Pros of OSS-Fuzz

• Broader scope: Supports fuzzing for multiple programming languages and various types of software
• Continuous integration: Integrates easily with CI/CD pipelines for automated fuzzing
• Large-scale infrastructure: Leverages Google's computing resources for extensive fuzzing

Cons of OSS-Fuzz

• Higher complexity: Requires more setup and configuration compared to Syzkaller
• Less specialized: Not as focused on kernel fuzzing as Syzkaller

Code Comparison

Syzkaller (syscall description):

open(file ptr[in, filename], flags flags[open_flags], mode flags[open_mode]) fd

OSS-Fuzz (build script):

#!/usr/bin/python3
import os
import sys
import subprocess

def build_fuzzers(src, work, project_name):
    # Build steps here

Key Differences

• Syzkaller focuses on kernel fuzzing, while OSS-Fuzz is a general-purpose fuzzing platform
• Syzkaller uses a custom description language for syscalls, whereas OSS-Fuzz relies on project-specific build scripts
• OSS-Fuzz supports a wider range of programming languages and integrates with various build systems

Use Cases

• Choose Syzkaller for specialized kernel and driver fuzzing
• Opt for OSS-Fuzz when fuzzing diverse open-source projects across different languages and platforms

Pros of AFLplusplus

• More versatile, supporting a wider range of target programs and platforms
• Offers advanced features like power schedules and custom mutators
• Actively maintained with frequent updates and community contributions

Cons of AFLplusplus

• Steeper learning curve due to numerous configuration options
• May require more manual setup and tuning for optimal performance
• Less specialized for kernel fuzzing compared to Syzkaller

Code Comparison

AFLplusplus example (instrumentation):

#define AFL_LLVM_PASS
#include "config.h"
#include "debug.h"

#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>

#include "llvm/ADT/Statistic.h"
#include "llvm/IR/IRBuilder.h"

Syzkaller example (syscall description):

include <linux/keyctl.h>

resource fd[int32]: 0xffffffffffffffff, AT_FDCWD
resource key[int32]

keyctl$get_keyring_id(id keyring_id, create bool) key
keyctl$join_session_keyring(name ptr[in, string]) key

Both projects are powerful fuzzing tools, but AFLplusplus is more general-purpose, while Syzkaller specializes in kernel fuzzing. AFLplusplus offers more flexibility and features, but Syzkaller provides a more streamlined experience for its specific use case.

Pros of ClusterFuzz

• Supports multiple programming languages and platforms
• Offers a web interface for easier management and result analysis
• Provides scalable distributed fuzzing infrastructure

Cons of ClusterFuzz

• More complex setup and configuration process
• Requires more resources for deployment and maintenance
• Steeper learning curve for new users

Code Comparison

Syzkaller (system call definition):

syz_open_dev = (dev ptr[in, string], id intptr, flags flags[open_flags]) fd

ClusterFuzz (fuzzer configuration):

fuzz_target:
  language: cpp
  engine: libFuzzer
  sanitizer: address

Both projects focus on fuzzing, but Syzkaller specializes in kernel fuzzing, while ClusterFuzz is a more general-purpose fuzzing platform. Syzkaller uses a custom description language for system calls, whereas ClusterFuzz employs configuration files for various fuzzing settings.

ClusterFuzz offers broader language support and a user-friendly interface, making it suitable for diverse projects. However, this versatility comes at the cost of increased complexity and resource requirements. Syzkaller, being more specialized, may be easier to set up for kernel-specific fuzzing tasks but lacks the extensive features and language support of ClusterFuzz.

Pros of Honggfuzz

• Simpler setup and usage, making it more accessible for beginners
• Supports a wider range of targets, including userspace applications
• Offers unique features like hardware-based feedback for ARM

Cons of Honggfuzz

• Less specialized for kernel fuzzing compared to Syzkaller
• May not be as effective for finding complex, multi-step vulnerabilities in kernels
• Lacks some advanced features specific to kernel fuzzing

Code Comparison

Syzkaller (system call definition):

open(file ptr[in, filename], flags flags[open_flags], mode flags[open_mode]) fd

Honggfuzz (example usage):

honggfuzz -f input_corpus/ -w output_corpus/ -- ./target_binary ___FILE___

Both tools use different approaches for defining and executing fuzz targets. Syzkaller focuses on system call definitions for kernel fuzzing, while Honggfuzz uses a more general command-line approach for various target types.

Syzkaller is specifically designed for kernel fuzzing, offering advanced features like coverage-guided syscall generation and kernel-specific sanitizers. Honggfuzz, while versatile, may not provide the same level of specialized kernel fuzzing capabilities but offers broader applicability across different target types.