> [!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.
> You can see more here at [code-intelligence.com](https://code-intelligence.com), or get in contact with us via [sales@code-intelligence.com](mailto:sales@code-intelligence.com)
>
> Thanks,
>
> The Code Intelligence team
Jazzer is a coverage-guided, in-process fuzzer for the JVM platform developed by [Code Intelligence](https://code-intelligence.com).
It is based on [libFuzzer](https://llvm.org/docs/LibFuzzer.html) 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](https://github.com/junit-team/junit5-samples).
1. Add a dependency on `com.code-intelligence:jazzer-junit:`.
All Jazzer Maven artifacts are signed with [this key](deploy/maven.pub).
2. Add a new *fuzz test* to a new or existing test class: a method annotated with [`@FuzzTest`](https://codeintelligencetesting.github.io/jazzer-docs/jazzer-junit/com/code_intelligence/jazzer/junit/FuzzTest.html) and at least one parameter.
Using a single parameter of type [`FuzzedDataProvider`](https://codeintelligencetesting.github.io/jazzer-docs/jazzer-api/com/code_intelligence/jazzer/api/FuzzedDataProvider.html), 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](https://github.com/CodeIntelligenceTesting/jazzer/issues/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):
```java
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`](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](https://github.com/CodeIntelligenceTesting/jazzer/releases).
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:
```shell
./jazzer --cp= --target_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`](examples/src/main/java/com/example) directory includes both toy and real-world examples of fuzz tests.
### Docker
The "distroless" Docker image [cifuzz/jazzer](https://hub.docker.com/r/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:
```sh
docker run -v path/containing/the/application:/fuzzing cifuzz/jazzer --cp= --target_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](https://github.com/bazelbuild/rules_fuzzing), the official Bazel rules for fuzzing.
See [the README](https://github.com/bazelbuild/rules_fuzzing#java-fuzzing) for instructions on how to use Jazzer in a Java Bazel project.
### OSS-Fuzz
[Code Intelligence](https://code-intelligence.com) and Google have teamed up to bring support for Java, Kotlin, and other JVM-based languages to [OSS-Fuzz](https://github.com/google/oss-fuzz), Google's project for large-scale fuzzing of open-souce software.
Read [the OSS-Fuzz guide](https://google.github.io/oss-fuzz/getting-started/new-project-guide/jvm-lang/) 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](CONTRIBUTING.md)
## Further documentation
* [Common options and workflows](docs/common.md)
* [Advanced techniques](docs/advanced.md)
## Findings
A list of security issues and bugs found by Jazzer is maintained [here](docs/findings.md).
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](https://github.com/serj),
[Christian Hartlage](https://github.com/dende),
[Fabian Meumertzheim](https://github.com/fmeum),
[Sebastian Pöplau](https://github.com/sebastianpoeplau),
[Mohammed Qasem](https://github.com/mohqas),
[Simon Resch](https://github.com/simonresch),
[Henrik Schnor](https://github.com/henrikschnor),
[Khaled Yakdan](https://github.com/kyakdan)
The LLVM-style edge coverage instrumentation for JVM bytecode used by Jazzer relies on [JaCoCo](https://github.com/jacoco/jacoco).
Previously, Jazzer used AFL-style coverage instrumentation as pioneered by [kelinci](https://github.com/isstac/kelinci).
[`FuzzedDataProvider`]: https://codeintelligencetesting.github.io/jazzer-docs/jazzer-api/com/code_intelligence/jazzer/api/FuzzedDataProvider.html
