all InfoSec news
Assessing Cybersecurity Vulnerabilities in Code Large Language Models
April 30, 2024, 4:11 a.m. | Md Imran Hossen, Jianyi Zhang, Yinzhi Cao, Xiali Hei
cs.CR updates on arXiv.org arxiv.org
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
More from arxiv.org / cs.CR updates on arXiv.org
Jobs in InfoSec / Cybersecurity
Information Security Engineers
@ D. E. Shaw Research | New York City
Technology Security Analyst
@ Halton Region | Oakville, Ontario, Canada
Senior Cyber Security Analyst
@ Valley Water | San Jose, CA
COMM Penetration Tester (PenTest-2), Chantilly, VA OS&CI Job #368
@ Allen Integrated Solutions | Chantilly, Virginia, United States
Consultant Sécurité SI H/F Gouvernance - Risques - Conformité
@ Hifield | Sèvres, France
Infrastructure Consultant
@ Telefonica Tech | Belfast, United Kingdom