An evolutionary knowledge-based fuzzer

Introduction

Chromosome
In the directory chromosome/parsers you can find the file PNG.py . This Python module describes the PNG file format to the fuzzer. You may add your custom modules for other file formats in this directory.
The fundamental idea behind the Chromosome subsystem is to convert the initial seed files using a Deserializer into a tree of Genes . At some point, the (fuzzed) Genes will be written into a file, using a Serializer .
Consider that in Choronzon the aim of the parser module is to provide the elementary structure of the file format, instead of every minor detail. This will help the fuzzer to construct files that are mostly sane, avoiding early exiting from the target application. Additionally, this approach saves time, because describing every aspect of the file format is time consuming and introduces significant development overhead.

How to write a custom parser
A new parser module must import:

• chromosome.gene.AbstractGene
• chromosome.serializer.BaseSerializer
• chromosome.deserializer.BaseDeserializer

and it must implement

• a Gene class derived from chromosome.gene.AbstractGene ,
• a Serializer class derived from chromosome.serializer.BaseSerializer ,
• and a Deserializer class derived from chromosome.deserializer.BaseDeserializer .

In the example shipped with Choronzon , each PNGGene corresponds to a PNG chunk. Generally, you may think of a Gene as an elementary data structure of the target format. Each Chromosome is comprised from a tree of Genes , and represents a unique file. Each Gene must be able to produce a byte string that contains its data combined with the data of the lower Genes in the tree.
The PNGSerializer must be able to produce (a mostly sane) file from when a list of Genes is given to it. On the other hand, PNGDeserializer must be a able to parse a valid file of the target format and deserialize it to a tree of Genes .
Check chromosome/parsers/PNG.py for a commented example for the PNG format.

Tracer
The Tracer module is used to disassemble the target application (and/or one or more of its libraries). In this version of Choronzon this is achieved with IDA. We used this approach because we can correlate any interesting information from the fuzzing campaign with our IDBs. However, we may drop the dependency on IDA in the near future in order to make Choronzon more portable and accessible.
A file is tested against an application with the help of a Pin utility. In the analyzer/coverage directory there's the source code of this Pin tool, which injects hooks in the beginning of each basic block at the target application. When the execution is finished, we correlate the basic block that was hit, with the basic block from the binary. Thus, we're able to calculate metrics that are valuable for us (coverage etc).

Fuzzer
The Fuzzer component is using the Chromosome representation to fuzz a file. As mentioned earlier, there are two fuzzing methods in Choronzon .
For the first method, Choronzon gets the content from one or more genes and applies one of the Mutators . Mutators implement common but effective fuzzing methods like random byte mutation, high bit set, byte swapping and many more. You may also write your own custom mutators and add them in fuzzers/mutators.py .
The second fuzzing method is called recombination. Recombinators are used to change the structure of the file. Here's an example with the PNG format.
PNG files are comprised by consecutive chunks that contain four fields,

• length,
• chunk's type,
• chunk's data,
• and a CRC.

Let's assume we have a PNG file that only has IHDR, IDAT and IEND chunks. Its structure would look like the following:

[ PNG signature ] [ IHDR ] [ IDAT ] [ IEND ]

Since Choronzon is aware of the basic structures (i.e the PNG chunks), it is able to alter their sequence. After a successful recombination the fuzzed PNG output file can look like this:

[ PNG signature ] [ IDAT ] [ IHDR ] [ IEND ]

Choronzon contains many more recombination strategies that make it able to cope even with complicated file formats.

Installation
Choronzon has been tested with Python 2.7, Pin 3, IDA Pro 6.6 to 6.9, on Ubuntu 16.04 LTS (Linux kernel 4.4) and Windows 10.
In order to run it you'll need to install the sortedcontainers Python package. You may find it here or install it via pip.
Moreover, Choronzon needs IDA Pro (actually, its terminal version). The path of IDA Pro should be specified in your configuration file like this:

DisassemblerPath = 'C:\\Program Files (x86)\\IDA 6.6'

It has been tested successfully with IDA Pro 6.6, 6.7, 6.8 and 6.9.
Choronzon's coverage Pin tool is located at analyzer/coverage and must be compiled. You may want to check Pin's documentation for details, or you can perform the following steps:

1. Copy the coverage.cpp and makefile.rules file to /path/to/pin/source/tools/MyPinTool
2. Run make . If you're on Windows you should run the Visual Studio command line, and use the make utility and its dependencies from Cygwin
3. Copy back to /path/to/choronzon/analysis/coverage the newly created obj-intel64 directory (or obj-ia32 for 32 bit systems)

Configuration
In order to fuzz with Choronzon , you must provide a configuration file. In the settings directory there is an example of Choronzon's configuration.