Python for Cybersecurity Course Demonstrates Testing and Security Automation

Summary

Brandon Keith demonstrates a Python training course for cybersecurity practitioners, covering unit testing, security data parsing and the risks of relying on unchecked AI-generated code.

Key points

• The course combines Python fundamentals with browser-based exercises and a cloud coding workspace.
• Keith demonstrates unit testing with a function that checks whether a port number is within the valid range.
• The speakers caution that AI-generated code and tests need review; Keith says AI can write tests merely to make them pass or select vulnerable libraries.
• Security exercises include parsing scan output and threat feeds and filtering logs.
• Keith describes using a Python JSON parser to turn Blood Hound results into a penetration-testing report, reducing manual data handling.
• Keith recommends specifying inputs, processing and desired outputs when asking AI to generate code.