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MALHEUR - Automatic Analysis of Malware Behavior
Copyright (c) 2009-2012 Konrad Rieck (konrad@mlsec.org)
University of Goettingen, Berlin Institute of Technology
Introduction
--
Malheur is a tool for the automatic analysis of malware behavior (program
behavior recorded from malicious software in a sandbox environment). It
has been designed to support the regular analysis of malicious software and
the development of detection and defense measures. Malheur allows for
identifying novel classes of malware with similar behavior and assigning
unknown malware to discovered classes. It supports four basic actions for
analysis which can be applied to reports of recorded behavior:
1. Extraction of prototypes
From a given set of reports, malheur identifies a subset of
prototypes representative for the full data set. The prototypes
provide a quick overview of recorded behavior and can be used to
guide manual inspection.
2. Clustering of behavior
Malheur automatically identifies groups (clusters) of reports
containing similar behavior. Clustering allows for discovering novel
classes of malware and provides the basis for crafting specific
detection and defense mechanisms, such as anti-virus signatures.
3. Classification of behavior
Based on a set of previously clustered reports, malheur is able to
assign unknown behavior to known groups of malware. Classification
enables identifying novel and unknown variants of malware and can be
used to filter program behavior prior to manual inspection.
4. Incremental analysis
Malheur can be applied incrementally for analysis of large data
sets. By processing reports in chunks, the run-time as well as
memory requirements can be significantly reduced. This renders
long-term application of malheur feasible, for example for daily
analysis of incoming malware programs.
A detailed description of these techniques as well as technical
background on analysis of malicious software is provided in the
following articles:
"Automatic Analysis of Malware Behavior using Machine Learning"
Konrad Rieck, Philipp Trinius, Carsten Willems, and Thorsten Holz
Journal of Computer Security (JCS), 19 (4) 639-668, 2011.
"A Malware Instruction Set for Behavior-Based Analysis"
Philipp Trinius, Carsten Willems, Thorsten Holz, and Konrad Rieck
Technical report TR-2009-07, University of Mannheim, 2009
Dependencies
--
>= libconfig-1.4
>= libarchive-2.70
Compilation & Installation
--
From GIT repository first run
$ ./bootstrap
From tarball run
$ ./configure [options]
$ make
$ make check
$ make install
Options for configure
--prefix=PATH Set directory prefix for installation
By default Malheur is installed into /usr/local. If you prefer
a different location, use this option to select an installation
directory.
--enable-openmp Enable support for OpenMP (experimental)
This option enables support for OpenMP in Malheur. Several
functions of the malware analysis have been enhanced using
OpenMP directives, such that they execute in parallel and
benefit from multi-core architectures.
--enable-matlab Enable optional Matlab tools
--with-matlab-dir=PATH Set directory prefix of matlab installation
Some functions of Malheur are also available in form of Matlab
.mex files which allows for using implemented analysis
methods directly from within a Matlab environment.
License
--
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 3 of the License, or
(at your option) any later version. This program is distributed
without any warranty. See the GNU General Public License for more
details.
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