ossfuzz
OSS-Fuzz automates vulnerability discovery by managing fuzzing harnesses, configuration files, and base images for open-source projects.
Install
mkdir -p .claude/skills/ossfuzz && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4188" && unzip -o skill.zip -d .claude/skills/ossfuzz && rm skill.zipInstalls to .claude/skills/ossfuzz
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
OSS-Fuzz provides free continuous fuzzing for open source projects. Use when setting up continuous fuzzing infrastructure or enrolling projects.Key capabilities
- →Manages fuzzing harness build infrastructure
- →Calculates project coverage metrics
- →Configures project.yaml for OSS-Fuzz enrollment
- →Supports harness testing via helper.py
How it works
Orchestrates Docker-based build processes to compile and execute test harnesses that find vulnerabilities through continuous fuzzing.
Inputs & outputs
When to use ossfuzz
- →Setting up continuous fuzzing for a project
- →Running a harness locally for testing
- →Reproducing bugs from OSS-Fuzz reports
About this skill
OSS-Fuzz
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.
Overview
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.
Key Concepts
| 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 |
When to Apply
Apply this technique when:
- Setting up continuous fuzzing for an open-source project
- Need distributed fuzzing infrastructure without managing servers
- Want coverage reports and bug tracking integrated with fuzzing
- Testing existing OSS-Fuzz harnesses locally
- Reproducing crashes from OSS-Fuzz bug reports
Skip this technique when:
- Project is closed-source (unless hosting your own OSS-Fuzz instance)
- Project doesn't meet OSS-Fuzz's criticality score threshold
- Need proprietary or specialized fuzzing infrastructure
- Fuzzing simple scripts that don't warrant infrastructure
Quick Reference
| 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 Project Components
OSS-Fuzz provides several publicly available tools and web interfaces:
Bug Tracker
The bug tracker allows you to:
- Check bugs from specific projects (initially visible only to maintainers, later made public)
- Create new issues and comment on existing ones
- Search for similar bugs across all projects to understand issues
Build Status System
The build status system helps track:
- Build statuses of all included projects
- Date of last successful build
- Build failures and their duration
Fuzz Introspector
Fuzz Introspector displays:
- Coverage data for projects enrolled in OSS-Fuzz
- Hit frequency for covered code
- Performance analysis and blocker identification
Read this case study for examples and explanations.
Step-by-Step: Running a Single Harness
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.
Step 1: Clone OSS-Fuzz
git clone https://github.com/google/oss-fuzz
cd oss-fuzz
python3 infra/helper.py --help
Step 2: Build Project Image
python3 infra/helper.py build_image --pull <project-name>
This downloads and builds the base Docker image for the project.
Step 3: Build Fuzzers with Sanitizers
python3 infra/helper.py build_fuzzers --sanitizer=address <project-name>
Sanitizer options:
--sanitizer=addressfor AddressSanitizer with LeakSanitizer- Other sanitizers available (language support varies)
Note: Fuzzers are built to /build/out/<project-name>/ containing the harness executables, dictionaries, corpus, and crash files.
Step 4: Run the Fuzzer
python3 infra/helper.py run_fuzzer <project-name> <harness-name> [<fuzzer-args>]
The helper script automatically runs any missed steps if you skip them.
Step 5: Coverage Analysis (Optional)
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.
Common Patterns
Pattern: Running irssi Example
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-
Pattern: Enrolling a New Project
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: "[email protected]"
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
Docker Images in OSS-Fuzz
Harnesses are built and executed in Docker containers. All projects share a runner image, but each project has its own build image.
Image Hierarchy
Images build on each other in this sequence:
- base_image - Specific Ubuntu version
- base_clang - Clang compiler; based on
base_image - base_builder - Build dependencies; based on
base_clang- Language-specific variants:
base_builder_go, etc. - See /oss-fuzz/infra/base-images/ for full list
- Language-specific variants:
- Your project Docker image - Project-specific dependencies; based on
base_builderor language variant
Runner Images (Used Separately)
- base_runner - Executes harnesses; based on
base_clang - base_runner_debug - With debug tools; based on
base_runner
Advanced Usage
Tips and Tricks
| 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 |
Criticality Score
OSS-Fuzz uses a criticality score to evaluate project acceptance. See [this example](https://github
Content truncated.
When not to use it
- →Proprietary, closed-source software
- →Projects failing criticality thresholds
Prerequisites
Limitations
- →Limited by Docker build dependencies
- →Performance requires host resources
How it compares
Provides a standardized infrastructure framework rather than just generating test cases.
Compared to similar skills
ossfuzz side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| ossfuzz (this skill) | 1 | 2mo | Review | Advanced |
| secrets-management | 5 | 3mo | Review | Advanced |
| mcp-activation | 3 | 6mo | Review | Intermediate |
| container-security-testing | 1 | 6mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
More by trailofbits
View all by trailofbits →You might also like
secrets-management
wshobson
Implement secure secrets management for CI/CD pipelines using Vault, AWS Secrets Manager, or native platform solutions. Use when handling sensitive credentials, rotating secrets, or securing CI/CD environments.
mcp-activation
netalertx
Enables live interaction with the NetAlertX runtime. This skill configures the Model Context Protocol (MCP) connection, granting full API access for debugging, troubleshooting, and real-time operations including database queries, network scans, and device management.
container-security-testing
Ed1s0nZ
容器安全测试的专业技能和方法论
fix-cves
okteto
Fix all CVEs in the Okteto CLI Docker image by scanning with Trivy and updating vulnerable dependencies and binaries
sca-trivy
rohunj
Software Composition Analysis (SCA) and container vulnerability scanning using Aqua Trivy for identifying CVE vulnerabilities in dependencies, container images, IaC misconfigurations, and license compliance risks. Use when: (1) Scanning container images and filesystems for vulnerabilities and misconfigurations, (2) Analyzing dependencies for known CVEs across multiple languages (Go, Python, Node.js, Java, etc.), (3) Detecting IaC security issues in Terraform, Kubernetes, Dockerfile, (4) Integrating vulnerability scanning into CI/CD pipelines with SARIF output, (5) Generating Software Bill of Materials (SBOM) in CycloneDX or SPDX format, (6) Prioritizing remediation by CVSS score and exploitability.
security-automation
Ed1s0nZ
安全自动化的专业技能和方法论