harness-writing

# Writing Fuzzing Harnesses

A fuzzing harness is the entrypoint function that receives random data from the fuzzer and routes it to your system under test (SUT). The quality of your harness directly determines which code paths get exercised and whether critical bugs are found. A poorly written harness can miss entire subsystems or produce non-reproducible crashes.

## Overview

The harness is the bridge between the fuzzer's random byte generation and your application's API. It must parse raw bytes into meaningful inputs, call target functions, and handle edge cases gracefully. The most important part of any fuzzing setup is the harness—if written poorly, critical parts of your application may not be covered.

### Key Concepts

| Concept | Description |
|---------|-------------|
| **Harness** | Function that receives fuzzer input and calls target code under test |
| **SUT** | System Under Test—the code being fuzzed |
| **Entry point** | Function signature required by the fuzzer (e.g., `LLVMFuzzerTestOneInput`) |
| **FuzzedDataProvider** | Helper class for structured extraction of typed data from raw bytes |
| **Determinism** | Property that ensures same input always produces same behavior |
| **Interleaved fuzzing** | Single harness that exercises multiple operations based on input |

## When to Apply

**Apply this technique when:**
- Creating a new fuzz target for the first time
- Fuzz campaign has low code coverage or isn't finding bugs
- Crashes found during fuzzing are not reproducible
- Target API requires complex or structured inputs
- Multiple related functions should be tested together

**Skip this technique when:**
- Using existing well-tested harnesses from your project
- Tool provides automatic harness generation that meets your needs
- Target already has comprehensive fuzzing infrastructure

## Quick Reference

| Task | Pattern |
|------|---------|
| Minimal C++ harness | `extern "C" int LLVMFuzzerTestOneInput(const uint8_t* data, size_t size)` |
| Minimal Rust harness | `fuzz_target!(|data: &[u8]| { ... })` |
| Size validation | `if (size < MIN_SIZE) return 0;` |
| Cast to integers | `uint32_t val = *(uint32_t*)(data);` |
| Use FuzzedDataProvider | `FuzzedDataProvider fuzzed_data(data, size);` |
| Extract typed data (C++) | `auto val = fuzzed_data.ConsumeIntegral<uint32_t>();` |
| Extract string (C++) | `auto str = fuzzed_data.ConsumeBytesWithTerminator<char>(32, 0xFF);` |

## Step-by-Step

### Step 1: Identify Entry Points

Find functions in your codebase that:
- Accept external input (parsers, validators, protocol handlers)
- Parse complex data formats (JSON, XML, binary protocols)
- Perform security-critical operations (authentication, cryptography)
- Have high cyclomatic complexity or many branches

Good targets are typically:
- Protocol parsers
- File format parsers
- Serialization/deserialization functions
- Input validation routines

### Step 2: Write Minimal Harness

Start with the simplest possible harness that calls your target function:

**C/C++:**
```cpp
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    target_function(data, size);
    return 0;
}
```

**Rust:**
```rust
#![no_main]
use libfuzzer_sys::fuzz_target;

fuzz_target!(|data: &[u8]| {
    target_function(data);
});
```

### Step 3: Add Input Validation

Reject inputs that are too small or too large to be meaningful:

```cpp
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    // Ensure minimum size for meaningful input
    if (size < MIN_INPUT_SIZE || size > MAX_INPUT_SIZE) {
        return 0;
    }
    target_function(data, size);
    return 0;
}
```

**Rationale:** The fuzzer generates random inputs of all sizes. Your harness must handle empty, tiny, huge, or malformed inputs without causing unexpected issues in the harness itself (crashes in the SUT are fine—that's what we're looking for).

### Step 4: Structure the Input

For APIs that require typed data (integers, strings, etc.), use casting or helpers like `FuzzedDataProvider`:

**Simple casting:**
```cpp
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;
}
```

**Using FuzzedDataProvider:**
```cpp
#include "FuzzedDataProvider.h"

extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    FuzzedDataProvider fuzzed_data(data, size);

    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);

    concat(&str1[0], str1.size(), &str2[0], str2.size(), allocation_size);
    return 0;
}
```

### Step 5: Test and Iterate

Run the fuzzer and monitor:
- Code coverage (are all interesting paths reached?)
- Executions per second (is it fast enough?)
- Crash reproducibility (can you reproduce crashes with saved inputs?)

Iterate on the harness to improve these metrics.

## Common Patterns

### Pattern: Beyond Byte Arrays—Casting to Integers

**Use Case:** When target expects primitive types like integers or floats

**Implementation:**
```cpp
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    // Ensure exactly 2 4-byte numbers
    if (size != 2 * sizeof(uint32_t)) {
        return 0;
    }

    // Split input into two integers
    uint32_t numerator = *(uint32_t*)(data);
    uint32_t denominator = *(uint32_t*)(data + sizeof(uint32_t));

    divide(numerator, denominator);
    return 0;
}
```

**Rust equivalent:**
```rust
fuzz_target!(|data: &[u8]| {
    if data.len() != 2 * std::mem::size_of::<i32>() {
        return;
    }

    let numerator = i32::from_ne_bytes([data[0], data[1], data[2], data[3]]);
    let denominator = i32::from_ne_bytes([data[4], data[5], data[6], data[7]]);

    divide(numerator, denominator);
});
```

**Why it works:** Any 8-byte input is valid. The fuzzer learns that inputs must be exactly 8 bytes, and every bit flip produces a new, potentially interesting input.

### Pattern: FuzzedDataProvider for Complex Inputs

**Use Case:** When target requires multiple strings, integers, or variable-length data

**Implementation:**
```cpp
#include "FuzzedDataProvider.h"

extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    FuzzedDataProvider fuzzed_data(data, size);

    // Extract different types of data
    size_t allocation_size = fuzzed_data.ConsumeIntegral<size_t>();

    // Consume variable-length strings with terminator
    std::vector<char> str1 = fuzzed_data.ConsumeBytesWithTerminator<char>(32, 0xFF);
    std::vector<char> str2 = fuzzed_data.ConsumeBytesWithTerminator<char>(32, 0xFF);

    char* result = concat(&str1[0], str1.size(), &str2[0], str2.size(), allocation_size);
    if (result != NULL) {
        free(result);
    }

    return 0;
}
```

**Why it helps:** `FuzzedDataProvider` handles the complexity of extracting structured data from a byte stream. It's particularly useful for APIs that need multiple parameters of different types.

### Pattern: Interleaved Fuzzing

**Use Case:** When multiple related operations should be tested in a single harness

**Implementation:**
```cpp
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    if (size < 1 + 2 * sizeof(int32_t)) {
        return 0;
    }

    // First byte selects operation
    uint8_t mode = data[0];

    // Next bytes are operands
    int32_t numbers[2];
    memcpy(numbers, data + 1, 2 * sizeof(int32_t));

    int32_t result = 0;
    switch (mode % 4) {
        case 0:
            result = add(numbers[0], numbers[1]);
            break;
        case 1:
            result = subtract(numbers[0], numbers[1]);
            break;
        case 2:
            result = multiply(numbers[0], numbers[1]);
            break;
        case 3:
            result = divide(numbers[0], numbers[1]);
            break;
    }

    // Prevent compiler from optimizing away the calls
    printf("%d", result);
    return 0;
}
```

**Advantages:**
- Faster to write one harness than multiple individual harnesses
- Single shared corpus means interesting inputs for one operation may be interesting for others
- Can discover bugs in interactions between operations

**When to use:**
- Operations share similar input types
- Operations are logically related (e.g., arithmetic operations, CRUD operations)
- Single corpus makes sense across all operations

### Pattern: Structure-Aware Fuzzing with Arbitrary (Rust)

**Use Case:** When fuzzing Rust code that uses custom structs

**Implementation:**
```rust
use arbitrary::Arbitrary;

#[derive(Debug, Arbitrary)]
pub struct Name {
    data: String
}

impl Name {
    pub fn check_buf(&self) {
        let data = self.data.as_bytes();
        if data.len() > 0 && data[0] == b'a' {
            if data.len() > 1 && data[1] == b'b' {
                if data.len() > 2 && data[2] == b'c' {
                    process::abort();
                }
            }
        }
    }
}
```

**Harness with arbitrary:**
```rust
#![no_main]
use libfuzzer_sys::fuzz_target;

fuzz_target!(|data: your_project::Name| {
    data.check_buf();
});
```

**Add to Cargo.toml:**
```toml
[dependencies]
arbitrary = { version = "1", features = ["derive"] }
```

**Why it helps:** The `arbitrary` crate automatically handles deserialization of raw bytes into your Rust structs, reducing boilerplate and ensuring valid struct construction.

**Limitation:** The arbitrary crate doesn't offer reverse serialization, so you can't manually construct byte arrays that map to specific structs. This works best when starting from an empty corpus (fine for libFuzzer, problematic for AFL++).

## Advanced Usage

### Tips and Tricks

| Tip | Why It Helps |
|-----|--------------|
| **Start with parsers** | High bug density, clear entry points, easy to harness |
| **Mock I/O operations** | Prevents hangs from blocking I/O, enables determinism |
| **Use FuzzedDataProvider** | Simplifies extraction of structured data from raw bytes |
| **Reset global state** | Ensures each iteration is independent and reproducible |
| **Free resources in harness** | Prevents memory exhaustion during long campaigns |
| **Avoid logging in harness** | Logging is slow—fuzzing needs 100s-1000s exec/sec |
| **Test harness manually first** | Run harness with known inputs before starting campaign |
| **Check coverage early** | Ensure harness reaches expected code paths |

### Structure-Aware Fuzzing with Protocol Buffers

For highly structured input formats, consider using Protocol Buffers as an intermediate format with custom mutators:

```cpp
// Define your input format in .proto file
// Use libprotobuf-mutator to generate valid mutations
// This ensures fuzzer mutates message contents, not the protobuf encoding itself
```

This approach is more setup but prevents the fuzzer from wasting time on unparseable inputs. See [structure-aware fuzzing documentation](https://github.com/google/fuzzing/blob/master/docs/structure-aware-fuzzing.md) for details.

### Handling Non-Determinism

**Problem:** Random values or timing dependencies cause non-reproducible crashes.

**Solutions:**
- Replace `rand()` with deterministic PRNG seeded from fuzzer input:
  ```cpp
  uint32_t seed = fuzzed_data.ConsumeIntegral<uint32_t>();
  srand(seed);
  ```
- Mock system calls that return time, PIDs, or random data
- Avoid reading from `/dev/random` or `/dev/urandom`

### Resetting Global State

If your SUT uses global state (singletons, static variables), reset it between iterations:

```cpp
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    // Reset global state before each iteration
    global_reset();

    target_function(data, size);

    // Clean up resources
    global_cleanup();
    return 0;
}
```

**Rationale:** Global state can cause crashes after N iterations rather than on a specific input, making bugs non-reproducible.

## Practical Harness Rules

Follow these rules to ensure effective fuzzing harnesses:

| Rule | Rationale |
|------|-----------|
| **Handle all input sizes** | Fuzzer generates empty, tiny, huge inputs—harness must handle gracefully |
| **Never call `exit()`** | Calling `exit()` stops the fuzzer process. Use `abort()` in SUT if needed |
| **Join all threads** | Each iteration must run to completion before next iteration starts |
| **Be fast** | Aim for 100s-1000s executions/sec. Avoid logging, high complexity, excess memory |
| **Maintain determinism** | Same input must always produce same behavior for reproducibility |
| **Avoid global state** | Global state reduces reproducibility—reset between iterations if unavoidable |
| **Use narrow targets** | Don't fuzz PNG and TCP in same harness—different formats need separate targets |
| **Free resources** | Prevent memory leaks that cause resource exhaustion during long campaigns |

**Note:** These guidelines apply not just to harness code, but to the entire SUT. If the SUT violates these rules, consider patching it (see the fuzzing obstacles technique).

## Anti-Patterns

| Anti-Pattern | Problem | Correct Approach |
|--------------|---------|------------------|
| **Global state without reset** | Non-deterministic crashes | Reset all globals at start of harness |
| **Blocking I/O or network calls** | Hangs fuzzer, wastes time | Mock I/O, use in-memory buffers |
| **Memory leaks in harness** | Resource exhaustion kills campaign | Free all allocations before returning |
| **Calling `exit()` in SUT** | Stops entire fuzzing process | Use `abort()` or return error codes |
| **Heavy logging in harness** | Reduces exec/sec by orders of magnitude | Disable logging during fuzzing |
| **Too many operations per iteration** | Slows down fuzzer | Keep iterations fast and focused |
| **Mixing unrelated input formats** | Corpus entries not useful across formats | Separate harnesses for different formats |
| **Not validating input size** | Harness crashes on edge cases | Check `size` before accessing `data` |

## Tool-Specific Guidance

### libFuzzer

**Harness signature:**
```cpp
extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    // Your code here
    return 0;  // Non-zero return is reserved for future use
}
```

**Compilation:**
```bash
clang++ -fsanitize=fuzzer,address -g harness.cc -o fuzz_target
```

**Integration tips:**
- Use `FuzzedDataProvider.h` for structured input extraction
- Compile with `-fsanitize=fuzzer` to link the fuzzing runtime
- Add sanitizers (`-fsanitize=address,undefined`) to detect more bugs
- Use `-g` for better stack traces when crashes occur
- libFuzzer can start with empty corpus—no seed inputs required

**Running:**
```bash
./fuzz_target corpus_dir/
```

**Resources:**
- [FuzzedDataProvider header](https://github.com/llvm/llvm-project/blob/main/compiler-rt/include/fuzzer/FuzzedDataProvider.h)
- [libFuzzer documentation](https://llvm.org/docs/LibFuzzer.html)

### AFL++

AFL++ supports multiple harness styles. For best performance, use persistent mode:

**Persistent mode harness:**
```cpp
#include <unistd.h>

int main(int argc, char **argv) {
    #ifdef __AFL_HAVE_MANUAL_CONTROL
        __AFL_INIT();
    #endif

    unsigned char buf[MAX_SIZE];

    while (__AFL_LOOP(10000)) {
        // Read input from stdin
        ssize_t len = read(0, buf, sizeof(buf));
        if (len <= 0) break;

        // Call target function
        target_function(buf, len);
    }

    return 0;
}
```

**Compilation:**
```bash
afl-clang-fast++ -g harness.cc -o fuzz_target
```

**Integration tips:**
- Use persistent mode (`__AFL_LOOP`) for 10-100x speedup
- Consider deferred initialization (`__AFL_INIT()`) to skip setup overhead
- AFL++ requires at least one seed input in the corpus directory
- Use `AFL_USE_ASAN=1` or `AFL_USE_UBSAN=1` for sanitizer builds

**Running:**
```bash
afl-fuzz -i seeds/ -o findings/ -- ./fuzz_target
```

### cargo-fuzz (Rust)

**Harness signature:**
```rust
#![no_main]
use libfuzzer_sys::fuzz_target;

fuzz_target!(|data: &[u8]| {
    // Your code here
});
```

**With structured input (arbitrary crate):**
```rust
#![no_main]
use libfuzzer_sys::fuzz_target;

fuzz_target!(|data: YourStruct| {
    data.check();
});
```

**Creating harness:**
```bash
cargo fuzz init
cargo fuzz add my_target
```

**Integration tips:**
- Use `arbitrary` crate for automatic struct deserialization
- cargo-fuzz wraps libFuzzer, so all libFuzzer features work
- Compile with sanitizers automatically via cargo-fuzz
- Harnesses go in `fuzz/fuzz_targets/` directory

**Running:**
```bash
cargo +nightly fuzz run my_target
```

**Resources:**
- [cargo-fuzz documentation](https://rust-fuzz.github.io/book/cargo-fuzz.html)
- [arbitrary crate](https://github.com/rust-fuzz/arbitrary)

### go-fuzz

**Harness signature:**
```go
// +build gofuzz

package mypackage

func Fuzz(data []byte) int {
    // Call target function
    target(data)

    // Return codes:
    // -1 if input is invalid
    //  0 if input is valid but not interesting
    //  1 if input is interesting (e.g., added new coverage)
    return 0
}
```

**Building:**
```bash
go-fuzz-build
```

**Integration tips:**
- Return 1 for inputs that add coverage (optional—fuzzer can detect automatically)
- Return -1 for invalid inputs to deprioritize similar mutations
- go-fuzz handles persistence automatically

**Running:**
```bash
go-fuzz -bin=./mypackage-fuzz.zip -workdir=fuzz
```

## Troubleshooting

| Issue | Cause | Solution |
|-------|-------|----------|
| **Low executions/sec** | Harness is too slow (logging, I/O, complexity) | Profile harness, remove bottlenecks, mock I/O |
| **No crashes found** | Coverage not reaching buggy code | Check coverage, improve harness to reach more paths |
| **Non-reproducible crashes** | Non-determinism or global state | Remove randomness, reset globals between iterations |
| **Fuzzer exits immediately** | Harness calls `exit()` | Replace `exit()` with `abort()` or return error |
| **Out of memory errors** | Memory leaks in harness or SUT | Free allocations, use leak sanitizer to find leaks |
| **Crashes on empty input** | Harness doesn't validate size | Add `if (size < MIN_SIZE) return 0;` |
| **Corpus not growing** | Inputs too constrained or format too strict | Use FuzzedDataProvider or structure-aware fuzzing |

## Related Skills

### Tools That Use This Technique

| Skill | How It Applies |
|-------|----------------|
| **libfuzzer** | Uses `LLVMFuzzerTestOneInput` harness signature with FuzzedDataProvider |
| **aflpp** | Supports persistent mode harnesses with `__AFL_LOOP` for performance |
| **cargo-fuzz** | Uses Rust-specific `fuzz_target!` macro with arbitrary crate integration |
| **atheris** | Python harness takes bytes, calls Python functions |
| **ossfuzz** | Requires harnesses in specific directory structure for cloud fuzzing |

### Related Techniques

| Skill | Relationship |
|-------|--------------|
| **coverage-analysis** | Measure harness effectiveness—are you reaching target code? |
| **address-sanitizer** | Detects bugs found by harness (buffer overflows, use-after-free) |
| **fuzzing-dictionary** | Provide tokens to help fuzzer pass format checks in harness |
| **fuzzing-obstacles** | Patch SUT when it violates harness rules (exit, non-determinism) |

## Resources

### Key External Resources

**[Split Inputs in libFuzzer - Google Fuzzing Docs](https://github.com/google/fuzzing/blob/master/docs/split-inputs.md)**
Explains techniques for handling multiple input parameters in a single fuzzing harness, including use of magic separators and FuzzedDataProvider.

**[Structure-Aware Fuzzing with Protocol Buffers](https://github.com/google/fuzzing/blob/master/docs/structure-aware-fuzzing.md)**
Advanced technique using protobuf as intermediate format with custom mutators to ensure fuzzer mutates message contents rather than format encoding.

**[libFuzzer Documentation](https://llvm.org/docs/LibFuzzer.html)**
Official LLVM documentation covering harness requirements, best practices, and advanced features.

**[cargo-fuzz Book](https://rust-fuzz.github.io/book/cargo-fuzz.html)**
Comprehensive guide to writing Rust fuzzing harnesses with cargo-fuzz and the arbitrary crate.

### Video Resources

- [Effective File Format Fuzzing](https://www.youtube.com/watch?v=qTTwqFRD1H8) - Conference talk on writing harnesses for file format parsers
- [Modern Fuzzing of C/C++ Projects](https://www.youtube.com/watch?v=x0FQkAPokfE) - Tutorial covering harness design patterns