pySQLY - Python Standard Query Language | SQL with YAML Syntax

pySQLY is a Python library that standardizes SQL querying with YAML syntax, making database operations consistent across multiple database engines

View project on GitHub

Security Policy

Supported Versions

Use this section to tell people about which versions of your project are currently being supported with security updates.

Version Supported
0.1.x :white_check_mark:

Reporting a Vulnerability

The pySQLY team takes security issues seriously. We appreciate your efforts to responsibly disclose your findings and will make every effort to acknowledge your contributions.

To report a security issue, please email support@antonybailey.net with a description of the issue, the steps you took to create the issue, affected versions, and if known, mitigations for the issue.

We aim to respond to security reports within 48 hours. If for some reason you don’t get a response within that timeframe, please follow up via email to ensure we received your original message.

After the initial reply to your report, the security team will keep you informed of the progress towards a fix and full announcement, and may ask for additional information or guidance.

Security Best Practices for Using pySQLY

When using pySQLY in your applications, consider these security best practices:

  1. Always sanitize user inputs: While pySQLY helps prevent SQL injection by using parameterized queries, it’s still important to validate and sanitize all user inputs before processing them.

  2. Use principle of least privilege: Configure your database users with the minimum required permissions for your application to function.

  3. Keep dependencies updated: Regularly update pySQLY and its dependencies to ensure you have the latest security patches.

  4. Store connection strings securely: Never hard-code database credentials in your source code. Use environment variables or a secure secret management system.

  5. Log responsibly: Be careful not to log sensitive information like queries that might contain personal data or credentials.

Thank you for helping keep pySQLY and its community safe!