TaintPipe: Pipelined Symbolic Taint Analysis

@inproceedings{Ming2015TaintPipePS,
  title={TaintPipe: Pipelined Symbolic Taint Analysis},
  author={Jiang Ming and Dinghao Wu and Gaoyao Xiao and Jun Wang and Peng Liu},
  booktitle={USENIX Security Symposium},
  year={2015}
}
Taint analysis has a wide variety of compelling applications in security tasks, from software attack detection to data lifetime analysis. Static taint analysis propagates taint values following all possible paths with no need for concrete execution, but is generally less accurate than dynamic analysis. Unfortunately, the high performance penalty incurred by dynamic taint analyses makes its deployment impractical in production systems. To ameliorate this performance bottleneck, recent research… CONTINUE READING
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