Class: Trojan-Dropper
Trojan-Dropper programs are designed to secretly install malicious programs built into their code to victim computers. This type of malicious program usually save a range of files to the victim’s drive (usually to the Windows directory, the Windows system directory, temporary directory etc.), and launches them without any notification (or with fake notification of an archive error, an outdated operating system version, etc.). Such programs are used by hackers to: secretly install Trojan programs and/or viruses protect known malicious programs from being detected by antivirus solutions; not all antivirus programs are capable of scanning all the components inside this type of Trojans.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: Trojan-Dropper.Win32.Dapato
No family descriptionExamples
40DCCA94B8A359F61EFB3869FBCE65BD1878946F341CC565A15B6E09B89B44E0
31207E06ADDD8F8BF000D40EAFDC04B4
090B922D7088C348CD20C03D9D757884
30120EF88E819FF70442D0B7F9BA14AE
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 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.
* © 2025 The MITRE Corporation. This work is reproduced and distributed with the permission of The MITRE Corporation.