Libfuzzer

libFuzzer

libFuzzer is an in-process, coverage-guided fuzzer that is part of the LLVM project. It's the recommended starting point for fuzzing C/C++ projects due to its simplicity and integration with the LLVM toolchain. While libFuzzer has been in maintenance-only mode since late 2022, it is easier to install and use than its alternatives, has wide support, and will be maintained for the foreseeable future.

When to Use

Choose libFuzzer when:

• You need a simple, quick setup for C/C++ code
• Project uses Clang for compilation
• Single-core fuzzing is sufficient initially
• Transitioning to AFL++ later is an option (harnesses are compatible)

Note: Fuzzing harnesses written for libFuzzer are compatible with AFL++, making it easy to transition if you need more advanced features like better multi-core support.

Quick Start

#include <stdint.h>#include <stddef.h>
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {    // Validate input if needed    if (size < 1) return 0;
    // Call your target function with fuzzer-provided data    my_target_function(data, size);
    return 0;}

Compile and run:

clang++ -fsanitize=fuzzer,address -g -O2 harness.cc target.cc -o fuzzmkdir corpus/./fuzz corpus/

Installation

Prerequisites

• LLVM/Clang compiler (includes libFuzzer)
• LLVM tools for coverage analysis (optional)

Linux (Ubuntu/Debian)

apt install clang llvm

For the latest LLVM version:

# Add LLVM repository from apt.llvm.org# Then install specific version, e.g.:apt install clang-18 llvm-18

macOS

# Using Homebrewbrew install llvm
# Or using Nixnix-env -i clang

Windows

Install Clang through Visual Studio. Refer to Microsoft's documentation for setup instructions.

Recommendation: If possible, fuzz on a local x86_64 VM or rent one on DigitalOcean, AWS, or Hetzner. Linux provides the best support for libFuzzer.

Verification

clang++ --version# Should show LLVM version information

Writing a Harness

Harness Structure

The harness is the entry point for the fuzzer. libFuzzer calls the LLVMFuzzerTestOneInput function repeatedly with different inputs.

#include <stdint.h>#include <stddef.h>
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {    // 1. Optional: Validate input size    if (size < MIN_REQUIRED_SIZE) {        return 0;  // Reject inputs that are too small    }
    // 2. Optional: Convert raw bytes to structured data    // Example: Parse two integers from byte array    if (size >= 2 * sizeof(uint32_t)) {        uint32_t a = *(uint32_t*)(data);        uint32_t b = *(uint32_t*)(data + sizeof(uint32_t));        my_function(a, b);    }
    // 3. Call target function    target_function(data, size);
    // 4. Always return 0 (non-zero reserved for future use)    return 0;}

Harness Rules

Rationale:

• Speed matters: Aim for 100s-1000s executions per second per core
• Reproducibility: Crashes must be reproducible after fuzzing completes
• Isolation: Each execution should be independent

Using FuzzedDataProvider for Complex Inputs

For complex inputs (strings, multiple parameters), use the FuzzedDataProvider helper:

#include <stdint.h>#include <stddef.h>#include "FuzzedDataProvider.h"  // From LLVM project
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {    FuzzedDataProvider fuzzed_data(data, size);
    // Extract structured data    size_t allocation_size = fuzzed_data.ConsumeIntegral<size_t>();    std::vector<char> str1 = fuzzed_data.ConsumeBytesWithTerminator<char>(32, 0xFF);    std::vector<char> str2 = fuzzed_data.ConsumeBytesWithTerminator<char>(32, 0xFF);
    // Call target with extracted data    char* result = concat(&str1[0], str1.size(), &str2[0], str2.size(), allocation_size);    if (result != NULL) {        free(result);    }
    return 0;}

Download FuzzedDataProvider.h from the LLVM repository.

Interleaved Fuzzing

Use a single harness to test multiple related functions:

extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {    if (size < 1 + 2 * sizeof(int32_t)) {        return 0;    }
    uint8_t mode = data[0];    int32_t numbers[2];    memcpy(numbers, data + 1, 2 * sizeof(int32_t));
    // Select function based on first byte    switch (mode % 4) {        case 0: add(numbers[0], numbers[1]); break;        case 1: subtract(numbers[0], numbers[1]); break;        case 2: multiply(numbers[0], numbers[1]); break;        case 3: divide(numbers[0], numbers[1]); break;    }
    return 0;}

See Also: For detailed harness writing techniques, patterns for handling complex inputs, structure-aware fuzzing, and protobuf-based fuzzing, see the fuzz-harness-writing technique skill.

Compilation

Basic Compilation

The key flag is -fsanitize=fuzzer, which:

• Links the libFuzzer runtime (provides main function)
• Enables SanitizerCoverage instrumentation for coverage tracking
• Disables built-in functions like memcmp

clang++ -fsanitize=fuzzer -g -O2 harness.cc target.cc -o fuzz

Flags explained:

• -fsanitize=fuzzer: Enable libFuzzer
• -g: Add debug symbols (helpful for crash analysis)
• -O2: Production-level optimizations (recommended for fuzzing)
• -DNO_MAIN: Define macro if your code has a main function

With Sanitizers

AddressSanitizer (recommended):

clang++ -fsanitize=fuzzer,address -g -O2 -U_FORTIFY_SOURCE harness.cc target.cc -o fuzz

Multiple sanitizers:

clang++ -fsanitize=fuzzer,address,undefined -g -O2 harness.cc target.cc -o fuzz

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

Build Flags

Building Static Libraries

For projects that produce static libraries:

1. Build the library with fuzzing instrumentation:

export CC=clang CFLAGS="-fsanitize=fuzzer-no-link -fsanitize=address"export CXX=clang++ CXXFLAGS="$CFLAGS"./configure --enable-shared=nomake

2. Link the static library with your harness:

clang++ -fsanitize=fuzzer -fsanitize=address harness.cc libmylib.a -o fuzz

CMake Integration

project(FuzzTarget)cmake_minimum_required(VERSION 3.0)
add_executable(fuzz main.cc harness.cc)target_compile_definitions(fuzz PRIVATE NO_MAIN=1)target_compile_options(fuzz PRIVATE -g -O2 -fsanitize=fuzzer -fsanitize=address)target_link_libraries(fuzz -fsanitize=fuzzer -fsanitize=address)

Build with:

cmake -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ .cmake --build .

Corpus Management

Creating Initial Corpus

Create a directory for the corpus (can start empty):

mkdir corpus/

Optional but recommended: Provide seed inputs (valid example files):

# For a PNG parser:cp examples/*.png corpus/
# For a protocol parser:cp test_packets/*.bin corpus/

Benefits of seed inputs:

• Fuzzer doesn't start from scratch
• Reaches valid code paths faster
• Significantly improves effectiveness

Corpus Structure

The corpus directory contains:

• Input files that trigger unique code paths
• Minimized versions (libFuzzer automatically minimizes)
• Named by content hash (e.g., a9993e364706816aba3e25717850c26c9cd0d89d)

Corpus Minimization

libFuzzer automatically minimizes corpus entries during fuzzing. To explicitly minimize:

mkdir minimized_corpus/./fuzz -merge=1 minimized_corpus/ corpus/

This creates a deduplicated, minimized corpus in minimized_corpus/.

See Also: For corpus creation strategies, seed selection, format-specific corpus building, and corpus maintenance, see the fuzzing-corpus technique skill.

Running Campaigns

Basic Run

./fuzz corpus/

This runs until a crash is found or you stop it (Ctrl+C).

Recommended: Continue After Crashes

./fuzz -fork=1 -ignore_crashes=1 corpus/

The -fork and -ignore_crashes flags (experimental but widely used) allow fuzzing to continue after finding crashes.

Common Options

Control input size:

./fuzz -max_len=4000 corpus/

Rule of thumb: 2x the size of minimal realistic input.

Set timeout:

./fuzz -timeout=2 corpus/

Abort test cases that run longer than 2 seconds.

Use a dictionary:

./fuzz -dict=./format.dict corpus/

Close stdout/stderr (speed up fuzzing):

./fuzz -close_fd_mask=3 corpus/

See all options:

./fuzz -help=1

Multi-Core Fuzzing

Option 1: Jobs and workers (recommended):

./fuzz -jobs=4 -workers=4 -fork=1 -ignore_crashes=1 corpus/

• -jobs=4: Run 4 sequential campaigns
• -workers=4: Process jobs in parallel with 4 processes
• Test cases are shared between jobs

Option 2: Fork mode:

./fuzz -fork=4 -ignore_crashes=1 corpus/

Note: For serious multi-core fuzzing, consider switching to AFL++, Honggfuzz, or LibAFL.

Re-executing Test Cases

Re-run a single crash:

./fuzz ./crash-a9993e364706816aba3e25717850c26c9cd0d89d

Test all inputs in a directory without fuzzing:

./fuzz -runs=0 corpus/

Interpreting Output

When fuzzing runs, you'll see statistics like:

INFO: Seed: 3517090860INFO: Loaded 1 modules (9 inline 8-bit counters)#2      INITED cov: 3 ft: 4 corp: 1/1b exec/s: 0 rss: 26Mb#57     NEW    cov: 4 ft: 5 corp: 2/4b lim: 4 exec/s: 0 rss: 26Mb

On crash:

==11672== ERROR: libFuzzer: deadly signalartifact_prefix='./'; Test unit written to ./crash-a9993e364706816aba3e25717850c26c9cd0d89d0x61,0x62,0x63,abcBase64: YWJj

The crash is saved to ./crash-<hash> with the input shown in hex, UTF-8, and Base64.

Reproducibility: Use -seed=<value> to reproduce a fuzzing campaign (single-core only).

Fuzzing Dictionary

Dictionaries help the fuzzer discover interesting inputs faster by providing hints about the input format.

Dictionary Format

Create a text file with quoted strings (one per line):

# Lines starting with '#' are comments
# Magic bytesmagic="\x89PNG"magic2="IEND"
# Keywords"GET""POST""Content-Type"
# Hex sequencesdelimiter="\xFF\xD8\xFF"

Using a Dictionary

./fuzz -dict=./format.dict corpus/

Generating a Dictionary

From header files:

grep -o '".*"' header.h > header.dict

From man pages:

man curl | grep -oP '^\s*(--|-)\K\S+' | sed 's/[,.]$//' | sed 's/^/"&/; s/$/&"/' | sort -u > man.dict

From binary strings:

strings ./binary | sed 's/^/"&/; s/$/&"/' > strings.dict

Using LLMs: Ask ChatGPT or similar to generate a dictionary for your format (e.g., "Generate a libFuzzer dictionary for a JSON parser").

See Also: For advanced dictionary generation, format-specific dictionaries, and dictionary optimization strategies, see the fuzzing-dictionaries technique skill.

Coverage Analysis

While libFuzzer shows basic coverage stats (cov: N), detailed coverage analysis requires additional tools.

Source-Based Coverage

1. Recompile with coverage instrumentation:

clang++ -fsanitize=fuzzer -fprofile-instr-generate -fcoverage-mapping harness.cc target.cc -o fuzz

2. Run fuzzer to collect coverage:

LLVM_PROFILE_FILE="coverage-%p.profraw" ./fuzz -runs=10000 corpus/

3. Merge coverage data:

llvm-profdata merge -sparse coverage-*.profraw -o coverage.profdata

4. Generate coverage report:

llvm-cov show ./fuzz -instr-profile=coverage.profdata

5. Generate HTML report:

llvm-cov show ./fuzz -instr-profile=coverage.profdata -format=html > coverage.html

Improving Coverage

Tips:

• Provide better seed inputs in corpus
• Use dictionaries for format-aware fuzzing
• Check if harness properly exercises target
• Consider structure-aware fuzzing for complex formats
• Run longer campaigns (days/weeks)

See Also: For detailed coverage analysis techniques, identifying coverage gaps, systematic coverage improvement, and comparing coverage across fuzzers, see the coverage-analysis technique skill.

Sanitizer Integration

AddressSanitizer (ASan)

ASan detects memory errors like buffer overflows and use-after-free bugs. Highly recommended for fuzzing.

Enable ASan:

clang++ -fsanitize=fuzzer,address -g -O2 -U_FORTIFY_SOURCE harness.cc target.cc -o fuzz

Example ASan output:

==1276163==ERROR: AddressSanitizer: heap-buffer-overflow on address 0x6020000c4ab1WRITE of size 1 at 0x6020000c4ab1 thread T0    #0 0x55555568631a in check_buf(char*, unsigned long) main.cc:13:25    #1 0x5555556860bf in LLVMFuzzerTestOneInput harness.cc:7:3

Configure ASan with environment variables:

ASAN_OPTIONS=verbosity=1:abort_on_error=1 ./fuzz corpus/

Important flags:

• verbosity=1: Show ASan is active
• detect_leaks=0: Disable leak detection (leaks reported at end)
• abort_on_error=1: Call abort() instead of _exit() on errors

Drawbacks:

• 2-4x slowdown
• Requires ~20TB virtual memory (disable memory limits: -rss_limit_mb=0)
• Best supported on Linux

See Also: For comprehensive ASan configuration, common pitfalls, symbolization, and combining with other sanitizers, see the address-sanitizer technique skill.

UndefinedBehaviorSanitizer (UBSan)

UBSan detects undefined behavior like integer overflow, null pointer dereference, etc.

Enable UBSan:

clang++ -fsanitize=fuzzer,undefined -g -O2 harness.cc target.cc -o fuzz

Combine with ASan:

clang++ -fsanitize=fuzzer,address,undefined -g -O2 harness.cc target.cc -o fuzz

MemorySanitizer (MSan)

MSan detects uninitialized memory reads. More complex to use (requires rebuilding all dependencies).

clang++ -fsanitize=fuzzer,memory -g -O2 harness.cc target.cc -o fuzz

Common Sanitizer Issues

Real-World Examples

Example 1: Fuzzing libpng

libpng is a widely-used library for reading/writing PNG images. Bugs can lead to security issues.

1. Get source code:

curl -L -O https://downloads.sourceforge.net/project/libpng/libpng16/1.6.37/libpng-1.6.37.tar.xztar xf libpng-1.6.37.tar.xzcd libpng-1.6.37/

2. Install dependencies:

apt install zlib1g-dev

3. Compile with fuzzing instrumentation:

export CC=clang CFLAGS="-fsanitize=fuzzer-no-link -fsanitize=address"export CXX=clang++ CXXFLAGS="$CFLAGS"./configure --enable-shared=nomake

4. Get a harness (or write your own):

curl -O https://raw.githubusercontent.com/glennrp/libpng/f8e5fa92b0e37ab597616f554bee254157998227/contrib/oss-fuzz/libpng_read_fuzzer.cc

5. Prepare corpus and dictionary:

mkdir corpus/curl -o corpus/input.png https://raw.githubusercontent.com/glennrp/libpng/acfd50ae0ba3198ad734e5d4dec2b05341e50924/contrib/pngsuite/iftp1n3p08.pngcurl -O https://raw.githubusercontent.com/glennrp/libpng/2fff013a6935967960a5ae626fc21432807933dd/contrib/oss-fuzz/png.dict

6. Link and compile fuzzer:

clang++ -fsanitize=fuzzer -fsanitize=address libpng_read_fuzzer.cc .libs/libpng16.a -lz -o fuzz

7. Run fuzzing campaign:

./fuzz -close_fd_mask=3 -dict=./png.dict corpus/

Example 2: Simple Division Bug

Harness that finds a division-by-zero bug:

#include <stdint.h>#include <stddef.h>
double divide(uint32_t numerator, uint32_t denominator) {    // Bug: No check if denominator is zero    return numerator / denominator;}
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {    if(size != 2 * sizeof(uint32_t)) {        return 0;    }
    uint32_t numerator = *(uint32_t*)(data);    uint32_t denominator = *(uint32_t*)(data + sizeof(uint32_t));
    divide(numerator, denominator);
    return 0;}

Compile and fuzz:

clang++ -fsanitize=fuzzer harness.cc -o fuzz./fuzz

The fuzzer will quickly find inputs causing a crash.

Advanced Usage

Tips and Tricks

Structure-Aware Fuzzing

For highly structured inputs (e.g., complex protocols, file formats), use libprotobuf-mutator:

• Define input structure using Protocol Buffers
• libFuzzer mutates protobuf messages (structure-preserving mutations)
• Harness converts protobuf to native format

See structure-aware fuzzing documentation for details.

Custom Mutators

libFuzzer allows custom mutators for specialized fuzzing:

extern "C" size_t LLVMFuzzerCustomMutator(uint8_t *Data, size_t Size,                                          size_t MaxSize, unsigned int Seed) {    // Custom mutation logic    return new_size;}
extern "C" size_t LLVMFuzzerCustomCrossOver(const uint8_t *Data1, size_t Size1,                                            const uint8_t *Data2, size_t Size2,                                            uint8_t *Out, size_t MaxOutSize,                                            unsigned int Seed) {    // Custom crossover logic    return new_size;}

Performance Tuning

Troubleshooting

Related Skills

Technique Skills

Related Fuzzers

Resources

Official Documentation

• LLVM libFuzzer Documentation - Official reference
• libFuzzer Tutorial by Google - Step-by-step guide
• SanitizerCoverage - Coverage instrumentation details

Advanced Topics

• Structure-Aware Fuzzing with libprotobuf-mutator
• Split Inputs in libFuzzer
• FuzzedDataProvider Header

Example Projects

• OSS-Fuzz - Continuous fuzzing for open-source projects (many libFuzzer examples)
• AFL++ Dictionary Collection - Reusable dictionaries