Time-based Evolution of Malware Behavior in Sandboxes
Time-based Evolution of Malware Behavior in Sandboxes
Supervisor(s): | Julian Kirsch Davide Balzarotti |
Status: | finished |
Topic: | Others |
Author: | Alexander Küchler |
Submission: | 2019-03-15 |
Type of Thesis: | Masterthesis |
DescriptionToday, sandboxes are one of the most important techniques for dynamic malware analysis. To perform an analysis, the malware sample is executed in an instrumented and isolated environment for a certain amount of time. As publicly available sandboxes have to serve a high amount of requests, the time to execute a single malware sample is often limited to only 1 or 2 minutes. However, so far no study on the evolution of malware behavior over time exists. Consequently, it is unknown if such a limited amount of time is actually sufficient to predict whether a program is malicious or benign. We developed a custom sandbox to combat this shortcoming of the current state of research. We therefore leverage the PANDA full-system emulator. Our sandbox carries out a fine-grained study of the evolvement of malware behavior over time. The key of the system is to run a malware sample for a long duration and measure how the code coverage evolves. Assuming that new behavior comes with new executed code, the evolution of code coverage gives us a hint about the evolution of additional behavior exhibited by the malware sample throughout its run-time. By executing this experiment for a large set of malware samples, we aim at first determining realistic values for malware code coverage in sandboxes and second studying the evolution of malware behavior. To extract high-level information about the malware's behavior, we further extract all system calls and provide data lifting of system and API calls as well as the disassembly of executed basic blocks to identify different phases of the malware sample's lifecycle. We present the sandbox system together with preliminary results of the analysis. |