🐍 Python Tutorial: Security Best Practices

Writing secure Python code is crucial to protect your applications and data. This tutorial covers best practices for secure coding, handling secrets, validating inputs, managing dependencies, and protecting against common vulnerabilities.


1. Write Safe and Readable Code

Clear and readable code reduces the chance of bugs and security flaws. Follow Python’s PEP 8 style guide and keep functions small and focused.

Avoid using eval(), exec(), or dynamic code execution with untrusted input—they can lead to code injection vulnerabilities.


2. Handle Secrets Securely

Never hardcode secrets like API keys, passwords, or tokens in your source code. Use environment variables or secret managers.

import os

api_key = os.getenv("API_KEY")
if not api_key:
    raise ValueError("API_KEY not set in environment variables")

Use libraries like python-dotenv during development to load environment variables from a .env file.


3. Validate and Sanitize Inputs

Always validate user inputs to prevent injection attacks and ensure data integrity.

For example, use regular expressions or specialized libraries to validate email addresses or phone numbers before processing them.


4. Manage Dependencies Carefully

Use virtual environments to isolate your project dependencies and keep them up to date.

Regularly audit dependencies for known vulnerabilities using tools like pip-audit or safety.


5. Protect Against Common Vulnerabilities


6. Logging and Error Handling

Avoid exposing sensitive information in logs or error messages. Use proper logging levels and redact secrets.

Handle exceptions gracefully and provide meaningful error responses without revealing internal details.


Additional Resources & References


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