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20242026
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cs.CR2026

Feedback-Driven Execution for LLM-Based Binary Analysis

XiangRui Zhang, Qiang Li, Haining Wang

Binary analysis increasingly relies on large language models (LLMs) to perform semantic reasoning over complex program behaviors. However, existing approaches largely adopt a one-p…

cs.CR2025

LLMs as Firmware Experts: A Runtime-Grown Tree-of-Agents Framework

Xiangrui Zhang, Zeyu Chen, Haining Wang +1

Large Language Models (LLMs) and their agent systems have recently demonstrated strong potential in automating code reasoning and vulnerability detection. However, when applied to…

cs.CR2025

An Analysis of Malicious Packages in Open-Source Software in the Wild

Xiaoyan Zhou, Ying Zhang, Wenjia Niu +3

The open-source software (OSS) ecosystem suffers from security threats caused by malware.However, OSS malware research has three limitations: a lack of high-quality datasets, a lac…

cs.CR2024

Tactics, Techniques, and Procedures (TTPs) in Interpreted Malware: A Zero-Shot Generation with Large Language Models

Ying Zhang, Xiaoyan Zhou, Hui Wen +4

Nowadays, the open-source software (OSS) ecosystem suffers from security threats of software supply chain (SSC) attacks. Interpreted OSS malware plays a vital role in SSC attacks,…

cs.CR2024

AutoFirm: Automatically Identifying Reused Libraries inside IoT Firmware at Large-Scale

YongLe Chen, Feng Ma, Ying Zhang +3

The Internet of Things (IoT) has become indispensable to our daily lives and work. Unfortunately, developers often reuse software libraries in the IoT firmware, leading to a major…

cs.CR2024

Obfuscating IoT Device Scanning Activity via Adversarial Example Generation

Haocong Li, Yaxin Zhang, Long Cheng +3

Nowadays, attackers target Internet of Things (IoT) devices for security exploitation, and search engines for devices and services compromise user privacy, including IP addresses,…