AI Code Assistants in Secure Software Development: Opportunities, Risks, and Best Practices

Abstract

Software development productivity, code quality, and knowledge sharing have all increased dramatically with the use of AI code assistants like GitHub Copilot. These technologies provide real-time suggestions, expedite workflows, and speed up prototyping by utilising massive language models that have been trained on extensive code repositories. However, serious questions about software security, developer dependency, and ethical ramifications are brought up by their increasing use. The advantages and disadvantages of AI code helpers for safe software development are discussed in this study. It highlights how crucial human oversight, frequent security audits, ongoing model upgrades, and conformity to DevSecOps and OWASP guidelines are. In the end, software integrity cannot be jeopardised by including AI into development processes. In an increasingly automated development context, strategic implementation is crucial to maximising AI's benefits while protecting against new risks.

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