Security of LLM-generated Code: A Comparative Analysis

Computer Science > Software Engineering [Submitted on 21 May 2026] Security of LLM-generated Code: A Comparative Analysis Srivathsan G Morkonda, Mahmoud Selim, Hala Assal The majority of software developers use or are planning to use Artificial Intelligence (AI) tools in their development processes. Their top reasons include improving productivity and faster learning. In fact, Large Language Model (LLM)-generated code is currently in production, including in major tech companies. However, concerns were raised about the risks associated with the use of AI tools to generate code. In this paper, we focus our attention on the risks to software security. We empirically evaluate the security of code generated by seven popular LLMs. We build upon previous work to mimic the behaviours of developers when using LLMs to generate code. Our results show that all seven LLMs that we have evaluated generate code that contains vulnerabilities, the majority of which are of critical or high severity. Subjects: Software Engineering (cs.SE); Artificial Intelligence (cs.AI); Cryptography and Security (cs.CR) Cite as: arXiv:2605.23091 [cs.SE]   (or arXiv:2605.23091v1 [cs.SE] for this version)   https://doi.org/10.48550/arXiv.2605.23091 Focus to learn more Submission history From: Hala Assal [view email] [v1] Thu, 21 May 2026 22:53:40 UTC (4,813 KB) Access Paper: view license Current browse context: cs.SE < prev   |   next > new | recent | 2026-05 Change to browse by: cs cs.AI cs.CR References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)