Generic taint analysis is a pivotal technique in software security. However, it suffers from staggeringly high overhead. In this paper, we explore the hypothesis whether just-in-time (JIT) generation of fast paths for tracking taint can enhance the performance. To this end, we present the Taint Rabbit, which supports highly customizable user-defined taint policies and combines a JIT with fast context switching. Our experimental results suggest that this combination outperforms notable existing implementations of generic taint analysis and bridges the performance gap to specialized trackers. For instance, Dytan incurs an average overhead of 237x, while the Taint Rabbit achieves 1.7x on the same set of benchmarks. This compares favorably to the 1.5x overhead delivered by the bitwise, non-generic, taint engine LibDFT.

中文翻译：

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污点兔子：使用动态快速路径生成优化通用污点分析

通用污点分析是软件安全中的关键技术。然而，它的开销高得惊人。在本文中，我们探讨了用于跟踪污点的快速路径的即时 (JIT) 生成是否可以提高性能的假设。为此，我们提出了 Taint Rabbit，它支持高度可定制的用户定义污点策略，并将 JIT 与快速上下文切换相结合。我们的实验结果表明，这种组合优于现有的通用污点分析的显着实现，并弥合了与专用跟踪器的性能差距。例如，Dytan 的平均开销为 237 倍，而 Taint Rabbit 在同一组基准测试中实现了 1.7 倍。与按位、非通用、污点引擎 LibDFT 提供的 1.5 倍开销相比，这更有利。