FuzzAgent

Multi-Agent System for Evolutionary Library Fuzzing
From C/C++ source code to evolving fuzzing campaigns.

Paper · Quick Start · Results · Benchmarks · Citation

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FuzzAgent is an autonomous multi-agent system for fuzzing C/C++ libraries. Starting from source code, specialized agents collaborate to prepare builds, generate harnesses and inputs, run fuzzers, and analyze coverage and crashes. This repository provides the research prototype and launchers for the 20 libraries evaluated in the paper.

• End-to-end automation: Coordinate library building, dictionary and seed acquisition, harness generation, fuzzing, and analysis.
• Dependency-aware harness generation: Construct API sequences around initialization, state dependencies, and object lifetimes.
• Coverage-guided evolution: Use execution feedback to refine harnesses and explore additional program paths.

Results

The paper's Table 1 reports per-library statistics, branch coverage, LLM cost, and detected bugs across all 20 targets. The screenshot below preserves the full table; click it to open the original-size image.

FuzzAgent covers 184,840 branches and reports 102 detected bugs. By reported total branch coverage, this is 49.3% more than OSS-Fuzz, 199.7% more than OSS-Fuzz-Gen, 78.3% more than PromptFuzz, and 97.7% more than PromeFuzz; the systems cover different target sets. Its end-to-end variant covers 179,619 branches using 24 hours of execution without an additional 24-hour standalone fuzzing phase. The other coverage results follow the paper's 24-hour execution plus 24-hour standalone fuzzing protocol. The paper explains the unsupported entries and per-system evaluation details in the table notes.

Quick Start

Tested on Ubuntu 24.04 LTS, using Docker and an OpenAI-compatible LLM endpoint. Run the following commands from the repository root.

1. Build the Docker image

Install Docker Engine and the Docker Compose plugin using the official guide, then build the image:

docker buildx build -t fuzzagent -f docker/Dockerfile .

2. Configure your LLM

cp .env_template .env

Edit .env with your endpoint, API key, and model:

OPENAI_BASE_URL=https://api.example.com/v1
OPENAI_API_KEY=your-api-key
OPENAI_MODEL=your-model

A GitHub token is optional. Create one at github.com/settings/tokens and set GITHUB_TOKEN in .env to enable GitHub search.

3. Launch a benchmark

./benchmark/run.sh cjson

The launcher prepares the source checkout and starts fuzzagent-cjson in the background. The default campaign runs for 24 hours, then exports full code coverage. Source and output paths are configured automatically.

Benchmarks

Choose a library below and use its Target ID with ./benchmark/run.sh <target>. Library names link to their source repositories.

The launcher caches checkouts in .cache/targets/<target> and saves results in output/<target>. It currently clones each repository's default branch; the paper's evaluation uses the specific revisions listed in Table I.

Library	Focus	Target ID
c-ares	Asynchronous DNS resolution	c-ares
cJSON	JSON parsing and serialization	cjson
curl	Data transfer and network protocols	curl
libaom	AV1 video encoding and decoding	libaom
libjpeg-turbo	JPEG encoding and decoding	libjpeg-turbo
liblouis	Braille translation	liblouis
libmagic	File type identification	libmagic
libpcap	Network packet capture	libpcap
libpng	PNG encoding and decoding	libpng
libtiff	TIFF image processing	libtiff
libvpx	VP8 and VP9 video encoding and decoding	libvpx
Little CMS	Color management	lcms
OpenCV	Computer vision and image processing	opencv
OpenSSL	Cryptography and TLS	openssl
Protocol Buffers	Structured data serialization	protobuf
pugixml	XML parsing and processing	pugixml
RE2	Regular expression matching	re2
SQLite	Embedded SQL database	sqlite
TinyGLTF	glTF model loading and serialization	tinygltf
zlib	Data compression	zlib

License

FuzzAgent is dual-licensed under AGPL-3.0-only or a separate commercial license obtained from the copyright holders. You can choose either option:

1. Open-source license (AGPL-3.0-only). Use, modify, and share HarnessMinimizer under the AGPL's terms. If you distribute covered binaries, provide the corresponding source as required by the license. If you run a modified version as a network service, offer its corresponding source to users who interact with it remotely. Full terms: LICENSE.

2. Commercial license. If you cannot or do not want to meet the AGPL requirements for your intended use, obtain a separately negotiated commercial license before proceeding. Contact fuzzanything@gmail.com. This repository does not grant a commercial license.

Citation

If you use FuzzAgent in your research, please cite our paper:

@misc{lyu2026fuzzagentmultiagentevolutionarylibrary,
      title={FuzzAgent: Multi-Agent System for Evolutionary Library Fuzzing},
      author={Yunlong Lyu and Peng Chen and Fengyi Wu and Junzhe Yu and Kit Long Hon and Hao Chen},
      year={2026},
      eprint={2605.14431},
      archivePrefix={arXiv},
      primaryClass={cs.SE},
      url={https://arxiv.org/abs/2605.14431},
}

Evaluation Artifacts

The evaluation artifacts in our paper: https://github.com/FuzzAnything/FuzzAgent-Artifacts