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.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "atheris" with this command: npx skills add trailofbits/skills/trailofbits-skills-atheris

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 test_one_input(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, test_one_input) atheris.Fuzz()

if name == "main": main()

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 pip install 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 test_one_input(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, test_one_input) atheris.Fuzz()

if name == "main": main()

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 test_one_input(data: bytes): target_function(data)

atheris.Setup(sys.argv, test_one_input) 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 python -m pip install --no-binary cbor2 cbor2==5.6.4

The --no-binary flag ensures the C extension is compiled locally with instrumentation.

Create cbor2-fuzz.py :

import sys import atheris

_cbor2 ensures the C library is imported

from _cbor2 import loads

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

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

if name == "main": main()

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:

python fuzz.py corpus/

Corpus Minimization

Atheris inherits corpus minimization from libFuzzer:

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

python fuzz.py

With Corpus Directory

python fuzz.py corpus/

Common Options

Run for 10 minutes

python fuzz.py -max_total_time=600

Limit input size

python fuzz.py -max_len=1024

Run with multiple workers

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 test_one_input(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

Example: Pure Python Parser

import sys import atheris import json

@atheris.instrument_func def test_one_input(data: bytes): try: # Fuzz Python's JSON parser json.loads(data.decode('utf-8', errors='ignore')) except (ValueError, UnicodeDecodeError): pass

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

if name == "main": main()

Example: HTTP Request Parsing

import sys import atheris

with atheris.instrument_imports(): from urllib3 import HTTPResponse from io import BytesIO

def test_one_input(data: bytes): try: # Fuzz HTTP response parsing fake_response = HTTPResponse( body=BytesIO(data), headers={}, preload_content=False ) fake_response.read() except Exception: pass

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

if name == "main": main()

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

Related Skills

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

Related Fuzzers

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.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Coding

codeql

No summary provided by upstream source.

Repository SourceNeeds Review
Coding

modern-python

No summary provided by upstream source.

Repository SourceNeeds Review
Coding

spec-to-code-compliance

No summary provided by upstream source.

Repository SourceNeeds Review