Vulnerabilities in ai code generators: Exploring targeted data poisoning attacks

D Cotroneo, C Improta, P Liguori… - Proceedings of the 32nd …, 2024 - dl.acm.org
AI-based code generators have become pivotal in assisting developers in writing software
starting from natural language (NL). However, they are trained on large amounts of data …

Securing Large Language Models: Threats, Vulnerabilities and Responsible Practices

S Abdali, R Anarfi, CJ Barberan, J He - arXiv preprint arXiv:2403.12503, 2024 - arxiv.org
Large language models (LLMs) have significantly transformed the landscape of Natural
Language Processing (NLP). Their impact extends across a diverse spectrum of tasks …

CoSec: On-the-Fly Security Hardening of Code LLMs via Supervised Co-decoding

D Li, M Yan, Y Zhang, Z Liu, C Liu, X Zhang… - Proceedings of the 33rd …, 2024 - dl.acm.org
Large Language Models (LLMs) specialized in code have shown exceptional proficiency
across various programming-related tasks, particularly code generation. Nonetheless, due …

Ocassionally secure: A comparative analysis of code generation assistants

R Elgedawy, J Sadik, S Dutta, A Gautam… - arXiv preprint arXiv …, 2024 - arxiv.org
$$ Large Language Models (LLMs) are being increasingly utilized in various applications,
with code generations being a notable example. While previous research has shown that …

An Exploratory Study on Fine-Tuning Large Language Models for Secure Code Generation

J Li, F Rabbi, C Cheng, A Sangalay, Y Tian… - arXiv preprint arXiv …, 2024 - arxiv.org
AI-powered coding assistants such as GitHub Copilot and OpenAI ChatGPT have achieved
notable success in automating code generation. However, these tools rely on pre-trained …