Proj THUDBFuzz Paper Reading: STOCHFUZZ: Sound and Cost-effective Fuzzing of Stripped Binaries by Incremental and Stochastic Rewriting

Github

https://github.com/ZhangZhuoSJTU/StochFuzz

Abstract

背景: 对stripped binaries进行fuzzing很困难，要么做出不切实际的假设，比如程序没有inlined data，要么使用硬件或者昂贵的动态二进制翻译引擎，比如QEMU。
本文: STOCHFUZZ
主要方法：生成不同版本的rewritten binaries, 这些二进制可以被fuzzing runs接受或者拒绝。本文证明这个过程最终将收敛在正确重写二进制上。

实验：两组真实程序
竞品：afl-gcc, afl-clang-fast, afl-qemu, ptfuzzer,e9patch, ddisarm
效果: sound, cost-effective

Proj THUDBFuzz Paper Reading: STOCHFUZZ: Sound and Cost-effective Fuzzing of Stripped Binaries by Incremental and Stochastic Rewriting

原文：https://www.cnblogs.com/xuesu/p/14682289.html