5 papers
Semantic Integrity Failures in Document-to-LLM Supply Chains
Side Liu, Jiang Ming
Document-to-LLM applications typically read uploaded PDFs by first translating them into text through a hidden extraction layer that users cannot observe or audit. We show that thi…
Analyzing PDFs like Binaries: Adversarially Robust PDF Malware Analysis via Intermediate Representation and Language Model
Side Liu, Jiang Ming, Guodong Zhou +3
Malicious PDF files have emerged as a persistent threat and become a popular attack vector in web-based attacks. While machine learning-based PDF malware classifiers have shown pro…
Resolving Indirect Calls in Binary Code via Cross-Reference Augmented Graph Neural Networks
Haotian Zhang, Kun Liu, Cristian Garces +3
Binary code analysis is essential in scenarios where source code is unavailable, with extensive applications across various security domains. However, accurately resolving indirect…
Retrofitting XoM for Stripped Binaries without Embedded Data Relocation
Chenke Luo, Jiang Ming, Mengfei Xie +2
In this paper, we present PXoM, a practical technique to seamlessly retrofit XoM into stripped binaries on the x86-64 platform. As handling the mixture of code and data is a well-k…
STEPWISE-CODEX-Bench: Evaluating Complex Multi-Function Comprehension and Fine-Grained Execution Reasoning
Kaiwen Yan, Yuhang Chang, Zirui Guo +3
In recent years, large language models (LLMs) have made significant progress in code intelligence, yet systematically evaluating their code understanding and reasoning abilities re…