138 citations · 477 across the 59 of their papers we have counts for
8 papers · 1 filter
AgenticSCR: An Autonomous Agentic Secure Code Review for Immature Vulnerabilities Detection
Wachiraphan Charoenwet, Kla Tantithamthavorn, Patanamon Thongtanunam +3
Secure code review is critical during pre-integration, where Atlassian developers rely on lightweight analysis tools, while deep security assessment is deferred to later stages, de…
AdaptiveGuard: Towards Adaptive Runtime Safety for LLM-Powered Software
Rui Yang, Michael Fu, Chakkrit Tantithamthavorn +3
Guardrails are critical for the safe deployment of Large Language Models (LLMs)-powered software. Unlike traditional rule-based systems with limited, predefined input-output spaces…
Protect Your Secrets: Understanding and Measuring Data Exposure in VSCode Extensions
Yue Liu, Chakkrit Tantithamthavorn, Li Li
Recent years have witnessed the emerging trend of extensions in modern Integrated Development Environments (IDEs) like Visual Studio Code (VSCode) that significantly enhance develo…
Learning to Quantize Vulnerability Patterns and Match to Locate Statement-Level Vulnerabilities
Michael Fu, Trung Le, Van Nguyen +2
Deep learning (DL) models have become increasingly popular in identifying software vulnerabilities. Prior studies found that vulnerabilities across different vulnerable programs ma…
Cross Project Software Vulnerability Detection via Domain Adaptation and Max-Margin Principle
Van Nguyen, Trung Le, Chakkrit Tantithamthavorn +3
Software vulnerabilities (SVs) have become a common, serious and crucial concern due to the ubiquity of computer software. Many machine learning-based approaches have been proposed…
Explainable AI for Android Malware Detection: Towards Understanding Why the Models Perform So Well?
Yue Liu, Chakkrit Tantithamthavorn, Li Li +1
Machine learning (ML)-based Android malware detection has been one of the most popular research topics in the mobile security community. An increasing number of research studies ha…
Statement-Level Vulnerability Detection: Learning Vulnerability Patterns Through Information Theory and Contrastive Learning
Van Nguyen, Trung Le, Chakkrit Tantithamthavorn +6
Software vulnerabilities are a serious and crucial concern. Typically, in a program or function consisting of hundreds or thousands of source code statements, there are only a few…
Deep Learning for Android Malware Defenses: a Systematic Literature Review
Yue Liu, Chakkrit Tantithamthavorn, Li Li +1
Malicious applications (particularly those targeting the Android platform) pose a serious threat to developers and end-users. Numerous research efforts have been devoted to develop…