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.