atheris
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 corrupt
Install
npx skills add https://github.com/trailofbits/skills/tree/main/plugins/testing-handbook-skills/skills/atheris
claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install trailofbits-skills@llmmart
git clone https://github.com/trailofbits/skills.git
The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole trailofbits/skills collection as a plugin from our marketplace. Git is the plain clone.
Skill manifest
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 instrumentationatheris.instrument_imports()- Context manager for instrumenting all imported modulesatheris.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_PRELOADmanually.
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 |
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.
Files (skills)
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agents
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openai.yaml 237 B
interface: display_name: "Atheris Fuzzing" short_description: "Fuzz Python code and native extensions with Atheris" icon_small: "assets/trail-of-bits-mark.svg" icon_large: "assets/trail-of-bits-mark.svg" brand_color: "#D83A34"
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assets
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trail-of-bits-mark.svg 3 KB · in bundle
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examples.md 1.3 KB
# Atheris Examples Two complete harnesses, each runnable as written. ## Example: Pure Python Parser ```python import sys import atheris import json @atheris.instrument_func def TestOneInput(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, TestOneInput) atheris.Fuzz() if __name__ == "__main__": main() ``` ## Example: HTTP Request Parsing ```python import sys import atheris with atheris.instrument_imports(): from urllib3 import HTTPResponse from io import BytesIO def TestOneInput(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, TestOneInput) atheris.Fuzz() if __name__ == "__main__": main() ``` Both catch `Exception` broadly to get a campaign started. Narrow that to the exceptions the target is documented to raise before you trust the results — a bare `except Exception` also swallows the bugs you are fuzzing for. -
SKILL.md 14.4 KB
--- name: atheris type: fuzzer description: "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." --- # 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 ```python 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: ```bash 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](https://github.com/llvm/llvm-project/releases)) - For Docker users: [Docker Desktop](https://www.docker.com/products/docker-desktop/) ### Linux/macOS ```bash 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: ```dockerfile # 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: ```bash docker build -t atheris . docker run -it atheris ``` ### Verification ```bash python -c "import atheris; print(atheris.__version__)" ``` ## Writing a Harness ### Harness Structure for Pure Python ```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: ```python fdp = atheris.FuzzedDataProvider(data) name = fdp.ConsumeUnicodeNoSurrogates(fdp.ConsumeIntInRange(0, 64)) strict = fdp.ConsumeBool() ``` See [structured-input.md](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: ```python 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: ```bash 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: ```bash 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`: ```python 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: ```bash uv run python cbor2-fuzz.py ``` > **Important:** When running locally (not in Docker), you must [set `LD_PRELOAD` manually](https://github.com/google/atheris/blob/master/native_extension_fuzzing.md#option-a-sanitizerlibfuzzer-preloads). ## Corpus Management ### Creating Initial Corpus ```bash mkdir corpus # Add seed inputs echo "test data" > corpus/seed1 echo '{"key": "value"}' > corpus/seed2 ``` Run with corpus: ```bash uv run python fuzz.py corpus/ ``` ### Corpus Minimization Atheris inherits corpus minimization from libFuzzer: ```bash 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 ```bash uv run python fuzz.py ``` ### With Corpus Directory ```bash uv run python fuzz.py corpus/ ``` ### Common Options ```bash # 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: ```bash export CFLAGS="-fsanitize=address,fuzzer-no-link" export CXXFLAGS="-fsanitize=address,fuzzer-no-link" ``` Configure ASan behavior: ```bash export ASAN_OPTIONS="allocator_may_return_null=1,detect_leaks=0" ``` ### LD_PRELOAD Configuration For native extension fuzzing: ```bash 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: ```python 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: ```bash 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](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 | ## 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](https://github.com/google/atheris)** Official repository with installation instructions, examples, and documentation for fuzzing both pure Python and native extensions. **[Native Extension Fuzzing Guide](https://github.com/google/atheris/blob/master/native_extension_fuzzing.md)** Comprehensive guide covering compilation flags, LD_PRELOAD setup, sanitizer configuration, and troubleshooting for Python C extensions. **[Continuously Fuzzing Python C Extensions](https://blog.trailofbits.com/2024/02/23/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](https://google.github.io/clusterfuzzlite/build-integration/python-lang/)** 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. -
structured-input.md 3.3 KB
# Structured Input with FuzzedDataProvider A target that takes several typed arguments — a string, a length, a flag — 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 while keeping each draw stable under mutation. ## Basic Usage ```python @atheris.instrument_func def TestOneInput(data: bytes): fdp = atheris.FuzzedDataProvider(data) name = fdp.ConsumeUnicodeNoSurrogates(fdp.ConsumeIntInRange(0, 64)) count = fdp.ConsumeIntInRange(1, 1000) strict = fdp.ConsumeBool() your_target_function(name, count, strict=strict) ``` Draw in a fixed order. Each call consumes from where the last one left off, so inserting or reordering a call reinterprets every byte after it and devalues the corpus already built. Ask for a size before the content it bounds, as above: an unbounded string lets the fuzzer spend the whole buffer on one field and starve every draw after it. ## Method Reference | Need | Call | |------|------| | Raw bytes | `ConsumeBytes(count)` | | Text | `ConsumeUnicodeNoSurrogates(count)` | | Text, including unpaired surrogates | `ConsumeUnicode(count)` | | Bounded integer | `ConsumeIntInRange(min, max)` | | Sized integer | `ConsumeInt(size)` (signed), `ConsumeUInt(size)` | | Float | `ConsumeFloat()`, `ConsumeRegularFloat()` (no `NaN`/`Inf`), `ConsumeProbability()` | | Flag | `ConsumeBool()` | | Choice from a fixed set | `PickValueInList(values)` | | Everything not yet consumed | `ConsumeBytes(fdp.remaining_bytes())` | `remaining_bytes()` is an accessor, not a draw — it returns the count of unconsumed bytes and consumes nothing. It is the one method here that is not named `Consume*`, and the only one whose return value is a length rather than a value. Pass it to `ConsumeBytes` to drain the buffer; using it directly hands your target an `int` where it expects `bytes`. Prefer `ConsumeUnicodeNoSurrogates` unless you are specifically testing surrogate handling. `ConsumeUnicode` may emit unpaired surrogates (U+D800–U+DFFF), which are legal in a Python `str` but raise `UnicodeEncodeError` the moment the target encodes them — so a target that encodes anywhere reports a crash on its own input handling rather than on your target's logic. List variants take the element count first: | Call | Produces | |------|----------| | `ConsumeIntList(count, bytes)` | `count` integers of `bytes` size each | | `ConsumeIntListInRange(count, min, max)` | `count` integers in `[min, max]` | | `ConsumeFloatList(count)` | `count` arbitrary floats, `NaN` and `Inf` included | | `ConsumeRegularFloatList(count)` | `count` floats, never `NaN` or `Inf` | | `ConsumeProbabilityList(count)` | `count` floats in `[0, 1]` | | `ConsumeFloatListInRange(count, min, max)` | `count` floats in `[min, max]` | ## Running Out of Input Every method degrades rather than raising when the buffer empties: consumers return empty values, and `ConsumeIntInRange` returns `min`. A harness that draws more than the fuzzer supplies will not error — it will quietly test the same degenerate case over and over, which looks like a healthy campaign that has stopped finding anything. Check `remaining_bytes()` and return early if your harness needs a minimum amount of input.
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