Class: Trojan
A malicious program designed to electronically spy on the user’s activities (intercept keyboard input, take screenshots, capture a list of active applications, etc.). The collected information is sent to the cybercriminal by various means, including email, FTP, and HTTP (by sending data in a request).Read more
Platform: PowerShell
PowerShell is a platform that is represented by scripts written in Powershell.Family: Trojan.PowerShell.Disdroth.gen
No family descriptionExamples
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5206CF1777BA2FC04A49DA10D52F5D38
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01613FF03FC161428CB0376001AF7E09
Tactics and Techniques: Mitre*
Adversaries may abuse a double extension in the filename as a means of masquerading the true file type. A file name may include a secondary file type extension that may cause only the first extension to be displayed (ex: File.txt.exe may render in some views as just File.txt). However, the second extension is the true file type that determines how the file is opened and executed. The real file extension may be hidden by the operating system in the file browser (ex: explorer.exe), as well as in any software configured using or similar to the system’s policies.
Adversaries may abuse a double extension in the filename as a means of masquerading the true file type. A file name may include a secondary file type extension that may cause only the first extension to be displayed (ex: File.txt.exe may render in some views as just File.txt). However, the second extension is the true file type that determines how the file is opened and executed. The real file extension may be hidden by the operating system in the file browser (ex: explorer.exe), as well as in any software configured using or similar to the system’s policies.
Adversaries may employ various system checks to detect and avoid virtualization and analysis environments. This may include changing behaviors based on the results of checks for the presence of artifacts indicative of a virtual machine environment (VME) or sandbox. If the adversary detects a VME, they may alter their malware to disengage from the victim or conceal the core functions of the implant. They may also search for VME artifacts before dropping secondary or additional payloads. Adversaries may use the information learned from Virtualization/Sandbox Evasion during automated discovery to shape follow-on behaviors.
Adversaries may set files and directories to be hidden to evade detection mechanisms. To prevent normal users from accidentally changing special files on a system, most operating systems have the concept of a ‘hidden’ file. These files don’t show up when a user browses the file system with a GUI or when using normal commands on the command line. Users must explicitly ask to show the hidden files either via a series of Graphical User Interface (GUI) prompts or with command line switches (dir /a for Windows and ls –a for Linux and macOS).
Adversaries may employ various system checks to detect and avoid virtualization and analysis environments. This may include changing behaviors based on the results of checks for the presence of artifacts indicative of a virtual machine environment (VME) or sandbox. If the adversary detects a VME, they may alter their malware to disengage from the victim or conceal the core functions of the implant. They may also search for VME artifacts before dropping secondary or additional payloads. Adversaries may use the information learned from Virtualization/Sandbox Evasion during automated discovery to shape follow-on behaviors.
Adversaries may employ various system checks to detect and avoid virtualization and analysis environments. This may include changing behaviors based on the results of checks for the presence of artifacts indicative of a virtual machine environment (VME) or sandbox. If the adversary detects a VME, they may alter their malware to disengage from the victim or conceal the core functions of the implant. They may also search for VME artifacts before dropping secondary or additional payloads. Adversaries may use the information learned from Virtualization/Sandbox Evasion during automated discovery to shape follow-on behaviors.
* © 2026 The MITRE Corporation. This work is reproduced and distributed with the permission of The MITRE Corporation.