Atheris

Trail of BitsOfficialPublished by Trail of Bits

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Tool integration
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CC-BY-SA-4.0
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From the author

Sets up and runs Atheris, the coverage-guided Python fuzzer built on libFuzzer. Covers TestOneInput harnesses, FuzzedDataProvider, instrumenting both pure Python and native C extensions, and running under AddressSanitizer. Use when fuzzing a Python package, hunting memory corruption in a Python C extension, or choosing between Atheris and Hypothesis for a Python target.

— the description by Trail of Bits

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Atheris is a coverage-guided fuzzer designed for the Python ecosystem. It enables developers to test both pure Python code and native C extensions by integrating with libFuzzer. The tool supports AddressSanitizer (ASan) to detect memory corruption issues, particularly within C extensions, and provides mechanisms for instrumenting code, managing seed corpora, and structuring input data for more effective fuzzing campaigns.

What it does

Provides coverage-guided fuzzing for pure Python and C extensions
Integrates with AddressSanitizer to identify memory corruption
Supports structured input generation via FuzzedDataProvider
Offers multiple instrumentation modes including function-level and module-level
Includes tools for corpus management and minimization
Facilitates integration with CI/CD pipelines

When to use it

When you need to fuzz pure Python code with coverage guidance
When testing Python C extensions for memory safety issues
When you require integration with the libFuzzer ecosystem
When you need to detect memory corruption using AddressSanitizer

Advantages

Native support for both Python and C extension instrumentation
Coverage-guided approach improves test effectiveness
Flexible instrumentation options for different project needs
Compatible with standard sanitizer tools for deep bug detection

Usage examples

“How do I set up a basic Atheris harness for a Python function?”: The agent provides a template using @atheris.instrument_func and atheris.Setup to define the entry point for the fuzzer.
“How can I fuzz a Python C extension with Atheris?”: The agent explains how to compile the extension with specific clang flags and configure LD_PRELOAD for sanitizer support.
“What is the best way to handle structured inputs in my fuzzer?”: The agent demonstrates using atheris.FuzzedDataProvider to split byte inputs into typed values like integers, booleans, or strings.
“How do I manage my initial seed corpus?”: The agent shows how to create a directory of seed files and pass that directory as an argument when running the fuzzer.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/trailofbits/atheris/download
Unzip it into the cross-client skills folder of your project:
```
mkdir -p .agents/skills && unzip atheris.zip -d .agents/skills
```

Documentation by Trail of Bits

Atheris

Atheris is a coverage-guided Python fuzzer built on libFuzzer. It enables fuzzing of both pure Python code and Python C extensions with integrated AddressSanitizer support for detecting memory corruption issues.

When to Use

Fuzzer	Best For	Complexity
Atheris	Python code and C extensions	Low-Medium
Hypothesis	Property-based testing	Low
python-afl	AFL-style fuzzing	Medium

Choose Atheris when:

Fuzzing pure Python code with coverage guidance
Testing Python C extensions for memory corruption
Integration with libFuzzer ecosystem is desired
AddressSanitizer support is needed

Quick Start

import sys
import atheris

@atheris.instrument_func
def TestOneInput(data: bytes):
    if len(data) == 4:
        if data[0] == 0x46:  # "F"
            if data[1] == 0x55:  # "U"
                if data[2] == 0x5A:  # "Z"
                    if data[3] == 0x5A:  # "Z"
                        raise RuntimeError("You caught me")

def main():
    atheris.Setup(sys.argv, TestOneInput)
    atheris.Fuzz()

if __name__ == "__main__":
    main()

Run:

uv run python fuzz.py

Installation

Atheris supports 32-bit and 64-bit Linux, and macOS. We recommend fuzzing on Linux because it's simpler to manage and often faster.

Prerequisites

Python 3.7 or later
Recent version of clang (preferably latest release)
For Docker users: Docker Desktop

Linux/macOS

uv init --bare   # once, if the harness directory is not yet a uv project
uv add atheris

Docker Environment (Recommended)

For a fully operational Linux environment with all dependencies configured:

# https://hub.docker.com/_/python
ARG PYTHON_VERSION=3.11

FROM python:$PYTHON_VERSION-slim-bookworm

RUN python --version

RUN apt update && apt install -y \
    ca-certificates \
    wget \
    && rm -rf /var/lib/apt/lists/*

# LLVM builds version 15-19 for Debian 12 (Bookworm)
# https://apt.llvm.org/bookworm/dists/
ARG LLVM_VERSION=19

RUN echo "deb http://apt.llvm.org/bookworm/ llvm-toolchain-bookworm-$LLVM_VERSION main" > /etc/apt/sources.list.d/llvm.list
RUN echo "deb-src http://apt.llvm.org/bookworm/ llvm-toolchain-bookworm-$LLVM_VERSION main" >> /etc/apt/sources.list.d/llvm.list
RUN wget -qO- https://apt.llvm.org/llvm-snapshot.gpg.key > /etc/apt/trusted.gpg.d/apt.llvm.org.asc

RUN apt update && apt install -y \
    build-essential \
    clang-$LLVM_VERSION \
    && rm -rf /var/lib/apt/lists/*

ENV APP_DIR "/app"
RUN mkdir $APP_DIR
WORKDIR $APP_DIR

ENV VIRTUAL_ENV "/opt/venv"
RUN python -m venv $VIRTUAL_ENV
ENV PATH "$VIRTUAL_ENV/bin:$PATH"

# https://github.com/google/atheris/blob/master/native_extension_fuzzing.md#step-1-compiling-your-extension
ENV CC="clang-$LLVM_VERSION"
ENV CFLAGS "-fsanitize=address,fuzzer-no-link"
ENV CXX="clang++-$LLVM_VERSION"
ENV CXXFLAGS "-fsanitize=address,fuzzer-no-link"
ENV LDSHARED="clang-$LLVM_VERSION -shared"
ENV LDSHAREDXX="clang++-$LLVM_VERSION -shared"
ENV ASAN_SYMBOLIZER_PATH="/usr/bin/llvm-symbolizer-$LLVM_VERSION"

# Allow Atheris to find fuzzer sanitizer shared libs
# https://github.com/google/atheris#building-from-source
RUN LIBFUZZER_LIB=$($CC -print-file-name=libclang_rt.fuzzer_no_main-$(uname -m).a) \
    python -m pip install --no-binary atheris atheris

# https://github.com/google/atheris/blob/master/native_extension_fuzzing.md#option-a-sanitizerlibfuzzer-preloads
ENV LD_PRELOAD "$VIRTUAL_ENV/lib/python3.11/site-packages/asan_with_fuzzer.so"

# 1. Skip memory allocation failures for now, they are common, and low impact (DoS)
# 2. https://github.com/google/atheris/blob/master/native_extension_fuzzing.md#leak-detection
ENV ASAN_OPTIONS "allocator_may_return_null=1,detect_leaks=0"

CMD ["/bin/bash"]

Build and run:

docker build -t atheris .
docker run -it atheris

Verification

python -c "import atheris; print(atheris.__version__)"

Writing a Harness

Harness Structure for Pure Python

import sys
import atheris

@atheris.instrument_func
def TestOneInput(data: bytes):
    """
    Fuzzing entry point. Called with random byte sequences.

    Args:
        data: Random bytes generated by the fuzzer
    """
    # Add input validation if needed
    if len(data) < 1:
        return

    # Call your target function
    try:
        your_target_function(data)
    except ValueError:
        # Expected exceptions should be caught
        pass
    # Let unexpected exceptions crash (that's what we're looking for!)

def main():
    atheris.Setup(sys.argv, TestOneInput)
    atheris.Fuzz()

if __name__ == "__main__":
    main()

Structured Input with FuzzedDataProvider

A target taking several typed arguments wastes most of the fuzzer's inputs if the harness slices data by hand, because every mutation shifts the byte offsets of everything after it. atheris.FuzzedDataProvider splits one bytes input into typed values instead:

fdp = atheris.FuzzedDataProvider(data)
name = fdp.ConsumeUnicodeNoSurrogates(fdp.ConsumeIntInRange(0, 64))
strict = fdp.ConsumeBool()

See structured-input.md for the full method reference, the fixed-draw- order rule, and what each method returns once the buffer runs dry.

Harness Rules

Do	Don't
Use `@atheris.instrument_func` for coverage	Forget to instrument target code
Catch expected exceptions	Catch all exceptions indiscriminately
Use `atheris.instrument_imports()` for libraries	Import modules after `atheris.Setup()`
Keep harness deterministic	Use randomness or time-based behavior

See Also: For detailed harness writing techniques, patterns for handling complex inputs, and advanced strategies, see the fuzz-harness-writing technique skill.

Fuzzing Pure Python Code

For fuzzing broader parts of an application or library, use instrumentation functions:

import atheris
with atheris.instrument_imports():
    import your_module
    from another_module import target_function

def TestOneInput(data: bytes):
    target_function(data)

atheris.Setup(sys.argv, TestOneInput)
atheris.Fuzz()

Instrumentation Options:

atheris.instrument_func - Decorator for single function instrumentation
atheris.instrument_imports() - Context manager for instrumenting all imported modules
atheris.instrument_all() - Instrument all Python code system-wide

Fuzzing Python C Extensions

Python C extensions require compilation with specific flags for instrumentation and sanitizer support.

Environment Configuration

If using the provided Dockerfile, these are already configured. For local setup:

export CC="clang"
export CFLAGS="-fsanitize=address,fuzzer-no-link"
export CXX="clang++"
export CXXFLAGS="-fsanitize=address,fuzzer-no-link"
export LDSHARED="clang -shared"

Example: Fuzzing cbor2

Install the extension from source:

CBOR2_BUILD_C_EXTENSION=1 uv add --no-binary-package cbor2 'cbor2==5.6.4'

The --no-binary-package flag ensures the C extension is compiled locally with instrumentation rather than pulled as a prebuilt wheel. Persist that choice with no-binary-package = ["cbor2"] under [tool.uv] in pyproject.toml, or a later uv sync can silently swap in an uninstrumented wheel.

Create cbor2-fuzz.py:

import sys
import atheris

# _cbor2 ensures the C library is imported
from _cbor2 import loads

def TestOneInput(data: bytes):
    try:
        loads(data)
    except Exception:
        # We're searching for memory corruption, not Python exceptions
        pass

def main():
    atheris.Setup(sys.argv, TestOneInput)
    atheris.Fuzz()

if __name__ == "__main__":
    main()

Run:

uv run python cbor2-fuzz.py

Important: When running locally (not in Docker), you must set LD_PRELOAD manually.

Corpus Management

Creating Initial Corpus

mkdir corpus
# Add seed inputs
echo "test data" > corpus/seed1
echo '{"key": "value"}' > corpus/seed2

Run with corpus:

uv run python fuzz.py corpus/

Corpus Minimization

Atheris inherits corpus minimization from libFuzzer:

uv run python fuzz.py -merge=1 new_corpus/ old_corpus/

See Also: For corpus creation strategies, dictionaries, and seed selection, see the fuzzing-corpus technique skill.

Running Campaigns

Basic Run

uv run python fuzz.py

With Corpus Directory

uv run python fuzz.py corpus/

Common Options

# Run for 10 minutes
uv run python fuzz.py -max_total_time=600

# Limit input size
uv run python fuzz.py -max_len=1024

# Run with multiple workers
uv run python fuzz.py -workers=4 -jobs=4

Interpreting Output

Output	Meaning
`NEW cov: X`	Found new coverage, corpus expanded
`pulse cov: X`	Periodic status update
`exec/s: X`	Executions per second (throughput)
`corp: X/Yb`	Corpus size: X inputs, Y bytes total
`ERROR: libFuzzer`	Crash detected

Sanitizer Integration

AddressSanitizer (ASan)

AddressSanitizer is automatically integrated when using the provided Docker environment or when compiling with appropriate flags.

For local setup:

export CFLAGS="-fsanitize=address,fuzzer-no-link"
export CXXFLAGS="-fsanitize=address,fuzzer-no-link"

Configure ASan behavior:

export ASAN_OPTIONS="allocator_may_return_null=1,detect_leaks=0"

LD_PRELOAD Configuration

For native extension fuzzing:

export LD_PRELOAD="$(python -c 'import atheris; import os; print(os.path.join(os.path.dirname(atheris.__file__), "asan_with_fuzzer.so"))')"

See Also: For detailed sanitizer configuration, common issues, and advanced flags, see the address-sanitizer and undefined-behavior-sanitizer technique skills.

Common Sanitizer Issues

Issue	Solution
`LD_PRELOAD` not set	Export `LD_PRELOAD` to point to `asan_with_fuzzer.so`
Memory allocation failures	Set `ASAN_OPTIONS=allocator_may_return_null=1`
Leak detection noise	Set `ASAN_OPTIONS=detect_leaks=0`
Missing symbolizer	Set `ASAN_SYMBOLIZER_PATH` to `llvm-symbolizer`

Advanced Usage

Tips and Tricks

Tip	Why It Helps
Use `atheris.instrument_imports()` early	Ensures all imports are instrumented for coverage
Start with small `max_len`	Faster initial fuzzing, gradually increase
Use dictionaries for structured formats	Helps fuzzer understand format tokens
Run multiple parallel instances	Better coverage exploration

Custom Instrumentation

Fine-tune what gets instrumented:

import atheris

# Instrument only specific modules
with atheris.instrument_imports():
    import target_module
# Don't instrument test harness code

def TestOneInput(data: bytes):
    target_module.parse(data)

Performance Tuning

Setting	Impact
`-max_len=N`	Smaller values = faster execution
`-workers=N -jobs=N`	Parallel fuzzing for faster coverage
`ASAN_OPTIONS=fast_unwind_on_malloc=0`	Better stack traces, slower execution

UndefinedBehaviorSanitizer (UBSan)

Add UBSan to catch additional bugs:

export CFLAGS="-fsanitize=address,undefined,fuzzer-no-link"
export CXXFLAGS="-fsanitize=address,undefined,fuzzer-no-link"

Note: Modify flags in Dockerfile if using containerized setup.

Real-World Examples

Two complete harnesses — a pure-Python parser and an HTTP response parser — are in examples.md.

Troubleshooting

Problem	Cause	Solution
No coverage increase	Poor seed corpus or target not instrumented	Add better seeds, verify `instrument_imports()`
Slow execution	ASan overhead or large inputs	Reduce `max_len`, use `ASAN_OPTIONS=fast_unwind_on_malloc=1`
Import errors	Modules imported before instrumentation	Move imports inside `instrument_imports()` context
Segfault without ASan output	Missing `LD_PRELOAD`	Set `LD_PRELOAD` to `asan_with_fuzzer.so` path
Build failures	Wrong compiler or missing flags	Verify `CC`, `CFLAGS`, and clang version

Technique Skills

Skill	Use Case
fuzz-harness-writing	Detailed guidance on writing effective harnesses
address-sanitizer	Memory error detection during fuzzing
undefined-behavior-sanitizer	Catching undefined behavior in C extensions
coverage-analysis	Measuring and improving code coverage
fuzzing-corpus	Building and managing seed corpora

Skill	When to Consider
hypothesis	Property-based testing with type-aware generation
python-afl	AFL-style fuzzing for Python when Atheris isn't available

Resources

Key External Resources

Atheris GitHub Repository Official repository with installation instructions, examples, and documentation for fuzzing both pure Python and native extensions.

Native Extension Fuzzing Guide Comprehensive guide covering compilation flags, LD_PRELOAD setup, sanitizer configuration, and troubleshooting for Python C extensions.

Continuously Fuzzing Python C Extensions Trail of Bits blog post covering CI/CD integration, ClusterFuzzLite setup, and real-world examples of fuzzing Python C extensions in continuous integration pipelines.

ClusterFuzzLite Python Integration Guide for integrating Atheris fuzzing into CI/CD pipelines using ClusterFuzzLite for automated continuous fuzzing.

Video Resources

Videos and tutorials are available in the main Atheris documentation and libFuzzer resources.

Files

ATTRIBUTION.mdAdded by AutoGineer931 B
LICENSELicence file added by AutoGineer19.7 KiB
SKILL.md14.4 KiB
agents/openai.yaml237 B
assets/trail-of-bits-mark.svg3.0 KiB
examples.md1.3 KiB
structured-input.md3.3 KiB

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs network access, Needs a command-line tool, Needs Python

Security

What our scanner noticed· Low risk

Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by

Trail of Bits

Publisher

Trail of Bits (Official)

Source

trailofbits/skills · plugins/testing-handbook-skills/skills/atheris · commit e4dd0bb

Licence

Creative Commons Attribution-ShareAlike 4.0 International (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Trail of Bits or Trail of Bits.

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The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download atheris.zip

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by Trail of Bits

Atheris

When to Use

Quick Start

Installation

Prerequisites

Linux/macOS

Docker Environment (Recommended)

Verification

Writing a Harness

Harness Structure for Pure Python

Structured Input with FuzzedDataProvider

Harness Rules

Fuzzing Pure Python Code

Fuzzing Python C Extensions

Environment Configuration

Example: Fuzzing cbor2

Corpus Management

Creating Initial Corpus

Corpus Minimization

Running Campaigns

Basic Run

With Corpus Directory

Common Options

Interpreting Output

Sanitizer Integration

AddressSanitizer (ASan)

LD_PRELOAD Configuration

Common Sanitizer Issues

Advanced Usage

Tips and Tricks

Custom Instrumentation

Performance Tuning

UndefinedBehaviorSanitizer (UBSan)

Real-World Examples

Troubleshooting

Related Skills

Technique Skills

Related Fuzzers

Resources

Key External Resources

Video Resources

Files

LICENSE

Requirements and compatibility

Security

Attribution and licence

Related skills

Security Audit

Sast Configuration

Firmware Analyst

Policy Enforcer

Backend Development Security Auditor

Memory Forensics

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