awesome-repositories.com
博客
awesome-repositories.com

通过 AI 驱动的搜索，发现最优秀的开源仓库。

探索精选搜索开源替代品自托管软件博客网站地图
项目关于排名机制媒体报道MCP 服务器
法律隐私政策服务条款
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·

4 个仓库

Awesome GitHub RepositoriesBinary Fuzzing

Executing compiled binaries with mutated inputs to trigger memory corruption and crashes.

Distinct from Binary Corpus Distillation: None of the candidates cover the act of fuzzing binaries; they cover standard input, corpus distillation, or remote execution.

Explore 4 awesome GitHub repositories matching security & cryptography · Binary Fuzzing. Refine with filters or upvote what's useful.

Awesome Binary Fuzzing GitHub Repositories

用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
  • aflplusplus/aflplusplusAFLplusplus 的头像

    AFLplusplus/AFLplusplus

    6,605在 GitHub 上查看↗

    AFL++ is a coverage-guided fuzzing framework that discovers crashes and hangs in software by mutating inputs while tracking which code paths are exercised. It functions as both a fuzzing engine and a campaign manager, supporting targets with or without source code through compile-time instrumentation, dynamic binary instrumentation, and emulation. The framework includes tools for crash triage and analysis, test case minimization, and campaign deployment across local or distributed environments. The framework distinguishes itself through its breadth of instrumentation backends, allowing users

    Applies dynamic binary instrumentation or emulation to fuzz programs without source code.

    C
    在 GitHub 上查看↗6,605
  • google/clusterfuzzgoogle 的头像

    google/clusterfuzz

    5,574在 GitHub 上查看↗

    ClusterFuzz is an automated platform that runs coverage-guided fuzzers at scale to find security and stability bugs in software. It orchestrates libFuzzer and AFL++ across distributed clusters of worker bots, collecting coverage feedback to guide input mutation and discover crashes. The platform provides a web-based dashboard for configuring fuzzing jobs, monitoring progress, and inspecting crash reports, with role-based access control to restrict sensitive features. The system automates the full fuzzing lifecycle, from build pipeline integration and corpus management to crash triage and bug

    Defines the execution parameters for fuzzing jobs, including binary names, arguments, and timeouts.

    Pythonfuzzingsecuritystability
    在 GitHub 上查看↗5,574
  • google/aflgoogle 的头像

    google/AFL

    4,064在 GitHub 上查看↗

    AFL is a coverage-guided fuzzer and security vulnerability scanner used to identify software bugs and memory corruption by feeding programs mutated data. It functions as a binary instrumentation tool and a test case minimizer to locate crashes and isolate the smallest set of bytes causing a fault. The project distinguishes itself through its ability to operate as a parallel fuzzing orchestrator, distributing workloads across multiple CPU cores or networked machines. It utilizes dictionary-based mutation for complex file formats and performs input sensitivity analysis to identify critical sect

    Provides the ability to execute target binaries with mutated inputs to trigger crashes and memory bugs.

    C
    在 GitHub 上查看↗4,064
  • google/fuzzinggoogle 的头像

    google/fuzzing

    3,772在 GitHub 上查看↗

    This project is a comprehensive software fuzzing knowledge base and technical guide designed for discovering software bugs and vulnerabilities. It serves as a resource for implementing coverage-guided, structure-aware, and hybrid fuzzing across various targets, including compiled binaries and hardware kernels. The resource provides specialized guidance on using grammars and defined data formats to generate syntactically valid inputs for complex APIs. It also details methods for combining grey-box fuzzing with symbolic execution to reach deep execution paths and utilizes binary instrumentation

    Provides technical guidance on performing coverage-guided fuzzing on compiled binaries without access to source code.

    C++
    在 GitHub 上查看↗3,772
  1. Home
  2. Security & Cryptography
  3. Binary Fuzzing

探索子标签

  • Binary-Only Fuzzing FrameworksApplies dynamic binary instrumentation or emulation to fuzz programs without source code. **Distinct from Binary Fuzzing:** Distinct from Binary Fuzzing: focuses on the framework aspect for binary-only targets, not just the act of fuzzing binaries.
  • Emulation-Based Fuzzings2 个子标签Runs coverage-guided fuzzing on compiled programs without source code using QEMU, Frida, or Unicorn emulation. **Distinct from Binary Fuzzing:** Distinct from Binary Fuzzing: focuses on emulation-based instrumentation for binary-only targets, not general binary fuzzing.
  • Grammar-Aware Input GenerationsGenerates inputs that follow a defined syntax to exercise structured parsers more effectively during fuzzing. **Distinct from Binary Fuzzing:** Distinct from Binary Fuzzing: adds syntax-aware input generation, not just random mutation of binary inputs.
  • Job Type DefinitionsSpecifies how to execute a target program during fuzzing by configuring environment variables like binary name, arguments, and timeouts. **Distinct from Binary Fuzzing:** Distinct from Binary Fuzzing: focuses on the configuration of job execution parameters rather than the act of fuzzing binaries themselves.
  • Sanitizer-Enhanced FuzzingsInstruments the target with memory or behavior sanitizers to catch deeper bugs like buffer overflows during fuzzing. **Distinct from Binary Fuzzing:** Distinct from Binary Fuzzing: adds sanitizer instrumentation to catch specific bug classes, not just general binary fuzzing.
  • Static Binary RewritingsRewrites x86-64 or arm64 binaries statically to insert instrumentation for near-compiler-level fuzzing performance. **Distinct from Binary Fuzzing:** Distinct from Binary Fuzzing: focuses on the rewriting technique to add instrumentation, not just executing binaries with mutated inputs.
  • Symbolic Execution FuzzingsCombines concrete fuzzing with symbolic reasoning to explore code paths that random mutation alone would miss. **Distinct from Binary Fuzzing:** Distinct from Binary Fuzzing: adds symbolic execution to guide path exploration, not just random mutation of binary inputs.
  • Unicorn Emulation FuzzingsEmulates arbitrary non-Linux binaries using Unicorn with custom runtime scripts for loading and execution during fuzzing. **Distinct from Binary Fuzzing:** Distinct from Binary Fuzzing: uses Unicorn emulation to fuzz non-Linux binaries, not just executing native binaries.