Update Date
11/22/2023

Class: Downloader

Programs of this type stealthily download a variety of content from network resources. They are not malicious programs, but malicious users can use them to download malicious content onto a victim computer. If a user has installed such a program on his/her computer, or if it was installed by a system administrator, then it does not pose any threat.

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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: VrBrothers

No family description

Examples

8BA95B48DE448FD7949098DE2964250C
CA6747EDF1A479DFBF8B2C48D0ACC2F7
DE243C68A0FF51AEE2E0C88B11784A3C
3B774F13CBE75F38EFDDC74AE940A225
44ABD407F5BDD6254AC883413FB136D7

Tactics and Techniques: Mitre*

TA0005
Defense Evasion

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)


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

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)


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)


T1518.001
Software Discovery: Security Software Discovery

Adversaries may attempt to get a listing of security software, configurations, defensive tools, and sensors that are installed on a system or in a cloud environment. This may include things such as firewall rules and anti-virus. Adversaries may use the information from Security Software Discovery during automated discovery to shape follow-on behaviors, including whether or not the adversary fully infects the target and/or attempts specific actions.


Example commands that can be used to obtain security software information are netsh, reg query with Reg, dir with cmd, and Tasklist, but other indicators of discovery behavior may be more specific to the type of software or security system the adversary is looking for. It is becoming more common to see macOS malware perform checks for LittleSnitch and KnockKnock software.


Adversaries may also utilize cloud APIs to discover the configurations of firewall rules within an environment.(Citation: Expel IO Evil in AWS) For example, the permitted IP ranges, ports or user accounts for the inbound/outbound rules of security groups, virtual firewalls established within AWS for EC2 and/or VPC instances, can be revealed by the DescribeSecurityGroups action with various request parameters. (Citation: DescribeSecurityGroups – Amazon Elastic Compute Cloud)


* © 2024 The MITRE Corporation. This work is reproduced and distributed with the permission of The MITRE Corporation.

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