Libfuzzer

Trail of BitsOfficialPublished by Trail of Bits

Skill
Tool integration
Software development
CC-BY-SA-4.0
Low risk

From the author

Sets up and runs libFuzzer, the coverage-guided fuzzer built into LLVM, on C/C++ code that compiles with Clang. Covers harness structure, -fsanitize=fuzzer builds, corpus and dictionary management, sanitizer integration, and campaign triage. Use when writing or debugging an LLVMFuzzerTestOneInput harness, starting fuzzing on a C/C++ library, choosing between libFuzzer and AFL++, or working out why a libFuzzer run finds nothing.

— the description by Trail of Bits

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

libFuzzer is an in-process, coverage-guided fuzzer built into the LLVM toolchain. It is a highly effective tool for identifying security vulnerabilities and stability issues in C/C++ codebases. This skill provides a comprehensive walkthrough for integrating libFuzzer, including writing effective test harnesses, managing corpora and dictionaries, configuring sanitizers like AddressSanitizer (ASan), and interpreting fuzzing results to improve code robustness.

What it does

Explains how to structure and write LLVMFuzzerTestOneInput harnesses.
Details compilation flags for enabling libFuzzer and sanitizers.
Provides strategies for corpus management and seed input selection.
Covers dictionary creation to accelerate discovery of complex input formats.
Offers guidance on running fuzzing campaigns and interpreting crash reports.
Includes techniques for multi-core execution and coverage analysis.

When to use it

When you need a quick, reliable setup for fuzzing C/C++ libraries.
When your project is compiled with Clang.
When you need to identify memory errors or undefined behavior in your code.
When you want to transition from simple fuzzing to more advanced techniques like AFL++.

Advantages

Seamless integration with the LLVM/Clang toolchain.
Low complexity for initial setup and deployment.
High compatibility with other fuzzing tools like AFL++.
Powerful instrumentation via SanitizerCoverage.
Excellent support for memory error detection through ASan integration.

Usage examples

“How do I compile a C++ file with libFuzzer and AddressSanitizer?”: The agent provides the command: clang++ -fsanitize=fuzzer,address -g -O2 harness.cc target.cc -o fuzz
“What is the best way to handle complex input formats in my fuzzer?”: The agent suggests using FuzzedDataProvider for structured data extraction or libprotobuf-mutator for structure-aware fuzzing.
“How can I speed up my fuzzing campaign?”: The agent recommends using -close_fd_mask=3 to suppress output, setting a reasonable -max_len, and utilizing a dictionary.
“How do I continue fuzzing after a crash is found?”: The agent advises using the flags -fork=1 and -ignore_crashes=1 to keep the campaign running.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/trailofbits/libfuzzer/download
Unzip it into the cross-client skills folder of your project:
```
mkdir -p .agents/skills && unzip libfuzzer.zip -d .agents/skills
```

Documentation by Trail of Bits

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`

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

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

Example Projects

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

Files

ATTRIBUTION.mdAdded by AutoGineer935 B
LICENSELicence file added by AutoGineer19.7 KiB
SKILL.md23.7 KiB
agents/openai.yaml234 B
assets/trail-of-bits-mark.svg3.0 KiB

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     Although not required by our licenses, you are encouraged to
     respect those requests where reasonable. More_considerations
     for the public:
	wiki.creativecommons.org/Considerations_for_licensees

=======================================================================

Creative Commons Attribution-ShareAlike 4.0 International Public
License

By exercising the Licensed Rights (defined below), You accept and agree
to be bound by the terms and conditions of this Creative Commons
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making the Licensed Material available under these terms and
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Section 1 -- Definitions.

  a. Adapted Material means material subject to Copyright and Similar
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     Adapted Material is always produced where the Licensed Material is
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  b. Adapter's License means the license You apply to Your Copyright
     and Similar Rights in Your contributions to Adapted Material in
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  c. BY-SA Compatible License means a license listed at
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  d. Copyright and Similar Rights means copyright and/or similar rights
     closely related to copyright including, without limitation,
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  e. Effective Technological Measures means those measures that, in the
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  f. Exceptions and Limitations means fair use, fair dealing, and/or
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  h. Licensed Material means the artistic or literary work, database,
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  i. Licensed Rights means the rights granted to You subject to the
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  m. You means the individual or entity exercising the Licensed Rights
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Section 2 -- Scope.

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       1. Subject to the terms and conditions of this Public License,
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          exercise the Licensed Rights in the Licensed Material to:

            a. reproduce and Share the Licensed Material, in whole or
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            b. produce, reproduce, and Share Adapted Material.

       2. Exceptions and Limitations. For the avoidance of doubt, where
          Exceptions and Limitations apply to Your use, this Public
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          its terms and conditions.

       3. Term. The term of this Public License is specified in Section
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       4. Media and formats; technical modifications allowed. The
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          technical modifications necessary to circumvent Effective
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          simply making modifications authorized by this Section 2(a)
          (4) never produces Adapted Material.

       5. Downstream recipients.

            a. Offer from the Licensor -- Licensed Material. Every
               recipient of the Licensed Material automatically
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            b. Additional offer from the Licensor -- Adapted Material.
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            c. No downstream restrictions. You may not offer or impose
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  b. Other rights.

       1. Moral rights, such as the right of integrity, are not
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       3. To the extent possible, the Licensor waives any right to
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                ii. a copyright notice;

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                 v. a URI or hyperlink to the Licensed Material to the
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            b. indicate if You modified the Licensed Material and
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            c. indicate the Licensed Material is licensed under this
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       2. You may satisfy the conditions in Section 3(a)(1) in any
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       3. If requested by the Licensor, You must remove any of the
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  b. ShareAlike.

     In addition to the conditions in Section 3(a), if You Share
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       1. The Adapter's License You apply must be a Creative Commons
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       2. You must include the text of, or the URI or hyperlink to, the
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       3. You may not offer or impose any additional or different terms
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Section 4 -- Sui Generis Database Rights.

Where the Licensed Rights include Sui Generis Database Rights that
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  a. for the avoidance of doubt, Section 2(a)(1) grants You the right
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  b. if You include all or a substantial portion of the database
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     including for purposes of Section 3(b); and
  c. You must comply with the conditions in Section 3(a) if You Share
     all or a substantial portion of the contents of the database.

For the avoidance of doubt, this Section 4 supplements and does not
replace Your obligations under this Public License where the Licensed
Rights include other Copyright and Similar Rights.


Section 5 -- Disclaimer of Warranties and Limitation of Liability.

  a. UNLESS OTHERWISE SEPARATELY UNDERTAKEN BY THE LICENSOR, TO THE
     EXTENT POSSIBLE, THE LICENSOR OFFERS THE LICENSED MATERIAL AS-IS
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  b. TO THE EXTENT POSSIBLE, IN NO EVENT WILL THE LICENSOR BE LIABLE
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  c. The disclaimer of warranties and limitation of liability provided
     above shall be interpreted in a manner that, to the extent
     possible, most closely approximates an absolute disclaimer and
     waiver of all liability.


Section 6 -- Term and Termination.

  a. This Public License applies for the term of the Copyright and
     Similar Rights licensed here. However, if You fail to comply with
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  b. Where Your right to use the Licensed Material has terminated under
     Section 6(a), it reinstates:

       1. automatically as of the date the violation is cured, provided
          it is cured within 30 days of Your discovery of the
          violation; or

       2. upon express reinstatement by the Licensor.

     For the avoidance of doubt, this Section 6(b) does not affect any
     right the Licensor may have to seek remedies for Your violations
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  c. For the avoidance of doubt, the Licensor may also offer the
     Licensed Material under separate terms or conditions or stop
     distributing the Licensed Material at any time; however, doing so
     will not terminate this Public License.

  d. Sections 1, 5, 6, 7, and 8 survive termination of this Public
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Section 7 -- Other Terms and Conditions.

  a. The Licensor shall not be bound by any additional or different
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  b. Any arrangements, understandings, or agreements regarding the
     Licensed Material not stated herein are separate from and
     independent of the terms and conditions of this Public License.


Section 8 -- Interpretation.

  a. For the avoidance of doubt, this Public License does not, and
     shall not be interpreted to, reduce, limit, restrict, or impose
     conditions on any use of the Licensed Material that could lawfully
     be made without permission under this Public License.

  b. To the extent possible, if any provision of this Public License is
     deemed unenforceable, it shall be automatically reformed to the
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     without affecting the enforceability of the remaining terms and
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  c. No term or condition of this Public License will be waived and no
     failure to comply consented to unless expressly agreed to by the
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  d. Nothing in this Public License constitutes or may be interpreted
     as a limitation upon, or waiver of, any privileges and immunities
     that apply to the Licensor or You, including from the legal
     processes of any jurisdiction or authority.


=======================================================================

Creative Commons is not a party to its public
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its public licenses to material it publishes and in those instances
will be considered the “Licensor.” The text of the Creative Commons
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Creative Commons may be contacted at creativecommons.org.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs network access, Needs a command-line tool

Security

What our scanner noticed· Low risk

Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by

Trail of Bits

Publisher

Trail of Bits (Official)

Source

trailofbits/skills · plugins/testing-handbook-skills/skills/libfuzzer · commit e4dd0bb

Licence

Creative Commons Attribution-ShareAlike 4.0 International (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

AutoGineer is not affiliated with or endorsed by Trail of Bits or Trail of Bits.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download libfuzzer.zip