The significant advancements in Large Language Models (LLMs) have resulted in their
widespread adoption across various tasks within Software Engineering (SE), including …

Software vulnerabilities pose significant security challenges and potential risks to society,
necessitating extensive efforts in automated vulnerability detection. There are two popular …

The number of new vulnerabilities continues to rise significantly each year. Simultaneously,
vulnerability databases have challenges in promptly sharing new security events with …

This paper provides a comprehensive review of the future of cybersecurity through
Generative AI and Large Language Models (LLMs). We explore LLM applications across …

With the advent of large language models (LLMs) in the artificial intelligence (AI) area, the
field of software engineering (SE) has also witnessed a paradigm shift. These models, by …

Software vendors often silently release security patches without providing sufficient
advisories (eg, Common Vulnerabilities and Exposures) or delayed updates via resources …

Large Language Models (LLMs) have emerged as powerful tools for automating various
programming tasks, including security-related ones, such as detecting and fixing …

The frequent discovery of security vulnerabilities in both open-source and proprietary
software underscores the urgent need for earlier detection during the development lifecycle …

Long contexts of recent LLMs have enabled a new use case: asking models to find security
vulnerabilities in entire codebases. To evaluate model performance on this task, we …