Classe: Trojan-Dropper
Os programas do Trojan-Dropper são projetados para instalar secretamente programas maliciosos embutidos em seus códigos nos computadores das vítimas. Esse tipo de programa malicioso geralmente salva vários arquivos na unidade da vítima (geralmente no diretório do Windows, no diretório de sistema do Windows, no diretório temporário, etc.) e os lança sem qualquer notificação (ou com notificação falsa de um erro de arquivamento). versão desatualizada do sistema operacional, etc.). Tais programas são usados por hackers para: instalar secretamente programas de Tróia e / ou vírus que protejam programas maliciosos conhecidos de serem detectados por soluções de antivírus; nem todos os programas antivírus são capazes de escanear todos os componentes dentro desse tipo de trojans.Plataforma: Win32
O Win32 é uma API em sistemas operacionais baseados no Windows NT (Windows XP, Windows 7, etc.) que oferece suporte à execução de aplicativos de 32 bits. Uma das plataformas de programação mais difundidas do mundo.Família: Trojan-Dropper.Win32.Agent
No family descriptionExamples
F67A4BC9BBD7312249444000624E9E12Tactics 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.
T1497.001
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
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.
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,
net view using Net, or, on ESXi servers, `esxcli network diag ping`. T1049
System Network Connections Discovery
Adversaries may attempt to get a listing of network connections to or from the compromised system they are currently accessing or from remote systems by querying for information over the network.
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.
* © 2026 The MITRE Corporation. This work is reproduced and distributed with the permission of The MITRE Corporation.