一句话：提出 FITS，通过推断中间污点源补全闭源固件中的污点传播路径，提升 IoT 固件漏洞分析效果。
论文关注 IoT 设备固件漏洞发现问题。固件漏洞可能导致针对物理设备的网络攻击，而污点分析因覆盖率高、可扩展性好成为有前景的技术。然而，大量固件闭源，从 recv 等接口库函数这类污点源到 sink 的完整数据流路径难以直接获得，限制了污点分析效果。FITS 的核心思路是推断中间污点源，以在缺少完整源到汇路径的情况下恢复或补充污点传播链，从而支持更有效的漏洞分析。摘要未给出具体实现细节与实验结果，需进一步阅读论文了解其推断机制、工具实现及在真实固件上的评估。
Finding vulnerabilities in firmware is vital as any firmware vulnerability may lead to cyberattacks to the physical IoT devices. Taint analysis is one promising technique for finding firmware vulnerabilities thanks to its high coverage and scalability. However, sizable closed-source firmware makes it extremely difficult to analyze the complete data-flow paths from taint sources (i.e., interface library functions such as recv) to sinks.
@inproceedings{paperbot10125,
title = {FITS: Inferring Intermediate Taint Sources for Effective Vulnerability Analysis of IoT Device Firmware},
author = {Puzhuo Liu and Yaowen Zheng and Chengnian Sun and Chuan Qin and Dongliang Fang and Mingdong Liu and Limin Sun},
booktitle = {ASPLOS},
year = {2023},
doi = {10.1145/3623278.3624759}
}