, .jpg, .gif)
  • PDFs
  • Zip files
  • Already committed files (use git filter-branch for historical scans)

Advanced Usage

CI/CD Integration

Add to GitHub Actions:

- name: Privacy Scan
  run: |
    python -m privacy_scan.scripts.privacy_scan --quiet

Custom Patterns

Extend privacy_scan.py with additional patterns:

# Add to patterns list in check_sensitive_patterns_in_content()
(r"custom_pattern", "Custom sensitive data"),

Ignore Specific Patterns

For files with known safe patterns (like test data):

# Modify scan_commit_for_secrets() to skip files
if "test_" in file_path.lower():
    continue

Install

Download ZIP
Requires askill CLI v1.0+β–Ά

AI Quality Score

96/100Analyzed 2/12/2026

An excellent, comprehensive guide for automated privacy reviews. It includes clear triggers, actionable remediation steps, and integration examples, making it highly valuable for security-conscious development.

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Metadata

Licenseunknown
Version-
Updated1/31/2026
Publisheremliunix

Tags

apici-cddatabasegithubgithub-actionsllmsecuritytesting