LibAFL
LibAFL is a modular fuzzing library that implements features from AFL-based fuzzers like AFL++. Unlike traditional fuzzers, LibAFL provides all functionality in a modular and customizable way as a Rust library. It can be used as a drop-in replacement for libFuzzer or as a library to build custom fuzzers from scratch.
When to Use
| Fuzzer | Best For | Complexity |
|---|---|---|
| libFuzzer | Quick setup, single-threaded | Low |
| AFL++ | Multi-core, general purpose | Medium |
| LibAFL | Custom fuzzers, advanced features, research | High |
Choose LibAFL when:
- You need custom mutation strategies or feedback mechanisms
- Standard fuzzers don't support your target architecture
- You want to implement novel fuzzing techniques
- You need fine-grained control over fuzzing components
- You're conducting fuzzing research
Quick Start
LibAFL can be used as a drop-in replacement for libFuzzer with minimal setup:
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
// Call your code with fuzzer-provided data
my_function(data, size);
return 0;
}
Build LibAFL's libFuzzer compatibility layer:
git clone https://github.com/AFLplusplus/LibAFL
cd LibAFL/libafl_libfuzzer_runtime
./build.sh
Compile and run:
clang++ -DNO_MAIN -g -O2 -fsanitize=fuzzer-no-link libFuzzer.a harness.cc main.cc -o fuzz
./fuzz corpus/
Installation
Prerequisites
- Clang/LLVM 15-18
- Rust (via rustup)
- Additional system dependencies
Linux/macOS
Install Clang:
apt install clang
Or install a specific version via apt.llvm.org:
wget https://apt.llvm.org/llvm.sh
chmod +x llvm.sh
sudo ./llvm.sh 15
Configure environment for Rust:
export RUSTFLAGS="-C linker=/usr/bin/clang-15"
export CC="clang-15"
export CXX="clang++-15"
Install Rust:
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
Install additional dependencies:
apt install libssl-dev pkg-config
For libFuzzer compatibility mode, install nightly Rust:
rustup toolchain install nightly --component llvm-tools
Verification
Build LibAFL to verify installation:
cd LibAFL/libafl_libfuzzer_runtime
./build.sh
# Should produce libFuzzer.a
Writing a Harness
LibAFL harnesses follow the same pattern as libFuzzer when using drop-in replacement mode:
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
// Your fuzzing target code here
return 0;
}
When building custom fuzzers with LibAFL as a Rust library, harness logic is integrated directly into the fuzzer. See the "Writing a Custom Fuzzer" section below for the full pattern.
See Also: For detailed harness writing techniques, see the harness-writing technique skill.
Usage Modes
LibAFL supports two primary usage modes:
1. libFuzzer Drop-in Replacement
Use LibAFL as a replacement for libFuzzer with existing harnesses.
Compilation:
clang++ -DNO_MAIN -g -O2 -fsanitize=fuzzer-no-link libFuzzer.a harness.cc main.cc -o fuzz
Running:
./fuzz corpus/
Recommended for long campaigns:
./fuzz -fork=1 -ignore_crashes=1 corpus/
2. Custom Fuzzer as Rust Library
Build a fully customized fuzzer using LibAFL components.
Create project:
cargo init --lib my_fuzzer
cd my_fuzzer
cargo add libafl@0.13 libafl_targets@0.13 libafl_bolts@0.13 libafl_cc@0.13 \
--features "libafl_targets@0.13/libfuzzer,libafl_targets@0.13/sancov_pcguard_hitcounts"
Configure Cargo.toml:
[lib]
crate-type = ["staticlib"]
Writing a Custom Fuzzer
See Also: For detailed harness writing techniques, patterns for handling complex inputs, and advanced strategies, see the fuzz-harness-writing technique skill.
Fuzzer Components
A LibAFL fuzzer consists of modular components:
- Observers - Collect execution feedback (coverage, timing)
- Feedback - Determine if inputs are interesting
- Objective - Define fuzzing goals (crashes, timeouts)
- State - Maintain corpus and metadata
- Mutators - Generate new inputs
- Scheduler - Select which inputs to mutate
- Executor - Run the target with inputs
Basic Fuzzer Structure
use libafl::prelude::*;
use libafl_bolts::prelude::*;
use libafl_targets::{libfuzzer_test_one_input, std_edges_map_observer};
#[no_mangle]
pub extern "C" fn libafl_main() {
let mut run_client = |state: Option<_>, mut restarting_mgr, _core_id| {
// 1. Setup observers
let edges_observer = HitcountsMapObserver::new(
unsafe { std_edges_map_observer("edges") }
).track_indices();
let time_observer = TimeObserver::new("time");
// 2. Define feedback
let mut feedback = feedback_or!(
MaxMapFeedback::new(&edges_observer),
TimeFeedback::new(&time_observer)
);
// 3. Define objective
let mut objective = feedback_or_fast!(
CrashFeedback::new(),
TimeoutFeedback::new()
);
// 4. Create or restore state
let mut state = state.unwrap_or_else(|| {
StdState::new(
StdRand::new(),
InMemoryCorpus::new(),
OnDiskCorpus::new(&output_dir).unwrap(),
&mut feedback,
&mut objective,
).unwrap()
});
// 5. Setup mutator
let mutator = StdScheduledMutator::new(havoc_mutations());
let mut stages = tuple_list!(StdMutationalStage::new(mutator));
// 6. Setup scheduler
let scheduler = IndexesLenTimeMinimizerScheduler::new(
&edges_observer,
QueueScheduler::new()
);
// 7. Create fuzzer
let mut fuzzer = StdFuzzer::new(scheduler, feedback, objective);
// 8. Define harness
let mut harness = |input: &BytesInput| {
let buf = input.target_bytes().as_slice();
libfuzzer_test_one_input(buf);
ExitKind::Ok
};
// 9. Setup executor
let mut executor = InProcessExecutor::with_timeout(
&mut harness,
tuple_list!(edges_observer, time_observer),
&mut fuzzer,
&mut state,
&mut restarting_mgr,
timeout,
)?;
// 10. Load initial inputs
if state.must_load_initial_inputs() {
state.load_initial_inputs(
&mut fuzzer,
&mut executor,
&mut restarting_mgr,
&input_dir
)?;
}
// 11. Start fuzzing
fuzzer.fuzz_loop(&mut stages, &mut executor, &mut state, &mut restarting_mgr)?;
Ok(())
};
// Launch fuzzer
Launcher::builder()
.run_client(&mut run_client)
.cores(&cores)
.build()
.launch()
.unwrap();
}
Compilation
Verbose Mode
Manually specify all instrumentation flags:
clang++-15 -DNO_MAIN -g -O2 \
-fsanitize-coverage=trace-pc-guard \
-fsanitize=address \
-Wl,--whole-archive target/release/libmy_fuzzer.a -Wl,--no-whole-archive \
main.cc harness.cc -o fuzz
Compiler Wrapper (Recommended)
Create a LibAFL compiler wrapper to handle instrumentation automatically.
Create src/bin/libafl_cc.rs:
use libafl_cc::{ClangWrapper, CompilerWrapper, Configuration, ToolWrapper};
pub fn main() {
let args: Vec<String> = env::args().collect();
let mut cc = ClangWrapper::new();
cc.cpp(is_cpp)
.parse_args(&args)
.link_staticlib(&dir, "my_fuzzer")
.add_args(&Configuration::GenerateCoverageMap.to_flags().unwrap())
.add_args(&Configuration::AddressSanitizer.to_flags().unwrap())
.run()
.unwrap();
}
Compile and use:
cargo build --release
target/release/libafl_cxx -DNO_MAIN -g -O2 main.cc harness.cc -o fuzz
See Also: For detailed sanitizer configuration, common issues, and advanced flags, see the address-sanitizer and undefined-behavior-sanitizer technique skills.
Running Campaigns
Basic Run
./fuzz --cores 0 --input corpus/
Multi-Core Fuzzing
./fuzz --cores 0,8-15 --input corpus/
This runs 9 clients: one on core 0, and 8 on cores 8-15.
With Options
./fuzz --cores 0-7 --input corpus/ --output crashes/ --timeout 1000
Text User Interface (TUI)
Enable graphical statistics view:
./fuzz -tui=1 corpus/
Interpreting Output
| Output | Meaning |
|---|---|
corpus: N |
Number of interesting test cases found |
objectives: N |
Number of crashes/timeouts found |
executions: N |
Total number of target invocations |
exec/sec: N |
Current execution throughput |
edges: X% |
Code coverage percentage |
clients: N |
Number of parallel fuzzing processes |
The fuzzer emits two main event types:
- UserStats - Regular heartbeat with current statistics
- Testcase - New interesting input discovered
Advanced Usage
Tips and Tricks
| Tip | Why It Helps |
|---|---|
Use -fork=1 -ignore_crashes=1 |
Continue fuzzing after first crash |
Use InMemoryOnDiskCorpus |
Persist corpus across restarts |
Enable TUI with -tui=1 |
Better visualization of progress |
| Use specific LLVM version | Avoid compatibility issues |
Set RUSTFLAGS correctly |
Prevent linking errors |
Crash Deduplication
Avoid storing duplicate crashes from the same bug:
Add backtrace observer:
let backtrace_observer = BacktraceObserver::owned(
"BacktraceObserver",
libafl::observers::HarnessType::InProcess
);
Update executor:
let mut executor = InProcessExecutor::with_timeout(
&mut harness,
tuple_list!(edges_observer, time_observer, backtrace_observer),
&mut fuzzer,
&mut state,
&mut restarting_mgr,
timeout,
)?;
Update objective with hash feedback:
let mut objective = feedback_and!(
feedback_or_fast!(CrashFeedback::new(), TimeoutFeedback::new()),
NewHashFeedback::new(&backtrace_observer)
);
This ensures only crashes with unique backtraces are saved.
Dictionary Fuzzing
Use dictionaries to guide fuzzing toward specific tokens:
Add tokens from file:
let mut tokens = Tokens::new();
if let Some(tokenfile) = &tokenfile {
tokens.add_from_file(tokenfile)?;
}
state.add_metadata(tokens);
Update mutator:
let mutator = StdScheduledMutator::new(
havoc_mutations().merge(tokens_mutations())
);
Hard-coded tokens example (PNG):
state.add_metadata(Tokens::from([
vec![137, 80, 78, 71, 13, 10, 26, 10], // PNG header
"IHDR".as_bytes().to_vec(),
"IDAT".as_bytes().to_vec(),
"PLTE".as_bytes().to_vec(),
"IEND".as_bytes().to_vec(),
]));
See Also: For detailed dictionary creation strategies and format-specific dictionaries, see the fuzzing-dictionaries technique skill.
Auto Tokens
Automatically extract magic values and checksums from the program:
Enable in compiler wrapper:
cc.add_pass(LLVMPasses::AutoTokens)
Load auto tokens in fuzzer:
tokens += libafl_targets::autotokens()?;
Verify tokens section:
echo "p (uint8_t *)__token_start" | gdb fuzz
Performance Tuning
| Setting | Impact |
|---|---|
| Multi-core fuzzing | Linear speedup with cores |
InMemoryCorpus |
Faster but non-persistent |
InMemoryOnDiskCorpus |
Balanced speed and persistence |
| Sanitizers | 2-5x slowdown, essential for bugs |
Optimization level -O2 |
Balance between speed and coverage |
Debugging Fuzzer
Run fuzzer in single-process mode for easier debugging:
// Replace launcher with direct call
run_client(None, SimpleEventManager::new(monitor), 0).unwrap();
// Comment out:
// Launcher::builder()
// .run_client(&mut run_client)
// ...
// .launch()
Then debug with GDB:
gdb --args ./fuzz --cores 0 --input corpus/
Real-World Examples
Example: libpng
Fuzzing libpng using LibAFL:
1. Get source code:
curl -L -O https://downloads.sourceforge.net/project/libpng/libpng16/1.6.37/libpng-1.6.37.tar.xz
tar xf libpng-1.6.37.tar.xz
cd libpng-1.6.37/
apt install zlib1g-dev
2. Set compiler wrapper:
export FUZZER_CARGO_DIR="/path/to/libafl/project"
export CC=$FUZZER_CARGO_DIR/target/release/libafl_cc
export CXX=$FUZZER_CARGO_DIR/target/release/libafl_cxx
3. Build static library:
./configure --enable-shared=no
make
4. Get harness:
curl -O https://raw.githubusercontent.com/glennrp/libpng/f8e5fa92b0e37ab597616f554bee254157998227/contrib/oss-fuzz/libpng_read_fuzzer.cc
5. Link fuzzer:
$CXX libpng_read_fuzzer.cc .libs/libpng16.a -lz -o fuzz
6. Prepare seeds:
mkdir seeds/
curl -o seeds/input.png https://raw.githubusercontent.com/glennrp/libpng/acfd50ae0ba3198ad734e5d4dec2b05341e50924/contrib/pngsuite/iftp1n3p08.png
7. Get dictionary (optional):
curl -O https://raw.githubusercontent.com/glennrp/libpng/2fff013a6935967960a5ae626fc21432807933dd/contrib/oss-fuzz/png.dict
8. Start fuzzing:
./fuzz --input seeds/ --cores 0 -x png.dict
Example: CMake Project
Integrate LibAFL with CMake build system:
CMakeLists.txt:
project(BuggyProgram)
cmake_minimum_required(VERSION 3.0)
add_executable(buggy_program main.cc)
add_executable(fuzz main.cc harness.cc)
target_compile_definitions(fuzz PRIVATE NO_MAIN=1)
target_compile_options(fuzz PRIVATE -g -O2)
Build non-instrumented binary:
cmake -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ .
cmake --build . --target buggy_program
Build fuzzer:
export FUZZER_CARGO_DIR="/path/to/libafl/project"
cmake -DCMAKE_C_COMPILER=$FUZZER_CARGO_DIR/target/release/libafl_cc \
-DCMAKE_CXX_COMPILER=$FUZZER_CARGO_DIR/target/release/libafl_cxx .
cmake --build . --target fuzz
Run fuzzing:
./fuzz --input seeds/ --cores 0
Troubleshooting
| Problem | Cause | Solution |
|---|---|---|
| No coverage increases | Instrumentation failed | Verify compiler wrapper used, check for -fsanitize-coverage |
| Fuzzer won't start | Empty corpus with no interesting inputs | Provide seed inputs that trigger code paths |
Linker errors with libafl_main |
Runtime not linked | Use -Wl,--whole-archive or -u libafl_main |
| LLVM version mismatch | LibAFL requires LLVM 15-18 | Install compatible LLVM version, set environment variables |
| Rust compilation fails | Outdated Rust or Cargo | Update Rust with rustup update |
| Slow fuzzing | Sanitizers enabled | Expected 2-5x slowdown, necessary for finding bugs |
| Environment variable interference | CC, CXX, RUSTFLAGS set |
Unset after building LibAFL project |
| Cannot attach debugger | Multi-process fuzzing | Run in single-process mode (see Debugging section) |
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 | Undefined behavior detection |
| coverage-analysis | Measuring and improving code coverage |
| fuzzing-corpus | Building and managing seed corpora |
| fuzzing-dictionaries | Creating dictionaries for format-aware fuzzing |
Related Fuzzers
| Skill | When to Consider |
|---|---|
| libfuzzer | Simpler setup, don't need LibAFL's advanced features |
| aflpp | Multi-core fuzzing without custom fuzzer development |
| cargo-fuzz | Fuzzing Rust projects with less setup |
Resources
Official Documentation
- LibAFL Book - Official handbook with comprehensive documentation
- LibAFL GitHub - Source code and examples
- LibAFL API Documentation - Rust API reference
Examples and Tutorials
- LibAFL Examples - Collection of example fuzzers
- cargo-fuzz with LibAFL - Using LibAFL as cargo-fuzz backend
- Testing Handbook LibAFL Examples - Complete working examples from this handbook