Application Security in AI Prompt Engineering
In today’s rapidly evolving technological landscape, AI has become a key tool in software development. However, ensuring that AI-generated code adheres to strict security standards is critical, especially for building web applications in environments like React. This two-day curriculum is designed to provide participants with the knowledge and skills to integrate secure coding principles into AI prompt engineering, focusing on how to craft prompts that lead to secure and robust code. The curriculum covers foundational application security concepts, common vulnerabilities, and techniques for ensuring AI-generated code meets the highest security standards.
Day 1: Foundations of Application Security in AI Prompt Engineering
- Introduction to Application Security and AI - Overview of the foundational principles of application security. - Introduction to AI in software development and the role of prompt engineering in influencing the security of AI-generated code. - Understanding the risks associated with AI-based code generation and why security should be a priority from the start.
- OWASP Top 10 Overview in the Context of AI - A detailed review of the OWASP Top 10 security vulnerabilities and how they manifest in web applications. - Examining real-world examples where AI-generated code can introduce vulnerabilities if not guided properly. - How to use AI to mitigate common risks like cross-site scripting (XSS), injection attacks, and improper authentication handling. - Exercise: Participants analyze AI-generated code for security vulnerabilities related to the OWASP Top 10 and discuss how to craft better prompts to avoid these issues.
- Crafting Secure Prompts for Code Generation - Best practices for constructing AI prompts that lead to secure and well-structured code. - Techniques for encouraging the AI to implement security best practices, such as input validation, secure authentication mechanisms, and error handling. - Prompt examples to help AI follow secure frameworks and design patterns, particularly in environments like React, Node.js, and other modern web development frameworks. - Exercise: Participants craft and test prompts designed to generate secure code and avoid common vulnerabilities like SQL injection, XSS, and data exposure.
Day 2: Advanced Techniques and Practical Applications
- Secure Software Development Lifecycle (SDLC) with AI Assistance - Integrating security into the software development lifecycle when using AI for code generation. - Ensuring that AI-generated code complies with industry security standards and best practices throughout development phases. - Key checkpoints for validating and verifying security during development and testing.
- Practical Prompt Engineering for Secure Coding in React - Deep dive into prompt engineering techniques for generating secure React code. - How to guide AI to implement safe component design, secure state management, and secure API interactions in React-based applications. - Exercise: Participants create and refine prompts that generate secure React components with proper security and design controls in place.
- Threat Modeling and AI-Assisted Security - Introduction to threat modeling and how it can be applied to AI-generated code. - How to prompt AI to consider security risks at every stage of code development. - Identifying potential threats, attack vectors, and ways to mitigate them through careful prompt design. - Exercise: Participants perform a basic threat model on AI-generated code and refine prompts to address identified security concerns.
Conclusion and Takeaways
By the end of this two-day course, participants will have a solid understanding of how to integrate application security principles into AI prompt engineering. They will be equipped with practical skills to craft prompts that guide AI to generate secure, scalable, and robust web applications. Additionally, they will gain insights into common vulnerabilities and the strategies needed to mitigate them in AI-generated code.
Jim Manico is the founder of Manicode Security where he trains software developers on secure coding and security engineering. He is also an investor/advisor for KSOC, Nucleus Security, Signal Sciences, and BitDiscovery. Jim is a frequent speaker on secure software practices, is a Java Champion, and is the author of 'Iron-Clad Java - Building Secure Web Applications' from Oracle Press. Jim also volunteers for OWASP as the project co-lead for the OWASP ASVS and the OWASP Proactive Controls.