We propose and release a new vulnerable source code dataset. We curate the dataset by
crawling security issue websites, extracting vulnerability-fixing commits and source codes …

Over the past decade, Open Source Software (OSS) has experienced rapid growth and
widespread adoption, attributed to its openness and editability. However, this expansion has …

DevOps has emerged as one of the most rapidly evolving software development paradigms.
With the growing concerns surrounding security in software systems, the DevSecOps …

Detecting vulnerabilities in source code using graph neural networks (GNN) has gained
significant attention in recent years. However, the detection performance of these …

Misconfigurations are major causes of software failures. Existing practices rely on developer-
written rules or test cases to validate configurations, which are expensive. Machine learning …

Large Language Models (LLMs) have been suggested for use in automated vulnerability
repair, but benchmarks showing they can consistently identify security-related bugs are …

Security vulnerabilities are increasingly prevalent in modern software and they are widely
consequential to our society. Various approaches to defending against these vulnerabilities …

Amidst the rapid development of the software industry and the burgeoning open-source
culture, vulnerability detection within the software security domain has emerged as an ever …

Large Language Models (LLMs) have been suggested for use in automated vulnerability
repair, but benchmarks showing they can consistently identify security-related bugs are …

Despite decades of research in vulnerability detection, vulnerabilities in source code remain
a growing problem, and more effective techniques are needed in this domain. To enhance …