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Accurate and Efficient Recurring Vulnerability Detection for IoT Firmware

Haoyu Xiao, Yuan Zhang, Minghang Shen, Chaoyang Lin, Can Zhang, Shengli Liu, Min Yang

2024Year
5Citations
4Top-tier citations

Abstract

IoT firmware faces severe threats to security vulnerabilities. As an important method to detect vulnerabilities, recurring vulnerability detection has not been systematically studied in IoT firmware. In fact, existing methods would meet significant challenges from two aspects. First, firmware vulnerabilities are usually reported in texts without too much code-level information, e.g., security patches. Second, firmware images are released as binaries, making the analysis of known vulnerabilities and the detection of unknown vulnerabilities quite difficult.

This paper presents FirmRec, the first recurring vulnerability detection approach for IoT firmware. FirmRec features several new techniques to enable accurate and efficient vulnerability detection.

First, it proposes a new exploitation-based vulnerability signature representation for firmware, which does not use syntactic code features but the semantic features along the dynamic vulnerability exploitation procedure (thus is more resilient to binary code changes and fits the context of binary-only firmware). Second, given a vulnerability report, it designs concolic execution-based vulnerability signature extraction to understand the vulnerability exploitation procedure and generate an exploitation-based vulnerability signature. Third, based on known vulnerability signatures, it employs a two-stage pipeline to accurately and efficiently detect recurring vulnerabilities.

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