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Found 4 papers, 1 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.
CyberMetric: A Benchmark Dataset for Evaluating Large Language Models Knowledge in Cybersecurity
Large Language Models (LLMs) excel across various domains, from computer vision to medical diagnostics.
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.
A New Era in Software Security: Towards Self-Healing Software via Large Language Models and Formal Verification
In this paper we present a novel solution that combines the capabilities of Large Language Models (LLMs) with Formal Verification strategies to verify and automatically repair software vulnerabilities.
