How does it handle PII discovery?

It identifies fields containing Personally Identifiable Information and confirms how they are stored and logged to ensure compliance with privacy standards.

What is the primary purpose of the security-privacy skill?

It is designed to reduce the risk of data leakage, PII exposure, and license violations in Python research and development code.

Does this skill automatically delete my sensitive data?

No. The skill follows strict guardrails; it identifies risks and escalates findings but does not delete or redact data without explicit user approval.

Can it identify license issues in my datasets?

Yes, part of its workflow includes checking both library and dataset licenses to ensure they are compatible with your project goals.

Python Security and Privacy Refactoring

Name: Python Security and Privacy Refactoring
Author: Silviase

bySilviase

セキュリティとテスト

Audits Python research code for data leaks, PII exposure, and license compliance risks.

概要

The Python Security and Privacy Refactoring skill is designed to transition research-grade Python scripts into secure, production-ready code. It systematically scans for hardcoded secrets, identifies sensitive PII (Personally Identifiable Information) fields, and verifies library license compatibility. By automating the auditing of .gitignore files and documenting privacy constraints, this skill ensures that sensitive outputs and large artifacts are never leaked to version control, making it essential for data scientists and developers handling sensitive datasets.

主な機能

Hardcoded secret and private endpoint detection
PII field identification and handling documentation
Automated .gitignore verification for sensitive data
Security constraint documentation in README.md
0 GitHub stars
Library and dataset license compatibility checks

ユースケース

Preparing internal research code for public repository release
Auditing data science projects for PII compliance and privacy
Cleaning up hardcoded tokens and credentials before code reviews

概要

主な機能

Hardcoded secret and private endpoint detection
PII field identification and handling documentation
Automated .gitignore verification for sensitive data
Security constraint documentation in README.md
0 GitHub stars
Library and dataset license compatibility checks

ユースケース

Preparing internal research code for public repository release
Auditing data science projects for PII compliance and privacy
Cleaning up hardcoded tokens and credentials before code reviews