all InfoSec news
Security Weaknesses of Copilot Generated Code in GitHub
April 5, 2024, 4:11 a.m. | Yujia Fu, Peng Liang, Amjed Tahir, Zengyang Li, Mojtaba Shahin, Jiaxin Yu, Jinfu Chen
cs.CR updates on arXiv.org arxiv.org
Abstract: Modern code generation tools, utilizing AI models like Large Language Models (LLMs), have gained popularity for producing functional code. However, their usage presents security challenges, often resulting in insecure code merging into the code base. Evaluating the quality of generated code, especially its security, is crucial. While prior research explored various aspects of code generation, the focus on security has been limited, mostly examining code produced in controlled environments rather than real-world scenarios. To address …
ai models arxiv base challenges code code base copilot cs.cr cs.se generated github insecure language language models large llms producing quality security security challenges tools weaknesses
More from arxiv.org / cs.CR updates on arXiv.org
Jobs in InfoSec / Cybersecurity
Senior Security Researcher
@ Microsoft | Redmond, Washington, United States
Sr. Cyber Risk Analyst
@ American Heart Association | Dallas, TX, United States
Cybersecurity Engineer 2/3
@ Scaled Composites, LLC | Mojave, CA, US
Information Security Operations Manager
@ DP World | Charlotte, NC, United States
Sr Cyber Security Engineer I
@ Staples | Framingham, MA, United States
Security Engineer - Heartland (Remote)
@ GuidePoint Security LLC | Remote in the US