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Large Language Models (LLMs) such as OpenAI Codex are increasingly being usedas AI-based coding assistants. Understanding the impact of these tools ondevelopers' code is paramount, especially as recent work showed that LLMs maysuggest cybersecurity vulnerabilities. We conduct a security-driven user study(N=58) to assess code written by student programmers when assisted by LLMs.Given the potential severity of low-level bugs as well as their relativefrequency in real-world projects, we tasked participants with implementing asingly-linked 'shopping list' structure in C. Our results indicate that thesecurity impact in this setting (low-level C with pointer and arraymanipulations) is small: AI-assisted users produce critical security bugs at arate no greater than 10% more than the control, indicating the use of LLMs doesnot introduce new security risks.

Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants