Researchers from Kaspersky's Global Research and Analysis Team (GReAT) have detailed a large-scale malware distribution campaign that leverages the trust inherent in the WhatsApp messaging platform. Threat actors are using previously compromised WhatsApp accounts to propagate malware by sending malicious VBScript files to the account's contacts. The files are socially engineered to look like legitimate business documents, increasing the likelihood of execution. The multi-stage infection process results in the attacker gaining remote access to the victim's computer. The campaign has a wide geographical distribution, with notable victim clusters in Malaysia, Brazil, Singapore, and across Europe.
This campaign's effectiveness hinges on its social engineering component. By originating from a compromised account, the malicious message appears to come from a trusted friend, family member, or colleague. This bypasses the natural suspicion that accompanies messages from unknown senders.
The attackers send a Visual Basic Script (.vbs) file disguised with a name suggesting a business document, such as an invoice, receipt, or order confirmation. The filenames are localized into multiple languages, indicating a deliberate effort to target users in specific regions. When the recipient is tricked into opening the .vbs file, it initiates an infection chain.
The attack follows a multi-stage process designed to evade initial detection and establish a persistent foothold.
.vbs file. This is a form of T1566 - Phishing delivered via an instant messaging service..vbs file. This action corresponds to T1204.002 - User Execution: Malicious File.wscript.exe), acts as a dropper or downloader. It connects to an external command-and-control (C2) server to download the next stage of the malware. This is an example of T1059.005 - Command and Scripting Interpreter: Visual Basic.T1219 - Remote Access Software.A successful infection can lead to a variety of negative outcomes for the victim:
No specific technical Indicators of Compromise (IOCs) such as C2 domains or file hashes were provided in the source articles.
Security teams and advanced users can hunt for signs of this activity:
process_namewscript.exewscript.exe processes making outbound network connections, which is often suspicious.command_line_patternwscript.exe //E:VBScript "C:\Users\...\invoice.vbs".vbs files, especially those downloaded from the internet.file_name*.vbs.vbs files in user download or temporary folders.log_sourcewscript.exe or powershell.exe..vbs, .js, .ps1). Enable script block logging for PowerShell.D3FEND Techniques:
File Analysis (D3-FA): Security tools analyzing the content of the .vbs file to identify malicious code patterns.Dynamic Analysis (D3-DA): Sandboxing the .vbs file to observe its behavior, such as network callbacks or file system changes..vbs and .js files entirely..vbs files from wscript.exe to notepad.exe. This will cause the script to open as a text file instead of executing, allowing the user to inspect it safely.D3FEND Techniques:
Application Configuration Hardening (D3-ACH): This includes disabling or restricting script interpreters like WSH.The most effective mitigation against this social engineering-heavy attack is training users to be suspicious of unexpected files.
Preventing the execution of scripts like VBScript through Group Policy or application control.
Mapped D3FEND Techniques:
Using endpoint security software to detect and block known malicious scripts and payloads.

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Every tactic, technique, and sub-technique used in this threat has been identified and mapped to the MITRE ATT&CK framework for consistent, actionable threat language.
Observables and indicators of compromise (IOCs) have been extracted and cataloged. Risk has been assessed and correlated with known threat actors and historical campaigns.
Detection rules, incident response steps, and D3FEND-aligned mitigation strategies are included so your team can act on this intelligence immediately.
Structured threat data is packaged as a STIX 2.1 bundle and can be visualized as an interactive graph — relationships between actors, malware, techniques, and indicators.
Sigma detection rules are derived from the threat techniques in this article and can be converted for deployment across any major SIEM or EDR platform.