Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants
Published in USENIX Security Symposium (USENIX Security '23), 2023
A security-driven user study (N=58) measuring whether LLM code assistants like OpenAI Codex lead student programmers to write less secure low-level C code. We find the security impact is small.
Recommended citation: Gustavo Sandoval, Hammond Pearce, Teo Nys, Ramesh Karri, Siddharth Garg, and Brendan Dolan-Gavitt. (2023). "Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants." 32nd USENIX Security Symposium. https://www.usenix.org/system/files/sec23summer_sandoval.pdf