dynmx

dynmx (spoken dynamics) is a signature-based detection approach for behavioural malware features based on Windows API call sequences. In a simplified way, you can think of dynmx as a sort of YARA for API call traces (so-called function logs) originating from malware sandboxes. Hence, the data basis for the detection approach is not the malware samples themselves which are analyzed statically but data that is generated during a dynamic analysis of the malware sample in a malware sandbox. Currently, dynmx supports function logs of the following malware sandboxes:

• VMRay (function log, text-based and XML format)
• CAPEv2 (report.json file)
• Cuckoo (report.json file)

The detection approach is described in detail in the master thesis Signature-Based Detection of Behavioural Malware Features with Windows API Calls. This project is the prototype implementation of this approach and was developed in the course of the master thesis. The signatures are manually defined by malware analysts in the dynmx signature DSL and can be detected in function logs with the help of this tool. Features and syntax of the dynmx signature DSL can also be found in the master thesis. Furthermore, you can find sample dynmx signatures in the repository dynmx-signatures. In addition to detecting malware features based on API calls, dynmx can extract OS resources that are used by the malware (a so-called Access Activity Model). These resources are extracted by examining the API calls and reconstructing operations on OS resources. Currently, OS resources of the categories filesystem, registry, and network are considered in the model.

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