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

Fuzzer Best For Complexity

libFuzzer Quick setup, single-project fuzzing Low

AFL++ Multi-core fuzzing, diverse mutations Medium

LibAFL Custom fuzzers, research projects High

Honggfuzz Hardware-based coverage Medium

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 fuzz mkdir 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 Homebrew

brew install llvm

Or using Nix

nix-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

Do Don't

Handle all input types (empty, huge, malformed) Call exit()

• stops fuzzing process

Join all threads before returning Leave threads running

Keep harness fast and simple Add excessive logging or complexity

Maintain determinism Use random number generators or read /dev/random

Reset global state between runs Rely on state from previous executions

Use narrow, focused targets Mix unrelated data formats (PNG + TCP) in one harness

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

Flag Purpose

-fsanitize=fuzzer

Enable libFuzzer runtime and instrumentation

-fsanitize=address

Enable AddressSanitizer (memory error detection)

-fsanitize=undefined

Enable UndefinedBehaviorSanitizer

-fsanitize=fuzzer-no-link

Instrument without linking fuzzer (for libraries)

-g

Include debug symbols

-O2

Production optimization level

-U_FORTIFY_SOURCE

Disable fortification (can interfere with ASan)

Building Static Libraries

For projects that produce static libraries:

• Build the library with fuzzing instrumentation:

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

• 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: 3517090860 INFO: 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

Output Meaning

INITED

Fuzzing initialized

NEW

New coverage found, added to corpus

REDUCE

Input minimized while keeping coverage

cov: N

Number of coverage edges hit

corp: X/Yb

Corpus size: X entries, Y total bytes

exec/s: N

Executions per second

rss: NMb

Resident memory usage

On crash:

==11672== ERROR: libFuzzer: deadly signal artifact_prefix='./'; Test unit written to ./crash-a9993e364706816aba3e25717850c26c9cd0d89d 0x61,0x62,0x63, abc Base64: 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 bytes

magic="\x89PNG" magic2="IEND"

Keywords

"GET" "POST" "Content-Type"

Hex sequences

delimiter="\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 0x6020000c4ab1 WRITE 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

Issue Solution

ASan slows fuzzing too much Use -fsanitize-recover=address for non-fatal errors

Out of memory Set ASAN_OPTIONS=rss_limit_mb=0 or -rss_limit_mb=0

Stack exhaustion Increase stack size: ASAN_OPTIONS=stack_size=8388608

False positives with _FORTIFY_SOURCE

Use -U_FORTIFY_SOURCE flag

MSan reports in dependencies Rebuild all dependencies with -fsanitize=memory

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.xz tar xf libpng-1.6.37.tar.xz cd 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=no make

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.png curl -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

Tip Why It Helps

Start with single-core, switch to AFL++ for multi-core libFuzzer harnesses work with AFL++

Use dictionaries for structured formats 10-100x faster bug discovery

Close file descriptors with -close_fd_mask=3

Speed boost if SUT writes output

Set reasonable -max_len

Prevents wasted time on huge inputs

Run for days/weeks, not minutes Coverage plateaus take time to break

Use seed corpus from test suites Starts fuzzing from valid inputs

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

Setting Impact

-close_fd_mask=3

Closes stdout/stderr, speeds up fuzzing

-max_len=<reasonable_size>

Avoids wasting time on huge inputs

-timeout=<seconds>

Detects hangs, prevents stuck executions

Disable ASan for baseline 2-4x speed boost (but misses memory bugs)

Use -jobs and -workers

Limited multi-core support

Run on Linux Best platform support and performance

Troubleshooting

Problem Cause Solution

No crashes found after hours Poor corpus, low coverage Add seed inputs, use dictionary, check harness

Very slow executions/sec (<100) Target too complex, excessive logging Optimize target, use -close_fd_mask=3 , reduce logging

Out of memory ASan's 20TB virtual memory Set -rss_limit_mb=0 to disable RSS limit

Fuzzer stops after first crash Default behavior Use -fork=1 -ignore_crashes=1 to continue

Can't reproduce crash Non-determinism in harness/target Remove random number generation, global state

Linking errors with -fsanitize=fuzzer

Missing libFuzzer runtime Ensure using Clang, check LLVM installation

GCC project won't compile with Clang GCC-specific code Switch to AFL++ with gcc_plugin instead

Coverage not improving Corpus plateau Run longer, add dictionary, improve seeds, check coverage report

Crashes but ASan doesn't trigger Memory error not detected without ASan Recompile with -fsanitize=address

Related Skills

Technique Skills

Skill Use Case

fuzz-harness-writing Detailed guidance on writing effective harnesses, structure-aware fuzzing, and FuzzedDataProvider usage

address-sanitizer Memory error detection configuration, ASAN_OPTIONS, and troubleshooting

undefined-behavior-sanitizer Detecting undefined behavior during fuzzing

coverage-analysis Measuring fuzzing effectiveness and identifying untested code paths

fuzzing-corpus Building and managing seed corpora, corpus minimization strategies

fuzzing-dictionaries Creating format-specific dictionaries for faster bug discovery

Related Fuzzers

Skill When to Consider

aflpp When you need serious multi-core fuzzing, or when libFuzzer coverage plateaus

honggfuzz When you want hardware-based coverage feedback on Linux

libafl When building custom fuzzers or conducting fuzzing research

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