VirtualMachineDetect is a tool aimed at detecting the presence of an underlying virtual machine. It can detect VMware, VirtualBox and VirtualPC. This tool is useful in understanding the methods using which programs can detect whether they are running on a Virtual Machine (VM) or not. A category of malware called as Split Personality Malware, detects the environment it is running on and behaves benignly/does not run, if it is on a VM. This tool VirtualMachineDetect is the result of the study of various methods used by this category of malware to detect VM.
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We invite the open source community to contribute to this work. The source code can be pulled from bitbucket repository (Project name: “VirtualMachineDetect” ). We need a Cloud based Infrastructure account to test the program on various combinations of systems possible. Please help our research by contributing cycles or help us automate the regression tests.
How does it work?
The tool detects the environment it is running on as VirtalBox, VirtualPC or VMWare. If any of the three is detected then the user is given an option to run a detailed check where he can view each test run and its results. The user is also provided with option to provide feedback on the correctness of the results.
What is new in this Version?
- Improved presentation of detection techniques for VirualBox and VirtualPC.
- Added a method for the users to provide us feedback.
- Improved the UI.
- Since the possible combinations of platforms for the product is huge, we do not have resources to test them all currently. So if you could not install this on your machine or had an unexpected behavior please report it to us with the complete set of logs found in “%appdata%/VirtualMachineDetect” to “v m Queries AT gmail DOT com”.
We are still in Beta and request you to provide us detailed feedback when ever you run the tool to make it better. Instructions – Provide us email and choose detailed feedback option.
Let us know if you liked this application and what more features you would like to add. Please book mark this page and recommend us on Facebook. We welcome your suggestions and feedback here.