信息安全研究 ›› 2024, Vol. 10 ›› Issue (1): 40-.

• 学术论文 • 上一篇    下一篇

基于静态分析和模糊测试的路由器漏洞检测方法

王洪义1沙乐天1,2   

  1. 1(南京邮电大学计算机学院、软件学院、网络空间安全学院南京210023)
    2(江苏省无线传感网高技术研究重点实验室南京210023)

  • 出版日期:2024-01-10 发布日期:2024-01-21
  • 通讯作者: 王洪义 硕士.主要研究方向为物联网安全、漏洞挖掘. hongyi0228@163.com
  • 作者简介:王洪义 硕士.主要研究方向为物联网安全、漏洞挖掘. hongyi0228@163.com 沙乐天 博士,副教授.主要研究方向为软件安全、网络安全、物联网安全. ltsha@njupt.edu.cn

Router Vulnerability Detection Method Based on Static Analysis and Fuzzing

Wang Hongyi1 and Sha Letian1,2#br#

#br#
  

  1. 1(School of Computer Science, Nanjing University of Posts and Telecomunications, Nanjing 210023)
    2(Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210023)

  • Online:2024-01-10 Published:2024-01-21

摘要: 针对路由器设备的网络攻击往往会造成严重后果.模糊测试是检测路由器设备安全漏洞的有效方法.然而,如果没有对目标设备的固件进行足够的分析,模糊测试往往是盲目和无效的.提出一种使用静态分析辅助模糊测试对路由器设备进行漏洞检测的方法.具体来讲,就是通过静态分析生成的结果指导测试用例的变异来对路由器设备的Web接口进行模糊测试.路由器固件中隐藏着大量有用的信息,通过静态分析提取程序代码可能存在的漏洞点,用来构建测试用例以提高模糊测试的效率.实现一个原型系统,并在4家主流路由器厂商的46个路由器固件上进行测试,发现16个漏洞,其中4个是零日漏洞.结果表明,与先进的自动化漏洞挖掘方法相比,该系统可以检测现有漏洞检测工具无法检测的漏洞.

关键词: 静态分析, 模糊测试, 固件, 漏洞挖掘, Web接口

Abstract: Network attacks targeting router devices often have serious consequences. Fuzzing testing is an effective method to detect security vulnerabilities in router devices. However, without sufficient analysis of the firmware of the target device, fuzzy testing is often blind and ineffective. In this paper, we propose a method of using static analysis assisted fuzzy testing to detect vulnerabilities in router devices. Specifically, the results generated by static analysis are used to construct more effective test cases to fuzz the web interface of the router device. Our opinion is that there is a lot of useful information hidden in the router firmware. We use static analysis to extract the possible loopholes in the program code to build test cases and improve the efficiency of fuzzing. We implemented a prototype system and tested it on 46 router firmware from 4 mainstream router vendors, and found 16 vulnerabilities, 4 of which were 0day vulnerabilities. The results show that our system can detect vulnerabilities that cannot be detected by existing vulnerability detection tools compared to advanced automated vulnerability mining methods. 

Key words: static analysis, fuzzing, firmware, vulnerability mining, Web interface

中图分类号: