Integrating a Java/JVM project

• Jazzer
• Project files
  • project.yaml
  • Dockerfile
  • Fuzzers
  • build.sh
• FuzzedDataProvider

---

The process of integrating a project written in Java or any other language running on the Java Virtual Machine (JVM) with ClusterFuzzLite is very similar to the general Build integration process. The key specifics of integrating a JVM project are outlined below.

Jazzer

Java fuzzing in ClusterFuzzLite depends on Jazzer, which is pre-installed on the base docker images. As Jazzer operates directly on the bytecode level, it can be applied to any project written in a JVM-based language. More information on how Jazzer fuzz targets look like can be found in its README’s Usage section.

Project files

project.yaml

The language attribute must be specified as follows:

language: jvm

The only supported sanitizers are AddressSanitizer (address) and UndefinedBehaviorSanitizer (undefined).

Dockerfile

The Dockerfile should start by FROM gcr.io/oss-fuzz-base/base-builder-jvm

The base Docker images already come with OpenJDK 15 pre-installed. If you need Maven to build your project, you can install it by adding the following line to your Dockerfile:

RUN apt-get update && apt-get install -y maven

Apart from this, you should usually not need to do more than to clone the project, set a WORKDIR, and copy any necessary files, or install any project-specific dependencies here as you normally would.

Fuzzers

In the simplest case, every fuzzer consists of a single Java file with a filename matching *Fuzzer.java and no package directive. An example fuzz target could thus be a file ExampleFuzzer.java with contents:

public class ExampleFuzzer {
    public static void fuzzerTestOneInput(byte[] input) {
        ...
        // Call a function of the project under test with arguments derived from
        // input and throw an exception if something unwanted happens.
        ...
    }
}

build.sh

For JVM projects, build.sh does need some more significant modifications over C/C++ projects. Below is an annotated example build script for a Java-only project with single-file fuzz targets as described above:

# Step 1: Build the project

# Build the project .jar as usual, e.g. using Maven.
mvn package
# In this example, the project is built with Maven, which typically includes the
# project version into the name of the packaged .jar file. The version can be
# obtained as follows:
CURRENT_VERSION=$(mvn org.apache.maven.plugins:maven-help-plugin:3.2.0:evaluate \
-Dexpression=project.version -q -DforceStdout)
# Copy the project .jar into $OUT under a fixed name.
cp "target/sample-project-$CURRENT_VERSION.jar" $OUT/sample-project.jar

# Specify the projects .jar file(s), separated by spaces if there are multiple.
PROJECT_JARS="sample-project.jar"

# Step 2: Build the fuzzers (should not require any changes)

# The classpath at build-time includes the project jars in $OUT as well as the
# Jazzer API.
BUILD_CLASSPATH=$(echo $PROJECT_JARS | xargs printf -- "$OUT/%s:"):$JAZZER_API_PATH

# All .jar and .class files lie in the same directory as the fuzzer at runtime.
RUNTIME_CLASSPATH=$(echo $PROJECT_JARS | xargs printf -- "\$this_dir/%s:"):\$this_dir

for fuzzer in $(find $SRC -name '*Fuzzer.java'); do
  fuzzer_basename=$(basename -s .java $fuzzer)
  javac -cp $BUILD_CLASSPATH $fuzzer
  cp $SRC/$fuzzer_basename.class $OUT/

  # Create an execution wrapper that executes Jazzer with the correct arguments.
  echo "#!/bin/sh
# LLVMFuzzerTestOneInput for fuzzer detection.
this_dir=\$(dirname \"\$0\")
LD_LIBRARY_PATH=\"$JVM_LD_LIBRARY_PATH\":\$this_dir \
\$this_dir/jazzer_driver --agent_path=\$this_dir/jazzer_agent_deploy.jar \
--cp=$RUNTIME_CLASSPATH \
--target_class=$fuzzer_basename \
--jvm_args=\"-Xmx2048m:-Djava.awt.headless=true\" \
\$@" > $OUT/$fuzzer_basename
  chmod +x $OUT/$fuzzer_basename
done

The java-example project contains an example of a build.sh for Java projects with native libraries.

FuzzedDataProvider

Jazzer provides a FuzzedDataProvider that can simplify the task of creating a fuzz target by translating the raw input bytes received from the fuzzer into useful primitive Java types. Its functionality is similar to FuzzedDataProviders available in other languages, such as Python and C++.

The required library is available in the base docker images under the path $JAZZER_API_PATH, which is added to the classpath by the example build script shown above. Locally, the library can be obtained from Maven Central.

A fuzz target using the FuzzedDataProvider would look as follows:

import com.code_intelligence.jazzer.api.FuzzedDataProvider;

public class ExampleFuzzer {
    public static void fuzzerTestOneInput(FuzzedDataProvider data) {
        int number = data.consumeInt();
        String string = data.consumeRemainingAsString();
        // ...
    }
}

For a list of convenience methods offered by FuzzedDataProvider, consult its javadocs.