Assessing Cybersecurity Vulnerabilities in Code Large Language Models

arXiv:2404.18567v1 Announce Type: new
Abstract: Instruction-tuned Code Large Language Models (Code LLMs) are increasingly utilized as AI coding assistants and integrated into various applications. However, the cybersecurity vulnerabilities and implications arising from the widespread integration of these models are not yet fully understood due to limited research in this domain. To bridge this gap, this paper presents EvilInstructCoder, a framework specifically designed to assess the cybersecurity vulnerabilities of instruction-tuned Code LLMs to adversarial attacks. EvilInstructCoder introduces the Adversarial Code Injection …

ai coding applications arxiv bridge code coding cs.cr cybersecurity cybersecurity vulnerabilities domain integration language language models large llms research vulnerabilities