Survey on automated vulnerability mining techniques for IoT device firmware

LIU Hangtian; GAN Shuitao; ZHANG Chao; ZHANG Hongqi; SUN Wenhou; GAO Zicong; ZHAO Min; BAI Xue

doi:10.11959/j.issn.2096-109x.2025014

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Survey on automated vulnerability mining techniques for IoT device firmware

Comprehensive Reviews | 更新时间：2025-05-14

- Survey on automated vulnerability mining techniques for IoT device firmware
- Chinese Journal of Network and Information Security Vol. 11, Issue 2, Pages: 26-49(2025)
- 作者机构：
  
  1.信息工程大学，河南郑州 450001
  2.先进计算与智能工程国家级重点实验室，江苏无锡 214084
  3.清华大学，北京 100084
  4.中关村实验室，北京 100190
  5.河南省信息安全重点实验室，河南郑州 450001
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-109x.2025014
  CLC： TP393
- Received：30 July 2024，
  
  Revised：2024-11-27，
  
  Published：25 April 2025
- 稿件说明：
移动端阅览
刘航天, 甘水滔, 张超, 等. 物联网设备固件自动化漏洞挖掘技术研究综述[J]. 网络与信息安全学报, 2025, 11(2): 26-49.

LIU H T, GAN S T, ZHANG C, et al. Survey on automated vulnerability mining techniques for IoT device firmware[J]. Chinese Journal of Network and Information Security, 2025, 11(2): 26-49.
刘航天, 甘水滔, 张超, 等. 物联网设备固件自动化漏洞挖掘技术研究综述[J]. 网络与信息安全学报, 2025, 11(2): 26-49. DOI： 10.11959/j.issn.2096-109x.2025014.

LIU H T, GAN S T, ZHANG C, et al. Survey on automated vulnerability mining techniques for IoT device firmware[J]. Chinese Journal of Network and Information Security, 2025, 11(2): 26-49. DOI： 10.11959/j.issn.2096-109x.2025014.

摘要

随着物联网技术的广泛应用，物联网设备爆炸式增长。近年来，物联网设备导致的安全事件频发，使得物联网设备安全研究成为热点。首先，对物联网设备固件的安全特性（包括黑盒特性、网络特性和定制化特性）进行了深入剖析，这些特性给自动化漏洞挖掘带来了新的挑战。固件代码闭源、运行环境封闭、网络交互复杂、软硬件高度定制化，这些都增加了固件安全分析的难度。针对这些挑战，研究人员研发了一系列解决方案。通过对现有文献进行综合分析，从黑盒模糊测试、灰盒模糊测试、静态程序分析和固件重托管4个方面，总结了物联网设备固件自动化漏洞挖掘技术的最新研究进展。在此基础上，分析了尚存在的挑战和不足，并提出了未来的研究方向和思路，包括多种技术有机组合的发展趋势、大语言模型在自动化漏洞挖掘中的应用前景，以及物联网技术演进驱动漏洞挖掘技术的同步升级。通过对物联网设备固件自动化漏洞挖掘技术现状及发展趋势的深入剖析和总结，为业界下一步研究及应用提供有价值的参考。

Abstract

With the wide application of IoT technology

IoT devices have exploded. In recent years

security incidents caused by IoT devices have occurred frequently

which makes the research of IoT device security become a hot spot. The security analysis of IoT device firmware has been conducted

with a focus on its black-box nature

network characteristics

and customization features. Challenges to automated vulnerability mining have been highlighted

such as the closed-source firmware code

closed operating environment

complex network interactions

and highly customized hardware-software. Researchers have proposed a series of advanced technologies and methods to address these challenges. The existing literature was comprehensively analyzed

and the latest research progress in automated vulnerability mining technology for IoT device firmware was summarized from four aspects: black-box fuzzing

gray-box fuzzing

static program analysis

and firmware re-hosting. Based on the analysis of the current research status

existing challenges and deficiencies were pointed out

and future research directions and ideas were proposed

including the development trend of multi-technology organically combination

the application prospects of large language models in automated vulnerability mining

and the synchronous upgrade of vulnerability mining technology driven by the evolution of IoT technology. An in-depth analysis and summary of the current status and development trends of automated vulnerability mining technology for IoT device firmware were provided

offering valuable references for future research and applications in the industry.

关键词

Keywords

references

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Detecting privacy compliance of mobile applications from the perspective of the "minimum necessary" principle

Instruction and demonstration-based secure service attribute generation mechanism for textual data

Related Author

Han Hao

Wu Zicheng

Zhao Xinjian

Ding Yixin

WANG Yuanyuan

FENG Haokang

WU Xuguang

HAN Yiliang

Related Institution

State Grid Jiangsu Electric Power Co., Ltd.

Nanjing University of Aeronautics and Astronautics

College of Cryptography Engineering, Engineering University of PAP

Key Laboratory of Counter-Terrorism Command Information Engineering of the Ministry of Education, Engineering University of PAP

State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology, China Electric Power Research Institute

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