5ky9uy / jvm-jazzer-fuzz

Coverage-guided, in-process fuzzing for the JVM

Jazzer

Fuzz Testing for the JVM

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Important

Hello Jazzer/Jazzer.js users!

We stopped maintaining Jazzer/Jazzer.js as open source. But we'd be happy to try and understand what you're trying to achieve with it, and help you if we can!

We already added significant new value to our CI Fuzz solution, which includes Jazzer and Jazzer.js. Learn more on how to turbocharge your Java Fuzz Testing with Jazzer Pro.

Visit code-intelligence.com for more information, or get in contact with us via [email protected].

Thanks,

The Code Intelligence team

Jazzer is a coverage-guided, in-process fuzzer for the JVM platform developed by Code Intelligence. It is based on libFuzzer and brings many of its instrumentation-powered mutation features to the JVM.

Jazzer currently supports the following platforms:

• Linux x86_64
• macOS 12+ x86_64 & arm64
• Windows x86_64

Quick start

You can use Docker to try out Jazzer's Autofuzz mode, in which it automatically generates arguments to a given Java function and reports unexpected exceptions and detected security issues:

docker run -it cifuzz/jazzer-autofuzz \
   com.mikesamuel:json-sanitizer:1.2.0 \
   com.google.json.JsonSanitizer::sanitize \
   --autofuzz_ignore=java.lang.ArrayIndexOutOfBoundsException

Here, the first two arguments are the Maven coordinates of the Java library and the fully qualified name of the Java function to be fuzzed in "method reference" form. The optional --autofuzz_ignore flag takes a list of uncaught exception classes to ignore.

After a few seconds, Jazzer should trigger an AssertionError, reproducing a bug it found in this library that has since been fixed.

Using Jazzer via...

JUnit 5

The following steps assume that JUnit 5.9.0 or higher is set up for your project, for example based on the official junit5-samples.

1. Add a dependency on com.code-intelligence:jazzer-junit:<latest version>. All Jazzer Maven artifacts are signed with this key.
2. Add a new fuzz test to a new or existing test class: a method annotated with @FuzzTest and at least one parameter. Using a single parameter of type FuzzedDataProvider, which provides utility functions to produce commonly used Java values, or byte[] is recommended for optimal performance and reproducibility of findings.
3. Assuming your test class is called com.example.MyFuzzTests, create the inputs directory src/test/resources/com/example/MyFuzzTestsInputs.
4. Run a fuzz test with the environment variable JAZZER_FUZZ set to 1 to let the fuzzer rapidly try new sets of arguments. If the fuzzer finds arguments that make your fuzz test fail or even trigger a security issue, it will store them in the inputs directory. In this mode, only a single fuzz test is executed per test run (see #599 for details).
5. Run the fuzz test without JAZZER_FUZZ set to execute it only on the inputs in the inputs directory. This mode, which behaves just like a traditional unit test, ensures that issues previously found by the fuzzer remain fixed and can also be used to debug the fuzz test on individual inputs.

A simple property-based fuzz test could look like this (excluding imports):

class ParserTests {
   @Test
   void unitTest() {
      assertEquals("foobar", SomeScheme.decode(SomeScheme.encode("foobar")));
   }

   @FuzzTest
   void fuzzTest(FuzzedDataProvider data) {
      String input = data.consumeRemainingAsString();
      assertEquals(input, SomeScheme.decode(SomeScheme.encode(input)));
   }
}

A complete Maven example project can be found in examples/junit.

GitHub releases

You can also use GitHub release archives to run a standalone Jazzer binary that starts its own JVM configured for fuzzing:

1. Download and extract the latest release from the GitHub releases page.
2. Add a new class to your project with a public static void fuzzerTestOneInput(FuzzedDataProvider data) method.
3. Compile your fuzz test with jazzer_standalone.jar on the classpath.
4. Run the jazzer binary (jazzer.exe on Windows), specifying the classpath and fuzz test class:

./jazzer --cp=<classpath> --target_class=<fuzz test class>

If you see an error saying that libjvm.so has not been found, make sure that JAVA_HOME points to a JDK.

The examples directory includes both toy and real-world examples of fuzz tests.

Docker

The "distroless" Docker image cifuzz/jazzer includes a recent Jazzer release together with OpenJDK 17. Mount a directory containing your compiled fuzz target into the container under /fuzzing and use it like a GitHub release binary by running:

docker run -v path/containing/the/application:/fuzzing cifuzz/jazzer --cp=<classpath> --target_class=<fuzz test class>

If Jazzer produces a finding, the input that triggered it will be available in the same directory.

Bazel

Support for Jazzer is available in rules_fuzzing, the official Bazel rules for fuzzing. See the README for instructions on how to use Jazzer in a Java Bazel project.

OSS-Fuzz

Code Intelligence and Google have teamed up to bring support for Java, Kotlin, and other JVM-based languages to OSS-Fuzz, Google's project for large-scale fuzzing of open-souce software. Read the OSS-Fuzz guide to learn how to set up a Java project.

Building from source

Information on building and testing Jazzer for development can be found in CONTRIBUTING.md

Further documentation

• Common options and workflows
• Advanced techniques

Findings

A list of security issues and bugs found by Jazzer is maintained here. If you found something interesting and the information is public, please send a PR to add it to the list.

Credit

The following developers have contributed to Jazzer before its public release:

Sergej Dechand, Christian Hartlage, Fabian Meumertzheim, Sebastian Pöplau, Mohammed Qasem, Simon Resch, Henrik Schnor, Khaled Yakdan

The LLVM-style edge coverage instrumentation for JVM bytecode used by Jazzer relies on JaCoCo. Previously, Jazzer used AFL-style coverage instrumentation as pioneered by kelinci.