Abstract:Most IoT malware operates as botnets dependent on Command and Control (C2) servers, but the short-lived nature of attack infrastructure often leaves samples dormant without C2 communication, hindering dynamic analysis. This paper proposes a system that combines Ghidra with a Large Language Model (LLM) to extract communication specifications from a malware binary and automatically generate a pseudo-C2 server. Experiments using Mirai demonstrate that the proposed system semantically interprets binary control structures and extracts all 20 core protocol elements in agreement with the ground truth (100\% specification extraction accuracy). The generated pseudo-C2 server fully reproduces seven of ten DDoS attack vectors with attack behavior consistent with the original C2. When applied to a customized variant created by modifying the publicly available Mirai source code, the method succeeds end-to-end -- from specification extraction through pseudo-C2 generation to attack reproduction -- demonstrating that the LLM infers specifications from binary structures without relying on pre-trained knowledge. This approach extends the applicability of LLMs from analysis assistance to the automated construction of dynamic analysis environments.
From: Masaki Hashimoto Assoc. Prof. [view email]
[v1]
Fri, 19 Jun 2026 11:46:47 UTC (237 KB)
此内容由惯性聚合(RSS阅读器)自动聚合整理，仅供阅读参考。 原文来自 — 版权归原作者所有。