Harnessing Large Language Models for Software Vulnerability Detection: A Comprehensive Benchmarking Study
K Tamberg, H Bahsi - arXiv preprint arXiv:2405.15614, 2024 - arxiv.org
Despite various approaches being employed to detect vulnerabilities, the number of
reported vulnerabilities shows an upward trend over the years. This suggests the problems …
reported vulnerabilities shows an upward trend over the years. This suggests the problems …
Towards Effectively Detecting and Explaining Vulnerabilities Using Large Language Models
Software vulnerabilities pose significant risks to the security and integrity of software
systems. Prior studies have proposed a series of approaches to vulnerability detection using …
systems. Prior studies have proposed a series of approaches to vulnerability detection using …
Can large language models find and fix vulnerable software?
D Noever - arXiv preprint arXiv:2308.10345, 2023 - arxiv.org
In this study, we evaluated the capability of Large Language Models (LLMs), particularly
OpenAI's GPT-4, in detecting software vulnerabilities, comparing their performance against …
OpenAI's GPT-4, in detecting software vulnerabilities, comparing their performance against …
VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models
Large Language Models (LLMs) have training corpora containing large amounts of program
code, greatly improving the model's code comprehension and generation capabilities …
code, greatly improving the model's code comprehension and generation capabilities …
Understanding the effectiveness of large language models in detecting security vulnerabilities
Security vulnerabilities in modern software are prevalent and harmful. While automated
vulnerability detection tools have made promising progress, their scalability and applicability …
vulnerability detection tools have made promising progress, their scalability and applicability …
Multi-role Consensus through LLMs Discussions for Vulnerability Detection
Recent advancements in large language models (LLMs) have highlighted the potential for
vulnerability detection, a crucial component of software quality assurance. Despite this …
vulnerability detection, a crucial component of software quality assurance. Despite this …
DLAP: A Deep Learning Augmented Large Language Model Prompting Framework for Software Vulnerability Detection
Software vulnerability detection is generally supported by automated static analysis tools,
which have recently been reinforced by deep learning (DL) models. However, despite the …
which have recently been reinforced by deep learning (DL) models. However, despite the …
Securefalcon: The next cyber reasoning system for cyber security
Software vulnerabilities leading to various detriments such as crashes, data loss, and
security breaches, significantly hinder the quality, affecting the market adoption of software …
security breaches, significantly hinder the quality, affecting the market adoption of software …
GRACE: Empowering LLM-based software vulnerability detection with graph structure and in-context learning
Software vulnerabilities inflict considerable economic and societal harm. Therefore, timely
and accurate detection of these flaws has become vital. Large language models (LLMs) …
and accurate detection of these flaws has become vital. Large language models (LLMs) …
Using large language models to better detect and handle software vulnerabilities and cyber security threats
SM Taghavi, F Feyzi - 2024 - researchsquare.com
Abstract Large Language Models (LLMs) have emerged as powerful tools in the domain of
software vulnerability and cybersecurity tasks, offering promising capabilities in detecting …
software vulnerability and cybersecurity tasks, offering promising capabilities in detecting …