Privacy-Conscious Development with AI Assistants

Learn to use AI coding assistants while maintaining privacy and security standards in production development workflows. You will explore privacy-conscious development principles, comparing web-based and command-line AI tool interfaces to understand their data handling characteristics and privacy implications. The course covers GitHub Advanced Security and Grype for automated vulnerability scanning, and hands-on AI-assisted code review using Claude Code to detect security issues including hardcoded passwords, exposed API keys, and common vulnerabilities. You will evaluate multiple AI tools including Windsurf and Gemini CLI, learning safe usage practices and secure prompting techniques that avoid exposing sensitive data. The security vulnerabilities module covers detecting and preventing SQL injection, path traversal in file handling, HTTP header misconfiguration, and vulnerable code patterns using AI analysis. You will implement security automation with GitHub Advanced Security code scanning, Dependabot for automated dependency updates, container scanning with Grype, and comprehensive security scanning pipelines for continuous vulnerability detection. By completing this course, you will be able to select and configure AI coding assistants based on privacy requirements, conduct AI-assisted security code reviews, and build automated security scanning pipelines that protect production applications.