The Taint Rabbit: Optimizing Generic Taint Analysis with Dynamic Fast Path Generation

July 12, 2020 · Declared Dead · 🏛 ACM Asia Conference on Computer and Communications Security

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Authors John Galea, Daniel Kroening arXiv ID 2007.05955 Category cs.CR: Cryptography & Security Cross-listed cs.SE Citations 18 Venue ACM Asia Conference on Computer and Communications Security Last Checked 3 months ago
Abstract
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.
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