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License: Apache License 2.0
The repository of blog's comments.
License: Apache License 2.0
https://bladchan.github.io/2022/06/24/GraphFuzz%E4%BD%BF%E7%94%A8%E8%AF%B4%E6%98%8E/
GraphFuzz使用说明1. 概述 GraphFuzz是一个用于构建结构感知、库API模糊器的实验性框架 论文: 《GraphFuzz: Library API Fuzzing with Lifetime-aware Dataflow Graphs》 GraphFuzz包含: gfuzz:命令行工具用来合成harness libgraphfuzz:一个运行时图变异引擎 文档:hgarr
AFL插桩剖析I. 前置知识 编译器产生可执行文件的流程如下图1、2所示(以gcc编译器为例,clang同理): 图1 gcc编译器工作流程(顶层架构) 图2 clang编译器工作流程(顶层架构) 主流的编译器【图1中第二个阶段】包括三个组件:前端、中间端和后端 [1] 前端:读取源文件并对其进行分析,通常是将源码转化为标准抽象语法树(AST) 中间端:进行源码优化,通常是使用生成的某
AFL++自定义变异器 支持C/C++库和Python模式 C/C++ library (*.so) Python module 1. 简介相关注意事项: custom_mutator_stage在确定性变异之后启用; 在使用C/C++接口时,需要引入一个动态链接库(动态库路径存放在环境变量AFL_CUSTOM_MUTATOR_LIBRARY中),该库(部分)定义AFL++暴露出来的接口
https://bladchan.github.io/2022/07/25/GraphFuzz%E6%BA%90%E7%A0%81%E8%A7%A3%E6%9E%90/
GraphFuzz源码解析 核心代码位于core目录下 graph.hpp为图结构体头文件,主要包含一个结构体NodeLink和一个类TGraph schema.hpp声明了一个类Schema,同时包含ScopeDef、Signature,hash,ScopeTree和TypeTree这五个结构体 harness.cpp为生成的harness文件,该文件调用libfuzzer的接口来实现相关功能
https://bladchan.github.io/2022/07/06/AFLplusplus%E6%BA%90%E7%A0%81%E6%B5%85%E6%9E%90/
AFL++源码解析afl-fuzz.cmain函数 rand_set_seed()设置四个种子:afl->init_seed, afl->rand_seed[0-2] while循环对选项进行判断,支持的选项有:"+Ab:B:c:CdDe:E:hi:I:f:F:g:G:l:L:m:M:nNOo:p:RQs:S:t:T:UV:WXx:YZ": 选项 描述 -i dir 测试
https://bladchan.github.io/2023/04/20/AFLplusplus-cmplog%E6%8F%92%E6%A1%A9%E8%A7%A3%E6%9E%90/
AFL++’s Cmplog插桩1. 源码解析afl-cc.c 代码片段: 123456789101112131415161718192021222324252627 if (cmplog_mode) { cc_params[cc_par_cnt++] = "-fno-inline";#if LLVM_MAJOR >= 11
https://bladchan.github.io/2022/09/27/Boofuzz%E6%BA%90%E7%A0%81%E8%A7%A3%E6%9E%90/
boofuzz源码分析以ftp_simple.py为例: 12345session = Session(target=Target(connection=TCPSocketConnection("127.0.0.1", 21))) # 创建sessiondefine_proto(session=session) # 定义protosession.fuzz() # 开始模糊测试 其中,defi
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