Raul Alvarez
Senior Security Reseacher Fortinet Technologies (USA)
BIOGRAPHY
Raul is working at Fortinet as a Senior Security Researcher/ AV Team Lead since 2004. He is also the Lead Trainer responsible for training junior AV/IPS analysts in malware analysis and reverse engineering.
He is a regular contributor in his company blog posts and also in Virus Bulletin publication. He currently have 21 published articles in Virus Bulletin.
Before Raul joined Fortinet, he was a Senior AntiVirus Engineer and an AntiVirus Trainer at TrendMicro Philippines.
Raul was also a college instructor at two major universities in the Philippines.
Challenges on Reversing Layered Malware
Malware analysis using automated tools and sandboxes is the best and fastest response against malicious file execution. We can easily determine the effects of the malware, including network activities and system infection.
Modern malware are now smarter than before, they can determine if they are being analyzed, being debugged, or simply being executed in a virtual environment. But to really know how the malware works, we have to dig deeper into its code.
Layers in malware are defense mechanisms against deep analysis. Within these layers, different malware tricks are also deployed.
In this presentation, we are going to look into Scieron, an information stealer Trojan. It is not known in the wild, perhaps due to its implementation of layers. We are going to look closely into its code on how it implements code injection and hooking. We will look into its use of shellcode and how it extracts another layer from the resource section of another layer. Also, we will investigate how it implements different layers to hide its main payload and to avoid detection.
I will show a video demo on how the layers of Scieron are executed within the debugger.
Also in this presentation, we will compare Scieron against Vawtrak, that also has layering technology in its code.
Finally, we are going to leverage Volatility, a memory forensic tool, to detect the presence of layers in an infected system.
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