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Adding a new benchmark

This page explains how to add a new benchmark to FuzzBench and test it.

OSS-Fuzz benchmarks vs Standard benchmarks

FuzzBench supports two methods of integrating benchmarks: OSS-Fuzz and standard. The OSS-Fuzz method makes it easy to integrate a fuzz target from an OSS-Fuzz project as a benchmark. With the “standard” method, instead of using our helper script to copy the project’s and Dockerfile from the OSS-Fuzz repo, you must create these yourself.

OSS-Fuzz benchmarks

You can use most existing OSS-Fuzz projects a benchmark. First decide which project and fuzz target you want to use as a benchmark. Next, find out the commit at which you want to use the project for the benchmark. Finally, find out the date and time (UTC) of that commit in ISO format. You can get the date and time from the project (benchmark) repo with this command:

git --no-pager log -1 $COMMIT_HASH --format=%cd --date=iso-strict

Once you have this information, run benchmarks/ to copy the necessary integration files, like so:

PYTHONPATH=. python3 benchmarks/ -p $PROJECT

Example :

PYTHONPATH=. python3 benchmarks/ -p bloaty
    -f fuzz_target -c f572d396fae9206628714fb2ce00f72e94f2258f -d 2019-10-19T09:07:25+01:00

The script should create the benchmark directory in benchmarks/$PROJECT_$FUZZ_TARGET (unless you specify the name manually) with all the files needed to build the benchmark. You should remove unnecessary files such as fuzz targets which are not used for the benchmark. The *.options files are usually unused, thus it is recommended to remove them along with the commands that copy them to $SRC or $OUT. Further, the file may also need to be modified accordingly, so as to build only the required fuzz target.

Add the files in the benchmark directory to git (and then commit them):

git add benchmarks/$BENCHMARK_NAME/*

Standard benchmarks: Create benchmark files

This process is very similar to adding a project to OSS-Fuzz. Note that this is not the same as integrating an OSS-Fuzz benchmark, since the integration work has already been done in the OSS-Fuzz repo. At a high level it involves:

  1. Creating a directory for your benchmark.
  2. Creating a fuzz target for your benchmark.
  3. Creating a Dockerfile and a to build your benchmark for fuzzing.
  4. Creating a benchmark.yaml file to define important details about your benchmark.

Create benchmark directory

Create a subdirectory under the root benchmarks directory. The name of this subdirectory will be the name FuzzBench uses for the benchmark. The benchmark name can contain alphanumeric characters, dots, hyphens and underscores.

cd benchmarks
export BENCHMARK_NAME=<your_benchmark_name>

Defining a fuzz target

Benchmarks in OSS-Fuzz consist of open source code and a libFuzzer compatible entrypoint into the targeted code that fuzzers such as AFL, libFuzzer and honggfuzz send data to fuzz. This section describes how to create a file that defines this entrypoint. This file should define a LLVMFuzzerTestOneInput function that accepts an array of bytes and the length of this array. This function should then pass those bytes to an API in the project/program that we want to fuzz.

extern "C" int LLVMFuzzerTestOneInput(const uint8_t *Data, size_t Size) {
  DoSomethingInterestingWithMyAPI(Data, Size);
  return 0;  // Non-zero return values are reserved for future use.

For example, if the project we are fuzzing is a JSON parsing library, our LLVMFuzzerTestOneInput could pass the data from the fuzzer to a function in the library that parses JSON.

Example: libxml2.

This file builds the fuzz target for your benchmark. It should use the environment variables CC, CXX, CFLAGS, CXXFLAGS $OUT and the fuzzer library. FUZZER_LIB (explanation) for this. These environment variables will be defined when runs By linking your fuzz target with the FUZZER_LIB and the project under test, you will produce a binary that can be fuzzed by the FuzzBench fuzzers. This is called the fuzz target binary. FUZZER_LIB is specific to each fuzzer, its primary purpose is taking data from the fuzzer and passing it to your benchmark’s LLVMFuzzerTestOneInput function.

Once the build is finished, copy the fuzz target binary, any library dependencies (and optionally the seeds directory and the dictionary) into the output directory ($OUT). NOTE: Only build artifacts added in $OUT directory are available when running the fuzzer. You should not have any dependencies outside of $OUT.

#!/bin/bash -ex

# Build project.
./ && ./configure && make -j

# Build fuzz target in $OUT directory.
export FUZZ_TARGET=fuzz_target
    -I BUILD/path/to/include/dir BUILD/path/to/project-lib.a \

# Optional: Copy seeds directory to $OUT directory.
cp -r seeds $OUT/

# Optional: Copy dictionary to $OUT directory.
cp $FUZZ_TARGET.dict $OUT/

Example: libxml2.

seeds directory (optional)

This directory should contain a set of test input files for the fuzz target that provide good code coverage to start from. This should be copied to $OUT/seeds

Example: libpng-1.2.56.

Dictionary file (optional)

In the $OUT directory, you can define a file that will be used by fuzzers as a dictionary. This file have the same name as the fuzz target binary followed by a .dict file extension. For example if your fuzz target binary is $OUT/fuzz-target the dictionary should be $OUT/fuzz-target.dict.


This file defines the steps to build the docker image for your benchmark. It should inherit from and do any one-time setup needed to build your benchmark, but should not actually build the benchmark itself. It also should copy any files from the benchmark directory into the image that will be needed to build the benchmark.


RUN apt-get update && \
    apt-get install -y \
    make \

COPY fuzz-target.dict $SRC/
ADD seeds $SRC/seeds

Example: libxml2.


Define the name of your fuzz target binary and the project that is fuzzed as part of the benchmark like so:

fuzz_target: fuzz-target
project: $PROJECT_NAME

Example: libxml2.

Testing it out

Once you integrated a benchmark, you should test that it builds and runs successfully with at least one fuzzer (e.g. afl):

export FUZZER_NAME=afl
export BENCHMARK_NAME=libpng-1.2.56


# This command will fuzz forever. Press Ctrl-C to stop it.

Submitting the benchmark in a pull request

  • Add your benchmark to the list in .github/workflows/benchmarks.yml so that our continuous integration will test that your fuzzer can build and briefly run on all benchmarks once you’ve submitted a pull request.

  • Submit the integration in a GitHub pull request. If everything works, submit the integration in a GitHub pull request.

Overview of how builds work in FuzzBench

We don’t think most end users need to know how this process works. But we describe it anyway for edge cases where this knowledge may help. Note that this process may change as it is fairly complex since it needs to ensure that the resulting docker images can run FuzzBench, build arbitrary fuzzers and build arbitrary benchmarks for their use, while trying to hide some implementation details from fuzzers and benchmarks.

Building benchmarks and fuzzers.

Building benchmarks and fuzzers entails the following process:

  1. The benchmark image is built. This image is defined by benchmarks/$BENCHMARK/Dockerfile. It inherits from which provides clang and other things needed by benchmarks (particular OSS-Fuzz benchmarks to build). Standard benchmarks (usually) inherit from the latest version of base-builder while OSS-Fuzz benchmarks (usually) inherit from the specific version of base-builder that was used to build the version of the project’s source (commit) that the benchmark uses. This is to ensure that builds of these benchmarks just work and don’t break when base-builder is updated to use a new version of clang. Note that pinning some benchmarks to specific versions of clang is a bit ugly and this behavior may change in the future.

  2. The fuzzer builder image is built. This image is defined by fuzzers/$FUZZER/builder.Dockerfile. This dockerfile will inherit from a parent image that is provided to it at buildtime (using the docker variable: parent_image). The parent image provided is the benchmark docker image from the previous step. The fuzzer builder image builds the fuzzer sets up anything the fuzzer needs to build the benchmark (such as FUZZER_LIB).

  3. The benchmark builder image is built. This image is defined by docker/benchmark-builder/Dockerfile. This inherits from the fuzzer builder image. This is the first image in this build process that is defined by the main FuzzBench code (e.g. not fuzzers, benchmarks, or OSS-Fuzz). Its first function is to copy the FuzzBench code and install packages needed to run FuzzBench like Python3.10. For benchmarks that define a commit in their benchmark.yaml (i.e. OSS-Fuzz benchmarks) the build process for this image checks out the source code of that project at the specified commit. Then the process defines the environment variables CC, CXX, CXXFLAGS, CFLAGS and OUT. It then calls the build function from the fuzzer’s file. build can change these environment variables as needed and then calls build_benchmark from fuzzers/ build_benchmark invokes the file of the benchmark building it with environment variables provided by or the benchmark builder image. build then copies build of the fuzzer (e.g. afl-fuzz) to $OUT (one reason why we do this here instead of when building the fuzzer is because the can overwrite it, in the future we will probably ensure that the build processes for the benchmark and the fuzzer don’t interfere). In some cases, such as QSYM (which is no longer a supported fuzzer for other reasons), build can reset OUT so that it can build the benchmark twice since some fuzzers may need two different builds of the same benchmark.

  4. Runners: TODO