Security of LLM-generated Code: A Comparative Analysis
A recent paper analyzes the security of code generated by Large Language Models (LLMs). The study finds that all evaluated LLMs produce code with vulnerabilities, many of which are critical or high severity. This raises concerns about the risks associated with using AI tools in software development.
- ▪The majority of software developers are using or planning to use AI tools in their development processes.
- ▪The paper evaluates the security of code generated by seven popular LLMs.
- ▪All seven LLMs evaluated were found to generate code containing vulnerabilities.
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Computer Science > Software Engineering arXiv:2605.23091 (cs) [Submitted on 21 May 2026] Title:Security of LLM-generated Code: A Comparative Analysis Authors:Srivathsan G Morkonda, Mahmoud Selim, Hala Assal View a PDF of the paper titled Security of LLM-generated Code: A Comparative Analysis, by Srivathsan G Morkonda and 2 other authors View PDF Abstract: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.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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