Using AI Assistants in Software Development: A Qualitative Study on Security Practices and Concerns

Jan H. Klemmer, Stefan Albert Horstmann, Nikhil Patnaik, Cordelia Ludden, Cordell Burton Jr., Carson Powers, Fabio Massacci, Akond Rahman, Daniel Votipka, Heather Richter Lipford, Awais Rashid, Alena Naiakshina, Sascha Fahl

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

10 Citations (Scopus)
7 Downloads (Pure)

Abstract

Following the recent release of AI assistants, such as OpenAI's ChatGPT and GitHub Copilot, the software industry quickly utilized these tools for software development tasks, e.g., generating code or consulting AI for advice. While recent research has demonstrated that AI-generated code can contain security issues, how software professionals balance AI assistant usage and security remains unclear. This paper investigates how software professionals use AI assistants in secure software development, what security implications and considerations arise, and what impact they foresee on security in software development. We conducted 27 semi-structured interviews with software professionals, including software engineers, team leads, and security testers. We also reviewed 190 relevant Reddit posts and comments to gain insights into the current discourse surrounding AI assistants for software development. Our analysis of the interviews and Reddit posts finds that, despite many security and quality concerns, participants widely use AI assistants for security-critical tasks, e.g., code generation, threat modeling, and vulnerability detection. Participants' overall mistrust leads to checking AI suggestions in similar ways to human code. However, they expect improvements and, therefore, a heavier use of AI for security tasks in the future. We conclude with recommendations for software professionals to critically check AI suggestions, for AI creators to improve suggestion security and capabilities for ethical security tasks, and for academic researchers to consider general-purpose AI in software development.
Original languageEnglish
Title of host publicationCCS '24
Subtitle of host publicationProceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security
EditorsBo Luo, Xiaojing Liao, Jun Xu, Engin Kirda, David Lie
PublisherACM SIGGRAPH
Pages2726-2740
Number of pages15
ISBN (Electronic)9798400706363
DOIs
Publication statusPublished - 9 Dec 2024
EventCCS '24: ACM SIGSAC Conference on Computer and Communications Security - Salt Lake City, United States
Duration: 14 Oct 202418 Oct 2024
https://www.sigsac.org/ccs/CCS2024/

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
PublisherACM
ISSN (Print)1543-7221

Conference

ConferenceCCS '24: ACM SIGSAC Conference on Computer and Communications Security
Abbreviated titleCCS '24
Country/TerritoryUnited States
CitySalt Lake City
Period14/10/2418/10/24
Internet address

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