OSS-Fuzz provides free continuous fuzzing for open source projects. Use when setting up continuous fuzzing infrastructure or enrolling projects.
OSS-Fuzz is an open-source project developed by Google that provides free distributed infrastructure for continuous fuzz testing. It streamlines the fuzzing process and facilitates simpler modifications. While only select projects are accepted into OSS-Fuzz, the project's core is open-source, allowing anyone to host their own instance for private projects.
OSS-Fuzz provides a simple CLI framework for building and starting harnesses or calculating their coverage. Additionally, OSS-Fuzz can be used as a service that hosts static web pages generated from fuzzing outputs such as coverage information.
| Concept | Description |
|---|---|
| helper.py | CLI script for building images, building fuzzers, and running harnesses locally |
| Base Images | Hierarchical Docker images providing build dependencies and compilers |
| project.yaml | Configuration file defining project metadata for OSS-Fuzz enrollment |
| Dockerfile | Project-specific image with build dependencies |
| build.sh | Script that builds fuzzing harnesses for your project |
| Criticality Score | Metric used by OSS-Fuzz team to evaluate project acceptance |
Apply this technique when:
Skip this technique when:
| Task | Command |
|---|---|
| Clone OSS-Fuzz | git clone https://github.com/google/oss-fuzz |
| Build project image | python3 infra/helper.py build_image --pull <project> |
| Build fuzzers with ASan | python3 infra/helper.py build_fuzzers --sanitizer=address <project> |
| Run specific harness | python3 infra/helper.py run_fuzzer <project> <harness> |
| Generate coverage report | python3 infra/helper.py coverage <project> |
| Check helper.py options | python3 infra/helper.py --help |
OSS-Fuzz provides several publicly available tools and web interfaces:
The bug tracker allows you to:
The build status system helps track:
Fuzz Introspector displays:
Read this case study for examples and explanations.
You don't need to host the whole OSS-Fuzz platform to use it. The helper script makes it easy to run individual harnesses locally.
git clone https://github.com/google/oss-fuzz
cd oss-fuzz
python3 infra/helper.py --help
python3 infra/helper.py build_image --pull <project-name>
This downloads and builds the base Docker image for the project.
python3 infra/helper.py build_fuzzers --sanitizer=address <project-name>
Sanitizer options:
--sanitizer=address for AddressSanitizer with LeakSanitizerNote: Fuzzers are built to /build/out/<project-name>/ containing the harness executables, dictionaries, corpus, and crash files.
python3 infra/helper.py run_fuzzer <project-name> <harness-name> [<fuzzer-args>]
The helper script automatically runs any missed steps if you skip them.
First, install gsutil (skip gcloud initialization).
python3 infra/helper.py build_fuzzers --sanitizer=coverage <project-name>
python3 infra/helper.py coverage <project-name>
Use --no-corpus-download to use only local corpus. The command generates and hosts a coverage report locally.
See official OSS-Fuzz documentation for details.
Use Case: Testing OSS-Fuzz setup with a simple enrolled project
# Clone and navigate to OSS-Fuzz
git clone https://github.com/google/oss-fuzz
cd oss-fuzz
# Build and run irssi fuzzer
python3 infra/helper.py build_image --pull irssi
python3 infra/helper.py build_fuzzers --sanitizer=address irssi
python3 infra/helper.py run_fuzzer irssi irssi-fuzz
Expected Output:
INFO:__main__:Running: docker run --rm --privileged --shm-size=2g --platform linux/amd64 -i -e FUZZING_ENGINE=libfuzzer -e SANITIZER=address -e RUN_FUZZER_MODE=interactive -e HELPER=True -v /private/tmp/oss-fuzz/build/out/irssi:/out -t gcr.io/oss-fuzz-base/base-runner run_fuzzer irssi-fuzz.
Using seed corpus: irssi-fuzz_seed_corpus.zip
/out/irssi-fuzz -rss_limit_mb=2560 -timeout=25 /tmp/irssi-fuzz_corpus -max_len=2048 < /dev/null
INFO: Running with entropic power schedule (0xFF, 100).
INFO: Seed: 1531341664
INFO: Loaded 1 modules (95687 inline 8-bit counters): 95687 [0x1096c80, 0x10ae247),
INFO: Loaded 1 PC tables (95687 PCs): 95687 [0x10ae248,0x1223eb8),
INFO: 719 files found in /tmp/irssi-fuzz_corpus
INFO: seed corpus: files: 719 min: 1b max: 170106b total: 367969b rss: 48Mb
#720 INITED cov: 409 ft: 1738 corp: 640/163Kb exec/s: 0 rss: 62Mb
#762 REDUCE cov: 409 ft: 1738 corp: 640/163Kb lim: 2048 exec/s: 0 rss: 63Mb L: 236/2048 MS: 2 ShuffleBytes-EraseBytes-
Use Case: Adding your project to OSS-Fuzz (or private instance)
Create three files in projects/<your-project>/:
1. project.yaml - Project metadata:
homepage: "https://github.com/yourorg/yourproject"
language: c++
primary_contact: "your-email@example.com"
main_repo: "https://github.com/yourorg/yourproject"
fuzzing_engines:
- libfuzzer
sanitizers:
- address
- undefined
2. Dockerfile - Build dependencies:
FROM gcr.io/oss-fuzz-base/base-builder
RUN apt-get update && apt-get install -y \
autoconf \
automake \
libtool \
pkg-config
RUN git clone --depth 1 https://github.com/yourorg/yourproject
WORKDIR yourproject
COPY build.sh $SRC/
3. build.sh - Build harnesses:
#!/bin/bash -eu
./autogen.sh
./configure --disable-shared
make -j$(nproc)
# Build harnesses
$CXX $CXXFLAGS -std=c++11 -I. \
$SRC/yourproject/fuzz/harness.cc -o $OUT/harness \
$LIB_FUZZING_ENGINE ./libyourproject.a
# Copy corpus and dictionary if available
cp $SRC/yourproject/fuzz/corpus.zip $OUT/harness_seed_corpus.zip
cp $SRC/yourproject/fuzz/dictionary.dict $OUT/harness.dict
Harnesses are built and executed in Docker containers. All projects share a runner image, but each project has its own build image.
Images build on each other in this sequence:
base_imagebase_clangbase_builder_go, etc.base_builder or language variantbase_clangbase_runner| Tip | Why It Helps |
|---|---|
| Don't manually copy source code | Project Dockerfile likely already pulls latest version |
| Check existing projects | Browse oss-fuzz/projects for examples |
| Keep harnesses in separate repo | Like curl-fuzzer - cleaner organization |
| Use specific compiler versions | Base images provide consistent build environment |
| Install dependencies in Dockerfile | May require approval for OSS-Fuzz enrollment |
OSS-Fuzz uses a criticality score to evaluate project acceptance. See this example for how scoring works.
Projects with lower scores may still be added to private OSS-Fuzz instances.
Since OSS-Fuzz is open-source, you can host your own instance for:
| Anti-Pattern | Problem | Correct Approach |
|---|---|---|
| Manually pulling source in build.sh | Doesn't use latest version | Let Dockerfile handle git clone |
| Copying code to OSS-Fuzz repo | Hard to maintain, violates separation | Reference external harness repo |
| Ignoring base image versions | Build inconsistencies | Use provided base images and compilers |
| Skipping local testing | Wastes CI resources | Use helper.py locally before PR |
| Not checking build status | Unnoticed build failures | Monitor build status page regularly |
OSS-Fuzz primarily uses libFuzzer as the fuzzing engine for C/C++ projects.
Harness signature:
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
// Your fuzzing logic
return 0;
}
Build in build.sh:
$CXX $CXXFLAGS -std=c++11 -I. \
harness.cc -o $OUT/harness \
$LIB_FUZZING_ENGINE ./libproject.a
Integration tips:
$LIB_FUZZING_ENGINE variable provided by OSS-Fuzz-fsanitize=fuzzer is handled automaticallyOSS-Fuzz supports AFL++ as an alternative fuzzing engine.
Enable in project.yaml:
fuzzing_engines:
- afl
- libfuzzer
Integration tips:
For Python projects with C extensions.
Example from cbor2 integration:
Harness:
import atheris
import sys
import cbor2
@atheris.instrument_func
def TestOneInput(data):
fdp = atheris.FuzzedDataProvider(data)
try:
cbor2.loads(data)
except (cbor2.CBORDecodeError, ValueError):
pass
def main():
atheris.Setup(sys.argv, TestOneInput)
atheris.Fuzz()
if __name__ == "__main__":
main()
Build in build.sh:
pip3 install .
for fuzzer in $(find $SRC -name 'fuzz_*.py'); do
compile_python_fuzzer $fuzzer
done
Integration tips:
compile_python_fuzzer helper provided by OSS-FuzzEnable in project.yaml:
language: rust
fuzzing_engines:
- libfuzzer
sanitizers:
- address # Only AddressSanitizer supported for Rust
Build in build.sh:
cargo fuzz build -O --debug-assertions
cp fuzz/target/x86_64-unknown-linux-gnu/release/fuzz_target_1 $OUT/
Integration tips:
| Issue | Cause | Solution |
|---|---|---|
| Build fails with missing dependencies | Dependencies not in Dockerfile | Add apt-get install or equivalent in Dockerfile |
| Harness crashes immediately | Missing input validation | Add size checks in harness |
| Coverage is 0% | Harness not reaching target code | Verify harness actually calls target functions |
| Build timeout | Complex build process | Optimize build.sh, consider parallel builds |
| Sanitizer errors in build | Incompatible flags | Use flags provided by OSS-Fuzz environment variables |
| Cannot find source code | Wrong working directory in Dockerfile | Set WORKDIR or use absolute paths |
| Skill | How It Applies |
|---|---|
| libfuzzer | Primary fuzzing engine used by OSS-Fuzz |
| aflpp | Alternative fuzzing engine supported by OSS-Fuzz |
| atheris | Used for fuzzing Python projects in OSS-Fuzz |
| cargo-fuzz | Used for Rust projects in OSS-Fuzz |
| Skill | Relationship |
|---|---|
| coverage-analysis | OSS-Fuzz generates coverage reports via helper.py |
| address-sanitizer | Default sanitizer for OSS-Fuzz projects |
| fuzz-harness-writing | Essential for enrolling projects in OSS-Fuzz |
| corpus-management | OSS-Fuzz maintains corpus for enrolled projects |
OSS-Fuzz Official Documentation Comprehensive documentation covering enrollment, harness writing, and troubleshooting for the OSS-Fuzz platform.
Getting Started Guide Step-by-step process for enrolling new projects into OSS-Fuzz, including requirements and approval process.
cbor2 OSS-Fuzz Integration PR Real-world example of enrolling a Python project with C extensions into OSS-Fuzz. Shows:
Fuzz Introspector Case Studies Examples and explanations of using Fuzz Introspector to analyze coverage and identify fuzzing blockers.
Check OSS-Fuzz documentation for workshop recordings and tutorials on enrollment and harness development.
