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Update Date
02/10/2024

Clase: Trojan

Un programa malicioso diseñado para espiar electrónicamente las actividades del usuario (interceptar la entrada del teclado, tomar capturas de pantalla, capturar una lista de aplicaciones activas, etc.). La información recopilada se envía al cibercriminal por diversos medios, incluidos el correo electrónico, FTP y HTTP (mediante el envío de datos en una solicitud).

Más información

Plataforma: Win32

Win32 es una API en sistemas operativos basados ​​en Windows NT (Windows XP, Windows 7, etc.) que admite la ejecución de aplicaciones de 32 bits. Una de las plataformas de programación más extendidas en el mundo.

Familia: Trojan.Win32.Phpw

No family description

Examples

C035C3B3C90E0F067C7F541C881FA9B3
79F50EACE377A6024EA3375109A87815
6C15C4EB1A191732BEA2C4014713EDD0
A9165F66C35363AF7306ECDE4ABA2EE2
79ADC61E908EAB195412D55C88D3A62A

Tactics and Techniques: Mitre*

TA0005
Defense Evasion
The adversary is trying to avoid being detected.

Defense Evasion consists of techniques that adversaries use to avoid detection throughout their compromise. Techniques used for defense evasion include uninstalling/disabling security software or obfuscating/encrypting data and scripts. Adversaries also leverage and abuse trusted processes to hide and masquerade their malware. Other tactics’ techniques are cross-listed here when those techniques include the added benefit of subverting defenses.
T1497.002
Virtualization/Sandbox Evasion: User Activity Based Checks
Adversaries may employ various user activity 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.(Citation: Deloitte Environment Awareness)

Adversaries may search for user activity on the host based on variables such as the speed/frequency of mouse movements and clicks (Citation: Sans Virtual Jan 2016) , browser history, cache, bookmarks, or number of files in common directories such as home or the desktop. Other methods may rely on specific user interaction with the system before the malicious code is activated, such as waiting for a document to close before activating a macro (Citation: Unit 42 Sofacy Nov 2018) or waiting for a user to double click on an embedded image to activate.(Citation: FireEye FIN7 April 2017)
TA0007
Discovery
The adversary is trying to figure out your environment.

Discovery consists of techniques an adversary may use to gain knowledge about the system and internal network. These techniques help adversaries observe the environment and orient themselves before deciding how to act. They also allow adversaries to explore what they can control and what’s around their entry point in order to discover how it could benefit their current objective. Native operating system tools are often used toward this post-compromise information-gathering objective.
T1497.002
Virtualization/Sandbox Evasion: User Activity Based Checks
Adversaries may employ various user activity 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.(Citation: Deloitte Environment Awareness)

Adversaries may search for user activity on the host based on variables such as the speed/frequency of mouse movements and clicks (Citation: Sans Virtual Jan 2016) , browser history, cache, bookmarks, or number of files in common directories such as home or the desktop. Other methods may rely on specific user interaction with the system before the malicious code is activated, such as waiting for a document to close before activating a macro (Citation: Unit 42 Sofacy Nov 2018) or waiting for a user to double click on an embedded image to activate.(Citation: FireEye FIN7 April 2017)

* © 2026 The MITRE Corporation. This work is reproduced and distributed with the permission of The MITRE Corporation.

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