Update Date
10/23/2024

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.

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Platform: BAT

No platform description

Family: Backdoor.Win32.RA-based

No family description

Examples

1A9DEFC3E6EBA4F71CB5D88373143BF9

Tactics and Techniques: Mitre*

TA0002
Execution

Adversaries may interact with the native OS application programming interface (API) to execute behaviors. Native APIs provide a controlled means of calling low-level OS services within the kernel, such as those involving hardware/devices, memory, and processes. These native APIs are leveraged by the OS during system boot (when other system components are not yet initialized) as well as carrying out tasks and requests during routine operations.


T1106
Native API

Adversaries may interact with the native OS application programming interface (API) to execute behaviors. Native APIs provide a controlled means of calling low-level OS services within the kernel, such as those involving hardware/devices, memory, and processes. These native APIs are leveraged by the OS during system boot (when other system components are not yet initialized) as well as carrying out tasks and requests during routine operations.


T1204.002
Malicious File

An adversary may rely upon a user opening a malicious file in order to gain execution. Users may be subjected to social engineering to get them to open a file that will lead to code execution. This user action will typically be observed as follow-on behavior from Spearphishing Attachment. Adversaries may use several types of files that require a user to execute them, including .doc, .pdf, .xls, .rtf, .scr, .exe, .lnk, .pif, and .cpl.


TA0005
Defense Evasion

Adversaries may use Obfuscated Files or Information to hide artifacts of an intrusion from analysis. They may require separate mechanisms to decode or deobfuscate that information depending on how they intend to use it. Methods for doing that include built-in functionality of malware or by using utilities present on the system.


T1140
Deobfuscate/Decode Files or Information

Adversaries may use Obfuscated Files or Information to hide artifacts of an intrusion from analysis. They may require separate mechanisms to decode or deobfuscate that information depending on how they intend to use it. Methods for doing that include built-in functionality of malware or by using utilities present on the system.


T1497.001
System Checks

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.


TA0007
Discovery

Adversaries may attempt to get a listing of open application windows. Window listings could convey information about how the system is used. For example, information about application windows could be used identify potential data to collect as well as identifying security tooling (Security Software Discovery) to evade.


T1010
Application Window Discovery

Adversaries may attempt to get a listing of open application windows. Window listings could convey information about how the system is used. For example, information about application windows could be used identify potential data to collect as well as identifying security tooling (Security Software Discovery) to evade.


T1018
Remote System Discovery

Adversaries may attempt to get a listing of other systems by IP address, hostname, or other logical identifier on a network that may be used for Lateral Movement from the current system. Functionality could exist within remote access tools to enable this, but utilities available on the operating system could also be used such as Ping or net view using Net.


T1057
Process Discovery

Adversaries may attempt to get information about running processes on a system. Information obtained could be used to gain an understanding of common software/applications running on systems within the network. Administrator or otherwise elevated access may provide better process details. Adversaries may use the information from Process Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.


T1497.001
System Checks

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.

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