An Improved Method for Dynamic Taint Analysis
Ling Zhong, E Shengguo, Shibo Lin, Shuo Li · 2024
Dynamic taint analysis methods, due to their language independence, reliance on binary code, and high accuracy, have been widely applied in the field of binary program vulnerability detection and security. However, these methods often incur significant performance overhead due to binary instrumentation. To address these issues, this study first categorizes x86 instructions and designs corresponding taint propagation strategies for each instruction category. It introduces the concept of taint analysis-agnostic classes to reduce redundant analysis and minimize performance overhead. Furthermore, a taint flow filtering mechanism is proposed during the taint propagation process to reduce inefficient analysis and improve analysis efficiency. Experimental results demonstrate that the improved dynamic taint analysis method can accurately detect vulnerabilities with CVE identifiers and outperforms traditional dynamic taint analysis methods in terms of performance. Therefore, the proposed improved dynamic taint analysis method effectively enhances both detection effectiveness and performance.