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Found 4 papers, 3 papers with code
Do Neutral Prompts Produce Insecure Code? FormAI-v2 Dataset: Labelling Vulnerabilities in Code Generated by Large Language Models
This study provides a comparative analysis of state-of-the-art large language models (LLMs), analyzing how likely they generate vulnerabilities when writing simple C programs using a neutral zero-shot prompt.
LLMs in Web Development: Evaluating LLM-Generated PHP Code Unveiling Vulnerabilities and Limitations
This study evaluates the security of web application code generated by Large Language Models, analyzing 2, 500 GPT-4 generated PHP websites.
CyberMetric: A Benchmark Dataset based on Retrieval-Augmented Generation for Evaluating LLMs in Cybersecurity Knowledge
The results can serve as a reference for comparing the general cybersecurity knowledge of humans and LLMs.
The FormAI Dataset: Generative AI in Software Security Through the Lens of Formal Verification
This paper presents the FormAI dataset, a large collection of 112, 000 AI-generated compilable and independent C programs with vulnerability classification.
