malheur: Automatic Analysis of Malware Behavior

MALHEUR – Automatic Analysis of Malware Behavior

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 datasets. By processing reports in chunks, the run-time, as well as memory requirements, can be significantly reduced. This renders the 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

Install

git clone https://github.com/rieck/malheur.git
$ ./configure [options]
$ make
$ make check
$ make install

Usage

Copyright (c) 2009-2015 Konrad Rieck

Source: https://github.com/rieck

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