Open-Source Testing · antonio-morales

Fuzzing101

Fuzzing101 is a structured educational course teaching fuzzing techniques through 10 hands-on exercises targeting real software (Xpdf, libexif, TCPdump, LibTIFF, Libxml2, GIMP, VLC, Adobe Reader, 7-Zip, Chrome V8). Each exercise guides learners to discover known CVEs using AFL++ and related tools, progressing from basics to advanced techniques like QEMU instrumentation and JavaScript engine fuzzing.

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Source: GitHub — github.com/antonio-morales/Fuzzing101

3.8k

GitHub stars

421

Forks

Unknown

Primary language

Apache-2.0

License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

Field	Value
Repository	antonio-morales/Fuzzing101
Owner	antonio-morales
Primary language	Unknown
License	Apache-2.0 — OSI-approved
Stars	3.8k
Forks	421
Open issues	28
Latest release	Unknown
Last updated	2026-06-16
Source	https://github.com/antonio-morales/Fuzzing101

What Fuzzing101 is

A GitHub Security Lab course providing step-by-step tutorials on coverage-guided evolutionary fuzzing. Covers AFL-clang-fast/LTO compilation, sanitizers (ASan), code coverage measurement (LCOV), fuzzing harnesses, persistent fuzzing, partial instrumentation, WinAFL, and Fuzzilli. Exercises are structured by difficulty and topic, with estimated completion times and target CVEs for validation.

Quickstart

Get the Fuzzing101 source

Clone the repository and explore it locally.

terminalbash

1git clone https://github.com/antonio-morales/Fuzzing101.git2cd Fuzzing1013# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Security researcher onboarding

Ideal for new security engineers or bug hunters learning fuzzing fundamentals through real-world targets and documented CVE discoveries, reducing time-to-productivity in vulnerability research.

Hands-on vulnerability assessment training

Organizations can use this as internal training material to upskill teams on modern fuzzing methodologies, tool chains, and instrumentation techniques before conducting security assessments.

Academic security curriculum

Universities and bootcamps can incorporate the exercises as practical labs in software security courses, providing students with reproducible, real-target experience prior to industry work.

Implementation considerations

Exercises assume Ubuntu 20.04 LTS; other Linux distributions may require package/dependency adaptation. Verify AFL++, Clang/LLVM versions, and sanitizer support before starting.
Each exercise has increasing complexity and time commitment (120 mins to 8 hours). Plan sequentially; skipping earlier exercises risks missing prerequisite tool/concept mastery.
Requires local VM or machine with adequate CPU and disk (fuzzing is I/O and CPU-intensive); cloud sandbox or resource-limited environments may be slow or impractical.
Exercises target historical CVEs; patched software must be sourced or built at specific vulnerable versions. Ensure legal right to test before proceeding.
GDB, sanitizers, code coverage tools, and AFL++ need manual installation and configuration. Provide or document pre-configured environment to reduce setup friction.

When to avoid it — and what to weigh

Automated vulnerability scanning requirement — This is educational courseware, not an automated scanner or framework. It requires manual execution, interpretation, and iteration—unsuitable for continuous, hands-off security pipelines.
Windows-only development environment — Most exercises require Linux (tested on Ubuntu 20.04 LTS). Exercise 9 (WinAFL) targets Windows, but the course foundation demands Linux system access and proficiency.
Zero Linux command-line experience — README explicitly recommends 'at least basic Linux skills.' Learners without shell, GDB, and build-tool familiarity will face steep initial friction and incomplete exercise completion.
Off-the-shelf tool integration — Not a library or API—it is a course repository. Cannot be imported as a dependency or integrated into existing development workflows; consumption is manual and time-intensive.

License & commercial use

Licensed under Apache License 2.0 (Apache-2.0), a permissive OSI-approved license. Grants rights to use, modify, and distribute subject to license and copyright notice retention. No warranty provided.

Apache-2.0 permits commercial use, including within commercial security training, consulting, or internal employee development. However, using course materials as-is to build commercial fuzzing products or services requires legal review to ensure attribution and derivative work handling align with your business model. Requires review if packaged as commercial offering.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

Signal	Assessment
Maintenance	Moderate
Documentation	Adequate
License clarity	Clear
Deployment complexity	Moderate
DEV.co fit	Good
Assessment confidence	High

Security considerations

Exercises intentionally target vulnerable software to teach fuzzing. Users will encounter, compile, and execute real CVE-affected binaries—network isolation and sandboxing are prudent. No security audit or supply-chain guarantees are stated. Fuzzing itself can expose system stability issues; run on non-production machines. Sanitizers (ASan) help detect memory safety bugs but do not prevent all attack vectors. Users must understand the software tested and use results responsibly.

Alternatives to consider

LibFuzzer (LLVM project)

Coverage-guided fuzzer alternative to AFL++; integrated into LLVM toolchain. Focuses on library fuzzing and continuous integration. Steeper learning curve but no dedicated tutorial equivalent to Fuzzing101.

HonggFuzz (Google)

Another coverage-guided evolutionary fuzzer supporting feedback-driven mutation. Less widely adopted than AFL++; Fuzzing101 does not cover it but learners could transfer AFL++ concepts.

Commercial/SaaS fuzzing platforms (e.g., Fuzz Introspection, CI Fuzz)

Closed-source, managed fuzzing services with built-in reporting and integration. Suitable for enterprises wanting hands-off scanning; lack the educational, self-directed learning model of Fuzzing101.

Software development agency

Build on Fuzzing101 with DEV.co software developers

Start with Fuzzing101 exercises to build hands-on expertise in coverage-guided fuzzing, security tooling, and vulnerability discovery. Fork the repo, set up Ubuntu 20.04, and begin with Exercise 1.

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Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

FuzzingPaper AFLplusplus ps-fuzz

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Fuzzing101 FAQ

Do I need to complete all 10 exercises or can I skip some?

Exercises build on each other conceptually (e.g., Exercise 1 introduces AFL basics; later exercises assume that knowledge). Skipping early exercises risks missing prerequisites. Sequential completion is recommended, though proficient users may fast-track.

Can I run Fuzzing101 on macOS or Windows directly?

No; exercises are tested and designed for Ubuntu 20.04 LTS. macOS and Windows users should use a Linux VM, WSL2, or container. Exercise 9 (WinAFL) is Windows-focused but still requires a Linux host for course context.

What if I find a real vulnerability using these exercises?

Exercises use historical, patched CVEs for learning. If you discover a new vulnerability in any target, follow responsible disclosure practices: contact the vendor, document findings, and allow a reasonable patch window before public disclosure.

Are the CVEs in exercises still exploitable?

Exercises intentionally guide learners to rediscover known CVEs in outdated or unpatched software binaries. These are learning targets, not production software. Modern, patched versions of the targets are not vulnerable to the exercise CVEs.

Custom software development services

From first prototype to production, DEV.co delivers software development services around tools like Fuzzing101. Our software development agency staffs experienced software developers and web developers for custom software development, web development, integrations, and ongoing support across open-source testing and beyond.

Ready to master fuzzing and find real vulnerabilities?

Start with Fuzzing101 exercises to build hands-on expertise in coverage-guided fuzzing, security tooling, and vulnerability discovery. Fork the repo, set up Ubuntu 20.04, and begin with Exercise 1.

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