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ISSTA2023顶会

Detecting Vulnerabilities in Linux-Based Embedded Firmware with SSE-Based On-Demand Alias Analysis

Kai Cheng, Yaowen Zheng, Tao Liu, Le Guan, Peng Liu, Hong Li, Hongsong Zhu, Kejiang Ye, Limin Sun

2023年份
28被引次数
13顶会引用

摘要

Although the importance of using static taint analysis to detect taintstyle vulnerabilities in Linux-based embedded rmware is widely recognized, existing approaches are plagued by following major limitations: (a) Existing works cannot properly handle indirect call on the path from attacker-controlled sources to security-sensitive sinks, resulting in lots of false negatives. (b) They employ heuristics to identify mediate taint source and it is not accurate enough, which leads to high false positives. To address issues, we propose EmTaint, a novel static approach for accurate and fast detection of taint-style vulnerabilities in Linuxbased embedded rmware. In EmTaint, we rst design a structured symbolic expression-based (SSE-based) on-demand alias analysis technique. Based on it, we come up with indirect call resolution and accurate taint analysis scheme. Combined with sanitization rule checking, EmTaint can eventually discovers a large number of taint-style vulnerabilities accurately within a limited time. We evaluated EmTaint against 35 real-world embedded rmware samples from six popular vendors. The result shows EmTaint discovered at least 192 vulnerabilities, including 41 n-day vulnerabilities and 151 0-day vulnerabilities. At least 115 CVE/PSV numbers have been * Yaowen Zheng is the corresponding author

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