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

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