21 citations · 46 across the 12 of their papers we have counts for
12 papers
The Data Problem in Software Vulnerability Analysis: Artifacts, Quality, and Consumption
Yu Nong, Yao Du, Tianxiang Xu +1
Learning- and LLM-based software vulnerability analysis is only as trustworthy as the data it is trained and evaluated on, yet that data is rarely examined as a first-class object.…
A Comprehensive Study of Native Code Bugs in Python Applications
Haoran Yang, Haipeng Cai
The impact of Python applications has been evidenced by their widespread presence in some of the most impactful software domains, such as machine learning frameworks and scientific…
POLYFLOW: A Neuro-Symbolic Framework for Static Cross-Language Information Flow Analysis
Haoran Yang, Zhixuan Zhong, Jiawei Guo +1
Modern software systems are commonly constructed in multiple, interacting programming languages. This construction leads to additional, often stealthy vulnerabilities buried in com…
How Reliable Are NVD CWE Labels? A Large-Scale Semantic Audit with Seclometry
Yu Nong, Yao Du, Majid Behravan +1
CWE labels in the National Vulnerability Database (NVD) are widely treated as ground truth for vulnerability search, scanner evaluation, benchmark construction, learning-based secu…
Dissecting Software Graphs: Structural Insights for Driver-Guided Fuzzing
Baihong Chen, Hua Ming, Weifeng Pan +3
Many software systems expose multiple execution modes through command-line options, subcommands, and configuration flags. For such programs, fuzzing depends on both mutated inputs…
Neuro-Symbolic Proof-of-Vulnerability Generation with Open-Weight Models
Yu Nong, Haipeng Cai
Software vulnerabilities are persistent, but validating them remains difficult: a Proof-of-Vulnerability (PoV) requires a concrete input that triggers the vulnerable behavior, yet…
System Prompt Poisoning: Persistent Attacks on Large Language Models Beyond User Injection
Zongze Li, Jiawei Guo, Haipeng Cai
Large language models (LLMs) have gained widespread adoption across diverse applications due to their impressive generative capabilities. Their plug-and-play nature enables both de…
Enhancing Android Malware Detection: The Influence of ChatGPT on Decision-centric Task
Yao Li, Sen Fang, Tao Zhang +1
With the rise of large language models, such as ChatGPT, non-decisional models have been applied to various tasks. Moreover, ChatGPT has drawn attention to the traditional decision…
APPATCH: Automated Adaptive Prompting Large Language Models for Real-World Software Vulnerability Patching
Yu Nong, Haoran Yang, Long Cheng +2
Timely and effective vulnerability patching is essential for cybersecurity defense, for which various approaches have been proposed yet still struggle to generate valid and correct…
VulScribeR: Exploring RAG-based Vulnerability Augmentation with LLMs
Seyed Shayan Daneshvar, Yu Nong, Xu Yang +2
Detecting vulnerabilities is vital for software security, yet deep learning-based vulnerability detectors (DLVD) face a data shortage, which limits their effectiveness. Data augmen…
From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future
Haolin Jin, Linghan Huang, Haipeng Cai +3
With the rise of large language models (LLMs), researchers are increasingly exploring their applications in var ious vertical domains, such as software engineering. LLMs have achie…
Chain-of-Thought Prompting of Large Language Models for Discovering and Fixing Software Vulnerabilities
Yu Nong, Mohammed Aldeen, Long Cheng +3
Security vulnerabilities are increasingly prevalent in modern software and they are widely consequential to our society. Various approaches to defending against these vulnerabiliti…