# DeepState

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DeepState is a framework that provides C and C++ developers with a common interface to various symbolic execution and fuzzing engines. Users can write one test harness using a Google Test-like API, then execute it using multiple backends without having to learn the complexities of the underlying engines. It supports writing unit tests and API sequence tests, as well as automatic test generation. Read more about the goals and design of DeepState in our [paper](https://agroce.github.io/bar18.pdf).

The [2018 IEEE Cybersecurity Development Conference](https://secdev.ieee.org/2018/home) will include a full tutorial on effective use of DeepState.

## Overview of Features

* Tests look like Google Test, but can use symbolic execution/fuzzing to generate data (parameterized unit testing)
  * Easier to learn than binary analysis tools/fuzzers, but provides similar functionality
* Already supports Manticore, Angr, Dr. Fuzz; more back-ends likely in future
  * Switch test generation tool without re-writing test harness
    * Work around show-stopper bugs
    * Find out which tool works best for your code under test
    * Different tools find different bugs/vulnerabilities
    * Fair way to benchmark/bakeoff tools
* Supports API-sequence generation with extensions to Google Test interface
  * Concise readable way (OneOf) to say "run one of these blocks of code"
  * Same construct supports fixed value set non-determinism
  * E.g., writing a POSIX file system tester is pleasant, not painful as in pure Google Test idioms
* Provides high-level strategies for improving symbolic execution/fuzzing effectiveness
  * Pumping (novel to DeepState) to pick concrete values when symbolic execution is too expensive
  * Automatic decomposition of integer compares to guide coverage-driven fuzzers

## Supported Platforms

DeepState currently targets Linux, with macOS support in progress.

## Dependencies

Build:

- CMake
- GCC and G++ with multilib support
- Python 2.7
- Setuptools

Runtime:

- Python 2.7
- Z3 (for the Manticore backend)

## Building on Ubuntu 16.04 (Xenial)

```shell
sudo apt update && sudo apt-get install build-essential gcc-multilib g++-multilib cmake python python-setuptools libffi-dev z3
git clone https://github.com/trailofbits/deepstate deepstate
mkdir deepstate/build && cd deepstate/build
cmake ../
make
```

## Installing

Assuming the DeepState build resides in `$DEEPSTATE`, run the following commands to install the DeepState python package:

```shell
virtualenv venv
. venv/bin/activate
python $DEEPSTATE/build/setup.py install
```

The `virtualenv`-enabled `$PATH` should now include two executables: `deepstate` and `deepstate-angr`. These are _executors_, which are used to run DeepState test binaries with specific backends (automatically installed as Python dependencies). The `deepstate` executor uses the Manticore backend while `deepstate-angr` uses angr. They share a common interface where you may specify a number of workers and an output directory for saving backend-generated test cases.

You can check your build using the test binaries that were (by default) built and emitted to `deepstate/build/examples`. For example, to use angr to symbolically execute the `IntegerOverflow` test harness with 4 workers, saving generated test cases in a directory called `out`, you would invoke:

```shell
deepstate-angr --num_workers 4 --output_test_dir out $DEEPSTATE/build/examples/IntegerOverflow
```

 The resulting `out` directory should look something like:

 ```
 out
└── IntegerOverflow.cpp
    ├── SignedInteger_AdditionOverflow
    │   ├── a512f8ffb2c1bb775a9779ec60b699cb.fail
    │   └── f1d3ff8443297732862df21dc4e57262.pass
    └── SignedInteger_MultiplicationOverflow
        ├── 6a1a90442b4d898cb3fac2800fef5baf.fail
        └── f1d3ff8443297732862df21dc4e57262.pass
 ```

## Usage

DeepState consists of a static library, used to write test harnesses, and command-line _executors_ written in Python. At this time, the best documentation is in the [examples](/examples) and in our [paper](https://agroce.github.io/bar18.pdf).

## Contributing

All accepted PRs are awarded bounties by Trail of Bits. Join the #deepstate channel on the [Empire Hacking Slack](https://empireslacking.herokuapp.com/) to discuss ongoing development and claim bounties. Check the [good first issue](https://github.com/trailofbits/deepstate/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) label for suggested contributions.

## License

DeepState is released under [The Apache License 2.0](LICENSE).