A Group of the researchers from the Iswatlab team at the University of Sannio demonstrated how is easy to create new malware that eludes antimalware.

It’s not easy to ‘write’ a new malware that is able to evade the detection of antimalware and other defensive software, but it is easier to ‘produce’ a new malware that can evade the detection of antimalware solutions.

The difference between writing and producing is very subtle and stands in the fact that in the latter case the malware writer does not need to write any line of code, he just needs to press a button.

The researchers at the Iswatlab (www.iswatlab.eu) at the University of Sannio (Italy) realized an engine that applies eight transformations to a mobile malware code which alter the code’s shape, but not the behavior of the malware.

This tool used by the team is named the “Malware Washing Machine” for obvious reasons.

The transformation engine developed by the researcher for Android malware works by applying the following transformations:

Disassembling & Reassembling.

Repacking.

Changing package name.

Identifier Renaming.

Data Encoding.

Call indirections.

Code Reordering.

Junk Code Insertion.

Composite Transformations.

The Iswatlab crew tested the Malware Washing Machine against 57 well known commercial antimalware solutions.

They used their engine for changing 5560 malware that was identified and classified as malware by tall the 57 antimalware used in the test session.

Anyway, after the modification, the majority of antimalware is no more able to recognize a large subset of the malware.

“Are the actual signature based detection algorithms effective on mobile environments? We developed a framework which applies a set of transformations to Android

applications small code. We then transformed a real world malware data-set (available at: https://www.sec.cs.tu-bs.de/~danarp/drebin/index.html) and then we submitted the applications to the website www.virustotal.com, in order to evaluate the maliciousness before and after the transformations (we submitted every sample pre and post transformation process).” reads the report.

The test showed that there are some malware families that are recognized by some antimalware also after the transformations, but they were a very little part.

“In the following table, first column represents the Anti-Malware, the second the number of samples (without transformations) correctly detected by the antimalware while in the third column (in red) the number of correctly detected samples after transformation process.”

“The results is impressive: the antimalware is not able to recognize the transformed malware (given that it was able to recognize the original malware).

The transformation engine is released for the scientific community with the open source license at the following url: https://github.com/faber03/AndroidMalwareEvaluatingTools“

The details of the test conducted by the Iswatlab are included in the report titled “Evaluating malware obfuscation techniques against antimalware detection algorithms”

This test raises the discussion about the capability to limit the production of malware, the experts at the Iswatlab were able to create new malware without writing any line of new code, but just scrambling some old well-known threats.

Summing up, the producing a new-born malware, that is not detectable by defense solutions, just takes a few minutes. Take an old malware and put it into the Malware Washing Machine!

The Malware Washing Machine is available at https://github.com/faber03/AndroidMalwareEvaluatingTools

About the Author Prof Corrado Aaron Visaggio

Corrado Aaron Visaggio is an assistant professor of Software Security of the MsC in Computer Engineering at the University of Sannio, Italy. He obtained the PhD in computer engineering aWashingsity of Sannio (Italy). His research interests include malware analysis, software security,code assessment, and data privacy. He is the author of more than 70 papers published in international journals, international and national conference proceedings, and books. PhD in computer engineering aWashingsity of Sannio (Italy). His research interests include malware analysis, software security,code assessment, and data privacy. He is the author of more than 70 papers published in international journals, international and national conference proceedings, and books.

He is responsible of the ISWATLAB a laboratory on Software Security research at the University of Sannio.

He is member of the CINI CyberSecurity Lab. member of the CINI CyberSecurity Lab. member of the CINI CyberSecurity Lab.

He is member of the European CyberSecurity Organization at EU.member of the European CyberSecurity Organization at EU.member of the European CyberSecurity Organization at EU.

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