Class: Backdoor
Backdoors are designed to give malicious users remote control over an infected computer. In terms of functionality, Backdoors are similar to many administration systems designed and distributed by software developers. These types of malicious programs make it possible to do anything the author wants on the infected computer: send and receive files, launch files or delete them, display messages, delete data, reboot the computer, etc. The programs in this category are often used in order to unite a group of victim computers and form a botnet or zombie network. This gives malicious users centralized control over an army of infected computers which can then be used for criminal purposes. There is also a group of Backdoors which are capable of spreading via networks and infecting other computers as Net-Worms do. The difference is that such Backdoors do not spread automatically (as Net-Worms do), but only upon a special “command” from the malicious user that controls them.Read more
Platform: Win32
Win32 is an API on Windows NT-based operating systems (Windows XP, Windows 7, etc.) that supports execution of 32-bit applications. One of the most widespread programming platforms in the world.Family: Farfli
No family descriptionExamples
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Tactics and Techniques: Mitre*
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.
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.
* © 2025 The MITRE Corporation. This work is reproduced and distributed with the permission of The MITRE Corporation.