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Software in Fuzzing

10 tools
Pricing
Platform
ToolPricing
AFL++

Coverage-guided fuzzer with mutation engines, LLVM instrumentation plugins, and binary-only modes for finding memory safety bugs.

Free / Commercial
Atheris

Coverage-guided Python fuzzer from Google based on libFuzzer, designed for pure Python code and native CPython extensions.

Open Source
boofuzz

Python network protocol fuzzing framework for defining packet templates, tracking state machines, and discovering network crashes.

Open Source
FormatFuzzer

Generates file-format fuzzers and parsers from 010 Editor binary templates.

Open Source
Honggfuzz

Multi-threaded, feedback-driven fuzzer using software and hardware coverage counters to uncover memory corruption defects.

Open Source
Jazzer

Coverage-guided in-process fuzzer for Java and the JVM based on libFuzzer, with built-in sanitizers for injection, path traversal, and SSRF bugs.

Open Source
LibAFL

Rust fuzzing library from the AFL++ team for building custom fuzzers from reusable components.

Open Source
libFuzzer

In-process, coverage-guided evolutionary fuzzing engine from LLVM for testing C and C++ libraries with AddressSanitizer.

Open Source
Radamsa

General-purpose mutational fuzzer that generates malformed test samples to test parser resilience and file format handlers.

Open Source
syzkaller

Coverage-guided syscall fuzzer for Linux and other kernels, with declarative syscall descriptions.

Open Source

About Fuzzing

Fuzzing tools automatically test software by feeding it malformed, randomized, or edge-case inputs to discover crashes, memory leaks, and logic errors. The category divides into coverage-guided fuzzers and protocol fuzzers. Coverage-guided fuzzers like AFL++, libFuzzer, and honggfuzz track which code paths each input exercises, then mutate inputs that reach new code to maximize path coverage. They are effective at finding memory corruption bugs in parsers, decoders, and file format handlers. Protocol fuzzers like boofuzz target network protocols by sending malformed messages in a defined sequence, which exercises protocol state such as login steps. Fuzzing engines produce crash inputs that developers can reproduce and debug. When integrated into CI pipelines, fuzzing catches regressions in parsing code before releases. Modern fuzzing frameworks provide crash triage (grouping similar crashes), corpus management (storing inputs that maximize coverage), and sanitizers (detecting memory errors like buffer overflows and use-after-free during fuzzing runs). Most fuzzing tools are open source and integrate with compiler sanitizers like AddressSanitizer and UndefinedBehaviorSanitizer for deeper bug detection.

Covered Topics

Coverage-Guided FuzzingProtocol & API FuzzingMutation EnginesCrash Triage & Corpus ManagementCompiler Sanitizer Integration

In This Catalog

  • This category lists 10 tools: 9 open source and 1 free / commercial.
  • By platform, 10 run on Linux, 6 on Windows, and 9 on macOS.
  • The most common license among the open-source tools is Apache-2.0 (4 tools).

Frequently Asked Questions

What is Fuzzing?→

Fuzzing tools test software by generating malformed inputs to discover memory safety bugs, parser crashes, and logic flaws before code reaches production.

What topics does the Fuzzing category cover?→

Coverage-Guided Fuzzing, Protocol & API Fuzzing, Mutation Engines, Crash Triage & Corpus Management, Compiler Sanitizer Integration

Which Fuzzing tools are open source?→

9 of the 10 tools in this category are open source: Atheris, boofuzz, FormatFuzzer, Honggfuzz, Jazzer, LibAFL, libFuzzer, Radamsa, and syzkaller.

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