Orchestrating Android Malware Experiments

Jean-François Lalande 1 Pierre Graux 1 Tomás Concepción Miranda 1
1 CIDRE - Confidentialité, Intégrité, Disponibilité et Répartition
CentraleSupélec, Inria Rennes – Bretagne Atlantique , IRISA-D1 - SYSTÈMES LARGE ÉCHELLE
Abstract : Experimenting with Android malware requires to manipulate a large amount of samples and to chain multiple analyses. Scripting such a sequence of analyses on a large malware dataset becomes a challenge: the analysis has to handle fails on the computer and crashes on the used smartphone, in case of dynamic analyses.We present a new tool, PyMaO, for handling such experiments on a regular desktop PC with the highest performance throughput. PyMaO helps to write sequences of analyses and handle partial experiments that should be restarted after a crash or continued with new unknown analyses. The tool also offers a post processing capability for generating number tables or bar graphs from the analyzed datasets.
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https://hal-centralesupelec.archives-ouvertes.fr/hal-02305473
Contributor : Jean-François Lalande <>
Submitted on : Friday, October 4, 2019 - 11:19:59 AM
Last modification on : Tuesday, November 12, 2019 - 4:09:19 PM

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  • HAL Id : hal-02305473, version 1

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CENTRALESUPELEC | UNIV-RENNES1 | SUP_CIDRE | INRIA | UNIV-RENNES | IRISA | UR1-UFR-ISTIC

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Jean-François Lalande, Pierre Graux, Tomás Concepción Miranda. Orchestrating Android Malware Experiments. MASCOTS 2019 - 27th IEEE International Symposium on the Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, Oct 2019, Rennes, France. pp.1-2. ⟨hal-02305473⟩

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