This repository contains Rekall with additions made to support Windows 10 memory compression. The system should automatically detect whether the kernel in the snapshot used memory compression. If the compression version is supported, we will automatically load an address space that supports decompression. All of this should be invisible to the user.

• Python
• Download/clone this repository (https://github.com/fireeye/win10_rekall)

To install, see the Quick Start.

To verify an address space supporting Windows 10 memory compression is loaded, first run the 'modules' plugin. After it finishes, execute the command "print(session)". The result should contain a "Cache" section indicating the "default_address_space". This should report one of the following values:

• WindowsIA32CompressedPagedMemoryPae
• WindowsAMD64CompressedPagedMemory

The decompression algorithms also rely on the value of the Virtual Store page file number. On default Windows 10 configurations this value is two. We parse the MiState (_MI_SYSTEM_INFORMATION) structure to parse the array of page files. If we are unsuccessful, we fall back on using the default value of two. You may override the default value by supplying a different value via the command line option:

--vspagefilenumber=<virtual_store_page_file_number>

The Rekall Framework is a completely open collection of tools, implemented in Python under the Apache and GNU General Public License, for the extraction and analysis of digital artifacts computer systems.

The Rekall distribution is available from: http://www.rekall-forensic.com/

Rekall should run on any platform that supports Python

Rekall supports investigations of the following 32bit and 64bit memory images:

• Microsoft Windows XP Service Pack 2 and 3
• Microsoft Windows 7 Service Pack 0 and 1
• Microsoft Windows 8 and 8.1
• Microsoft Windows 10
• Linux Kernels 2.6.24 to most recent.
• OSX 10.7-10.12.x.

Rekall also provides a complete memory sample acquisition capability for all major operating systems (see the tools directory).

Rekall is available as a python package installable via the pip package manager. To install it, first create a virtal env, switch to it and then install rekall:

$ virtualenv  /tmp/MyEnv
New python executable in /tmp/MyEnv/bin/python
Installing setuptools, pip...done.
$ source /tmp/MyEnv/bin/activate
$ pip install --upgrade setuptools pip wheel
$ pip install rekall-agent rekall

For windows, Rekall is also available as a self contained installer package. Please check the download page for the most appropriate installer to use Rekall-Forensic.com

To install from this git repository you will need to use pip --editable and follow the correct order of installation (otherwise pip will pull released dependencies which might be older):

$ virtualenv  /tmp/MyEnv
New python executable in /tmp/MyEnv/bin/python
Installing setuptools, pip...done.
$ source /tmp/MyEnv/bin/activate
$ pip install --upgrade setuptools pip wheel
$ git clone https://github.com/google/rekall.git rekall
$ pip install --editable rekall/rekall-lib
$ pip install --editable rekall/rekall-core
$ pip install --editable rekall/rekall-agent
$ pip install --editable rekall

On Windows you will need to install the Microsoft Visual C compilers for python (for more info see this blog post http://rekall-forensic.blogspot.ch/2015/09/installing-rekall-on-windows.html)

Mailing lists to support the users and developers of Rekall can be found at the following address:

[email protected]

Copyright (C) 2007-2011 Volatile Systems Copyright 2012-2016 Google Inc. All Rights Reserved.

All Rights Reserved

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.

There is no support provided with Rekall. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

If you think you've found a bug, please report it at:

https://github.com/google/rekall/issues

In order to help us solve your issues as quickly as possible, please include the following information when filing a bug:

• The version of rekall you're using
• The operating system used to run rekall
• The version of python used to run rekall
• The suspected operating system of the memory image
• The complete command line you used to run rekall

In December 2011, a new branch within the Volatility project was created to explore how to make the code base more modular, improve performance, and increase usability. The modularity allowed Volatility to be used in GRR, making memory analysis a core part of a strategy to enable remote live forensics. As a result, both GRR and Volatility would be able to use each other's strengths.

Over time this branch has become known as the "scudette" branch or the "Technology Preview" branch. It was always a goal to try to get these changes into the main Volatility code base. But, after two years of ongoing development, the "Technology Preview" was never accepted into the Volatility trunk version.

Since it seemed unlikely these changes would be incorporated in the future, it made sense to develop the Technology Preview branch as a separate project. On December 13, 2013, the former branch was forked to create a new stand-alone project named "Rekall.” This new project incorporates changes made to streamline the codebase so that Rekall can be used as a library. Methods for memory acquisition and other outside contributions have also been included that were not in the Volatility codebase.

Rekall strives to advance the state of the art in memory analysis, implementing the best algorithms currently available and a complete memory acquisition and analysis solution for at least Windows, OSX and Linux.

Further documentation is available at http://www.rekall-forensic.com/