ConfTainter: Static Taint Analysis For Configuration Options
Teng Wang, Haochen He, Xiaodong Liu, Shanshan Li, Zhouyang Jia, Yu Jiang, Qing Liao, Wang Li
摘要
The prevalence and severity of software configuration-induced issues have driven the design and development of a number of detection and diagnosis techniques. Many of these techniques need to perform static taint analysis on configuration-related variables to analyze the data flow, control flow, and execution paths given by configuration options. However, existing taint analysis or static slicer tools are not suitable for configuration analysis due to the complex effects of configuration on program behaviors. In this experience paper, we conducted an empirical study on the propagation policy of configuration options. We concluded four rules of how configurations affect program behaviors, among which implicit data-flow and control-flow propagation are often ignored by existing tools. We report our experience designing and implementing a taint analysis infrastructure for configurations, ConfTainter. It can support various kinds of configuration analysis, e.g., explicit or implicit analysis for data or control flow. Based on the infrastructure, researchers and developers can easily implement analysis techniques for different configuration-related targets, e.g., misconfiguration detection. We evaluated the effectiveness of ConfTainter on 5 popular open-source systems. The result shows that the accuracy rate of data- and control-flow analysis is 96.1% and 97.7%, and the recall rate is 94.2% and 95.5%, respectively. We also apply ConfTainter to two types of configuration-related tasks: misconfiguration detection and configuration-related bug detection. The result shows that ConfTainter is highly applicable for configuration-related tasks with a few lines of code.
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引用它的顶会 Paper4
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- The Same Only Different: On Information Modality for Configuration Performance AnalysisHongyuan Liang, Yue Huang, Tao ChenICSE 2025 · 被引用 3 次
- ConfLogger: Enhance Systems' Configuration Diagnosability through Configuration LoggingShiwen Shan, Yintong Huo, Yuxin Su, Zhining Wang 等ICSE 2026
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- Directed Greybox FuzzingMarcel Böhme, Van-Thuan Pham, Manh-Dung Nguyen, Abhik RoychoudhuryCCS 2017 · 被引用 836 次
- Neutaint: Efficient Dynamic Taint Analysis with Neural NetworksDongdong She, Yizheng Chen, Abhishek Shah, Baishakhi Ray 等S&P 2020 · 被引用 54 次
- Understanding and discovering software configuration dependencies in cloud and datacenter systemsQingrong Chen, Teng Wang, Owolabi Legunsen, Shanshan Li 等FSE 2020 · 被引用 54 次
- One Engine To Serve 'em All: Inferring Taint Rules Without Architectural SemanticsZheng Leong Chua, Yanhao Wang, Teodora Baluta, Prateek Saxena 等NDSS 2019 · 被引用 40 次
- Path-sensitive sparse analysis without path conditionsQingkai Shi, Peisen Yao, Rongxin Wu, Charles ZhangPLDI 2021 · 被引用 24 次
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