487 lines
19 KiB
Markdown
487 lines
19 KiB
Markdown
# DeepState
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[](https://empireslacking.herokuapp.com/)
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[](https://travis-ci.org/trailofbits/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).
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The
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[2018 IEEE Cybersecurity Development Conference](https://secdev.ieee.org/2018/home)
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included a
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[full tutorial](https://github.com/trailofbits/publications/tree/master/workshops/DeepState:%20Bringing%20vulnerability%20detection%20tools%20into%20the%20development%20lifecycle%20-%20SecDev%202018)
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on effective use of DeepState.
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There are two blog posts on using DeepState: [Part 1](https://blog.trailofbits.com/2019/01/22/fuzzing-an-api-with-deepstate-part-1/) and [Part 2](https://blog.trailofbits.com/2019/01/23/fuzzing-an-api-with-deepstate-part-2/).
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## Overview of Features
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* Tests look like Google Test, but can use symbolic execution/fuzzing to generate data (parameterized unit testing)
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* Easier to learn than binary analysis tools/fuzzers, but provides similar functionality
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* Already supports Manticore, Angr, libFuzzer, file-based fuzzing with e.g., AFL; more back-ends likely in future
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* Switch test generation tool without re-writing test harness
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* Work around show-stopper bugs
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* Find out which tool works best for your code under test
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* Different tools find different bugs/vulnerabilities
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* Fair way to benchmark/bakeoff tools
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* Provides test replay for regression plus effective automatic test case reduction to aid debugging
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* Supports API-sequence generation with extensions to Google Test interface
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* Concise readable way (OneOf) to say "run one of these blocks of code"
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* Same construct supports fixed value set non-determinism
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* E.g., writing a POSIX file system tester is pleasant, not painful as in pure Google Test idioms
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* Provides high-level strategies for improving symbolic execution/fuzzing effectiveness
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* Pumping (novel to DeepState) to pick concrete values when symbolic execution is too expensive
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* Automatic decomposition of integer compares to guide coverage-driven fuzzers
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To put it another way, DeepState sits at the intersection of
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*property-based testing*, *traditional unit testing*, *fuzzing*, and
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*symbolic execution*. It lets you perform property-based unit testing
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using fuzzing or symbolic execution as a back end to generate data, and saves the
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results so that what DeepState finds can easily be used in
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deterministic settings such as regression testing or CI.
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## Supported Platforms
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DeepState currently targets Linux, with macOS support in progress
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(the fuzzers work fine, but symbolic execution is not well-supported
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yet, without a painful cross-compilation process).
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## Dependencies
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Build:
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- CMake
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- GCC and G++ with multilib support
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- Python 2.7
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- Setuptools
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Runtime:
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- Python 2.7
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- Z3 (for the Manticore backend)
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## Building on Ubuntu 16.04 (Xenial)
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```shell
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sudo apt update && sudo apt-get install build-essential gcc-multilib g++-multilib cmake python python-setuptools libffi-dev z3
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git clone https://github.com/trailofbits/deepstate deepstate
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mkdir deepstate/build && cd deepstate/build
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cmake ../
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make
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```
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## Installing
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Assuming the DeepState build resides in `$DEEPSTATE`, run the following commands to install the DeepState python package:
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```shell
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virtualenv venv
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. venv/bin/activate
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python $DEEPSTATE/build/setup.py install
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```
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The `virtualenv`-enabled `$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.
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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:
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```shell
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deepstate-angr --num_workers 4 --output_test_dir out $DEEPSTATE/build/examples/IntegerOverflow
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```
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The resulting `out` directory should look something like:
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```
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out
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└── IntegerOverflow.cpp
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├── SignedInteger_AdditionOverflow
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│ ├── a512f8ffb2c1bb775a9779ec60b699cb.fail
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│ └── f1d3ff8443297732862df21dc4e57262.pass
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└── SignedInteger_MultiplicationOverflow
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├── 6a1a90442b4d898cb3fac2800fef5baf.fail
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└── f1d3ff8443297732862df21dc4e57262.pass
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```
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To run these tests, you can just use the native executable, e.g.:
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```shell
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$DEEPSTATE/build/examples/IntegerOverflow --input_test_dir out
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```
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to run all the generated tests, or
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```shell
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$DEEPSTATE/build/examples/IntegerOverflow --input_test_files_dir out/IntegerOverflow.cpp/SignedInteger_AdditionOverflow --input_which_test SignedInteger_AdditionOverflow
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```
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to run the tests in one directory (in this case, you want to specify
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which test to run, also). You can also run a single test, e.g.:
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```shell
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$DEEPSTATE/build/examples/IntegerOverflow --input_test_file out/IntegerOverflow.cpp/SignedInteger_AdditionOverflow/a512f8ffb2c1bb775a9779ec60b699cb.fail--input_which_test SignedInteger_AdditionOverflow
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```
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In the absence of an `--input_which_test` argument, DeepState defaults
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to the last-defined test. Run the native executable with the `--help`
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argument to see all DeepState options.
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If you want to use DeepState in C/C++ code, you will likely want to run `sudo make install` from the `$DEEPSTATE/build` directory as well. The examples mentioned below (file system, databases) assume this has already been done.
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## Usage
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DeepState consists of a static library, used to write test harnesses,
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and command-line _executors_ written in Python. At this time, the best
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documentation is in the [examples](/examples) and in our
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[paper](https://agroce.github.io/bar18.pdf). A more extensive
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example, using DeepState and libFuzzer to test a user-mode file
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system, is available [here](https://github.com/agroce/testfs); in
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particular the
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[Tests.cpp](https://github.com/agroce/testfs/blob/master/Tests.cpp)
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file and CMakeLists.txt show DeepState usage. Another extensive
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example is a [differential tester that compares Google's leveldb and
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Facebook's rocksdb](https://github.com/agroce/testleveldb).
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## Example Code
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```
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#include <deepstate/DeepState.hpp>
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using namespace deepstate;
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/* Simple, buggy, run-length encoding that creates "human readable"
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* encodings by adding 'A'-1 to the count, and splitting at 26.
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* e.g., encode("aaabbbbbc") = "aCbEcA" since C=3 and E=5 */
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char* encode(const char* input) {
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unsigned int len = strlen(input);
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char* encoded = (char*)malloc((len*2)+1);
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int pos = 0;
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if (len > 0) {
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unsigned char last = input[0];
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int count = 1;
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for (int i = 1; i < len; i++) {
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if (((unsigned char)input[i] == last) && (count < 26))
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count++;
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else {
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encoded[pos++] = last;
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encoded[pos++] = 64 + count;
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last = (unsigned char)input[i];
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count = 1;
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}
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}
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encoded[pos++] = last;
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encoded[pos++] = 65; // Should be 64 + count
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}
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encoded[pos] = '\0';
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return encoded;
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}
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char* decode(const char* output) {
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unsigned int len = strlen(output);
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char* decoded = (char*)malloc((len/2)*26);
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int pos = 0;
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for (int i = 0; i < len; i += 2) {
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for (int j = 0; j < (output[i+1] - 64); j++) {
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decoded[pos++] = output[i];
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}
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}
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decoded[pos] = '\0';
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return decoded;
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}
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// Can be (much) higher (e.g., > 1024) if we're using fuzzing, not symbolic execution
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#define MAX_STR_LEN 6
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TEST(Runlength, BoringUnitTest) {
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ASSERT_EQ(strcmp(encode(""), ""), 0);
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ASSERT_EQ(strcmp(encode("a"), "aA"), 0);
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ASSERT_EQ(strcmp(encode("aaabbbbbc"), "aCbEcA"), 0);
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}
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TEST(Runlength, EncodeDecode) {
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char* original = DeepState_CStrUpToLen(MAX_STR_LEN, "abcdef0123456789");
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char* encoded = encode(original);
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ASSERT_LE(strlen(encoded), strlen(original)*2) << "Encoding is > length*2!";
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char* roundtrip = decode(encoded);
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ASSERT_EQ(strncmp(roundtrip, original, MAX_STR_LEN), 0) <<
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"ORIGINAL: '" << original << "', ENCODED: '" << encoded <<
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"', ROUNDTRIP: '" << roundtrip << "'";
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}
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```
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The code above (which can be found
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[here](https://github.com/trailofbits/deepstate/blob/master/examples/Runlen.cpp))
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shows an example of a DeepState test harness. Most of the code is
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just the functions to be tested. Using DeepState to test them requires:
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- Including the DeepState C++ header and using the DeepState namespace
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- Defining at least one TEST, with names
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- Calling some DeepState APIs that produce data
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- In this example, we see the `DeepState_CStrUpToLen` call tells
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DeepState to produce a string that has up to `MAX_STR_LEN`
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characters, chosen from those present in hex strings.
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- Optionally making some assertions about the correctness of the
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results
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- In `Runlen.cpp` this is the `ASSERT_LE` and `ASSERT_EQ` checks.
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- In the absence of any properties to check, DeepState can still
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look for memory safety violations, crashes, and other general
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categories of undesirable behavior, like any fuzzer.
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DeepState will also run the "BoringUnitTest," but it (like a
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traditional hand-written unit test) is simply a test of fixed inputs
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devised by a programmer. These inputs do not expose the bug in
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`encode`. Nor do the default values (all zero bytes) for the DeepState test:
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```
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~/deepstate/build/examples$ ./Runlen
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TRACE: Running: Runlength_EncodeDecode from /Users/alex/deepstate/examples/Runlen.cpp(55)
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TRACE: Passed: Runlength_EncodeDecode
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TRACE: Running: Runlength_BoringUnitTest from /Users/alex/deepstate/examples/Runlen.cpp(49)
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TRACE: Passed: Runlength_BoringUnitTest
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```
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Using DeepState, however, it is easy to find the bug. Just
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go into the `$DEEPSTATE/build/examples` directory and try:
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```shell
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deepstate-angr ./Runlen
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```
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or
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```shell
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./Runlen --fuzz --exit_on_fail
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```
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The fuzzer will output something like:
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```
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INFO: Starting fuzzing
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WARNING: No seed provided; using 1546631311
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WARNING: No test specified, defaulting to last test defined (Runlength_EncodeDecode)
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CRITICAL: /Users/alex/deepstate/examples/Runlen.cpp(60): ORIGINAL: '91c499', ENCODED: '9A1AcA4A9A', ROUNDTRIP: '91c49'
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ERROR: Failed: Runlength_EncodeDecode
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```
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## Log Levels
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By default, DeepState is not very verbose about testing activity,
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other than failing tests. The `--log_level` argument lowers the
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threshold for output, with 0 = `DEBUG`, 1 = `TRACE` (output from the
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tests, including from `printf`), 2 = INFO (DeepState messages, the default), 3 = `WARNING`,
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4 = `ERROR`, 5 = `EXTERNAL` (output from other programs such as
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libFuzzer), and 6 = `CRITICAL` messages. Lowering the `log_level` can be very
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useful for understanding what a DeepState harness is actually doing;
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often, setting `--log_level 1` in either fuzzing or symbolic
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execution will give sufficient information to debug your test harness.
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## Built-In Fuzzer
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Every DeepState executable provides a simple built-in fuzzer that
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generates tests using completely random data. Using this fuzzer is as
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simple as calling the native executable with the `--fuzz` argument.
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The fuzzer also takes a `seed` and `timeout` (default of two minutes)
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to control the fuzzing. By default fuzzing saves
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only failing and crashing tests, and these only when given an output
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directory. If you want to actually save the test cases
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generated, you need to add a `--output_test_dir` argument to tell
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DeepState where to put the generated tests, and if you want the
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(totally random and unlikely to be high-quality) passing tests, you
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need to add `--fuzz_save_passing`.
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Note that while symbolic execution only works on Linux, without a
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fairly complex cross-compilation process, the brute force fuzzer works
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on macOS or (as far as we know) any Unix-like system.
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## A Note on MacOS and Forking
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Normally, when running a test for replay or fuzzing, DeepState forks
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in order to cleanly handle crashes of a test. Unfortunately, `fork()`
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on macOS is _extremely_ slow. When using the built-in fuzzer or
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replaying more than a few tests, it is highly recommended to add the `--no_fork`
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option on macOS, unless you need the added crash handling (that is,
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only when things aren't working without that option).
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## Fuzzing with libFuzzer
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If you install clang 6.0 or later, and run `cmake` when you install
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with the `BUILD_LIBFUZZER` environment variable defined, you can
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generate tests using libFuzzer. Because both DeepState and libFuzzer
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want to be `main`, this requires building a different executable for
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libFuzzer. The `examples` directory shows how this can be done. The
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libFuzzer executable works like any other libFuzzer executable, and
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the tests produced can be replayed using the normal DeepState executable.
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For example, generating some tests of the `OneOf` example (up to 5,000
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runs), then running those tests to examine the results, would look
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like:
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```shell
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mkdir OneOf_libFuzzer_corpus
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./OneOf_LF -runs=5000 OneOf_libFuzzer_corpus
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./OneOf --input_test_files_dir OneOf_libFuzzer_corpus
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```
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Use the `LIBFUZZER_WHICH_TEST`
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environment variable to control which test libFuzzer runs, using a
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fully qualified name (e.g.,
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`Arithmetic_InvertibleMultiplication_CanFail`). By default, you get
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the last test defined (which works fine if there is only one test).
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Obviously, libFuzzer may work better if you provide a non-empty
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corpus, but fuzzing will work even without an initial corpus, unlike AFL.
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One hint when using libFuzzer is to avoid dynamically allocating
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memory during a test, if that memory would not be freed on a test
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failure. This will leak memory and libFuzzer will run out of memory
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very quickly in each fuzzing session. Using libFuzzer on macOS
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requires compiling DeepState and your program with a clang that
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supports libFuzzer (which the Apple built-in probably won't); this can be as simple as doing:
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```shell
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brew install llvm@7
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CC=/usr/local/opt/llvm\@7/bin/clang CXX=/usr/local/opt/llvm\@7/bin/clang++ BUILD_LIBFUZZER=TRUE cmake ..
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make install
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```
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Other ways of getting an appropriate LLVM may also work.
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On macOS, libFuzzer's normal output is not visible. Because libFuzzer
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does not fork to execute tests, there is no issue with fork speed on
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macOS for this kind of fuzzing.
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On any platform,
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you can see more about what DeepState under libFuzzer is doing by
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setting the `LIBFUZZER_LOUD` environment variable, and tell libFuzzer
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to stop upon finding a failing test using `LIBFUZZER_EXIT_ON_FAIL`.
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## Test case reduction
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While tests generated by symbolic execution are likely to be highly
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concise already, fuzzer-generated tests may be much larger than they
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need to be.
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DeepState provides a test case reducer to shrink tests intelligently,
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aware of the structure of a DeepState test. For example, if your
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executable is named `TestFileSystem` and the test you want to reduce
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is named `rmdirfail.test` you would use it like this:
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```shell
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deepstate-reduce ./TestFileSystem rmdirfail.test minrmdirfail.test
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```
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In many cases, this will result in finding a different failure or
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crash that allows smaller test cases, so you can also provide a string
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that controls the criteria for which test outputs are considered valid
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reductions (by default, the reducer looks for any test that fails or
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crashes). Only outputs containing the `--criteria` are considered to
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be valid reductions:
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```shell
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deepstate-reduce ./TestFileSystem rmdirfail.test minrmdirfail.test --criteria "FATAL: /root/testfs/super.c(252)"
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```
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The output will look something like:
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```
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ORIGINAL TEST HAS 119 BYTES
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ONEOF REMOVAL REDUCED TEST TO 103 BYTES
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ONEOF REMOVAL REDUCED TEST TO 87 BYTES
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ONEOF REMOVAL REDUCED TEST TO 67 BYTES
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ONEOF REMOVAL REDUCED TEST TO 51 BYTES
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BYTE RANGE REMOVAL REDUCED TEST TO 50 BYTES
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BYTE RANGE REMOVAL REDUCED TEST TO 49 BYTES
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BYTE REDUCTION: BYTE 3 FROM 4 TO 0
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BYTE REDUCTION: BYTE 43 FROM 4 TO 0
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ONEOF REMOVAL REDUCED TEST TO 33 BYTES
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ONEOF REMOVAL REDUCED TEST TO 17 BYTES
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BYTE REDUCTION: BYTE 7 FROM 2 TO 1
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BYTE REDUCTION: BYTE 15 FROM 2 TO 1
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NO REDUCTIONS FOUND
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PADDING TEST WITH 3 ZEROS
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WRITING REDUCED TEST WITH 20 BYTES TO minrmdirfail.test
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```
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You can use `--which_test <testname>` to specify which test to
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run, as with the `--input_which_test` options to test replay.
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Test case reduction should work on any OS.
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## Fuzzing with AFL
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DeepState can also be used with a file-based fuzzer (e.g. AFL). There
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are a few steps to this. First, compile DeepState itself with any
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needed instrumentation. E.g., to use it with AFL, you will want to
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set the compilers to `afl-gcc` and `afl-g++` or `afl-clang` and
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`afl-clang++` when you `cmake` on your DeepState install:
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```
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CC=afl-clang CXX=afl-clang++ cmake ..
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```
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Alternatively, you can edit the `CMakeLists.txt` file and add:
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```
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SET(CMAKE_C_COMPILER /usr/local/bin/afl-gcc)
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SET(CMAKE_CXX_COMPILER /usr/local/bin/afl-g++)
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```
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Do the same for your DeepState
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test harness and any code it links to you want instrumented. Finally, run the fuzzing via the
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interface to replay test files. For example, to fuzz the `OneOf`
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example, if we were in the `deepstate/build/examples` directory, you
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would do something like:
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```shell
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afl-fuzz -d -i corpus -o afl_OneOf -- ./OneOf --input_test_file @@ --abort_on_fail
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```
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where `corpus` contains at least one file to start fuzzing from. The
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file needs to be smaller than the DeepState input size limit, but has
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few other limitations (for AFL it should also not cause test
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failure). The `abort_on_fail` flag makes DeepState crashes and failed
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tests appear as crashes to the fuzzer.
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|
|
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To replay the tests from AFL:
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|
|
|
```shell
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./OneOf --input_test_files_dir afl_OneOf/crashes
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./OneOf --input_test_files_dir afl_OneOf/queue
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|
```
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|
|
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Finally, if an example has more than one test, you need to specify,
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|
with a fully qualified name (e.g.,
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|
`Arithmetic_InvertibleMultiplication_CanFail`), which test to run,
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|
using the `--input_which_test` flag to the binary. By
|
|
default, DeepState will run the last test defined.
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|
|
|
You can compile with `afl-clang-fast` and `afl-clang-fast++` for
|
|
deferred instrumentation. You'll need code like:
|
|
|
|
```
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|
#ifdef __AFL_HAVE_MANUAL_CONTROL
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|
__AFL_INIT();
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|
#endif
|
|
```
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|
|
|
just before the call to `DeepState_Run()` (which reads the entire
|
|
input file) in your `main`.
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|
|
|
Because AFL and other file-based fuzzers only rely on the DeepState
|
|
native test executable, they should (like DeepState's built-in simple
|
|
fuzzer) work fine on macOS and other Unix-like OSes. On macOS, you
|
|
will want to consider doing the work to use [persistent mode](http://lcamtuf.blogspot.com/2015/06/new-in-afl-persistent-mode.html), or even
|
|
running inside a VM, due to AFL (unless in persistent mode) relying
|
|
extensively on
|
|
forks, which are very slow on macOS.
|
|
|
|
## Contributing
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|
|
|
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.
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|
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## License
|
|
|
|
DeepState is released under [The Apache License 2.0](LICENSE).
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