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Home»Cybersecurity»Rust-Based VENON Malware Targets 33 Brazilian Banks with Credential-Stealing Overlays
Cybersecurity

Rust-Based VENON Malware Targets 33 Brazilian Banks with Credential-Stealing Overlays

primereportsBy primereportsMarch 12, 2026No Comments3 Mins Read
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Rust-Based VENON Malware Targets 33 Brazilian Banks with Credential-Stealing Overlays
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Ravie LakshmananMar 12, 2026Malware / Cybercrime

Rust-Based VENON Malware Targets 33 Brazilian Banks with Credential-Stealing Overlays

Cybersecurity researchers have disclosed details of a new banking malware targeting Brazilian users that’s written in Rust, marking a significant departure from other known Delphi-based malware families associated with the Latin American cybercrime ecosystem.

The malware, which is designed to infect Windows systems and was first discovered last month, has been codenamed VENON by Brazilian cybersecurity company ZenoX.

What makes VENON notable is that it shares behaviors that are consistent with established banking trojans targeting the region, such as Grandoreiro, Mekotio, and Coyote, specifically when it comes to features like banking overlay logic, active window monitoring, and a shortcut (LNK) hijacking mechanism.

The malware has not been attributed to any previously documented group or campaign. However, an earlier version of the artifact, dating back to January 2026, has been found to expose full paths from the malware author’s development environment. The paths repeatedly reference a Windows machine username “byst4” (e.g., “C:\Users\byst4\…”).

Cybersecurity

“The Rust code structure presents patterns suggesting a developer familiar with the capabilities of existing Latin American banking trojans, but who used generative AI to rewrite and expand these functionalities in Rust, a language that requires significant technical experience to use at the observed level of sophistication,” ZenoX said.

VENON is distributed by means of a sophisticated infection chain that uses DLL side-loading to launch a malicious DLL. It’s suspected that the campaign leverages social engineering ploys like ClickFix to trick users into downloading a ZIP archive containing the payloads by means of a PowerShell script.

Once the DLL is executed, it performs nine evasion techniques, including anti-sandbox checks, indirect syscalls, ETW bypass, AMSI bypass, before actually initiating any malicious actions. It also reaches out to a Google Cloud Storage URL to retrieve a configuration, install a scheduled task, and establish a WebSocket connection to the command-and-control (C2) server.

Also extracted from the DLL are two Visual Basic Script blocks that implement a shortcut hijacking mechanism exclusively targeting the Itaú banking application. The components work by replacing the legitimate system shortcuts with tampered versions that redirect the victim to a web page under the threat actor’s control.

The attack also supports an uninstall step to undo the modifications, suggesting that the operation can be remotely controlled by the operator to restore the shortcuts to what they originally were to cover up the tracks.

In all, the banking malware is equipped to target 33 financial institutions and digital asset platforms by monitoring the window title and active browser domain, springing into action only when any of the targeted applications or websites are opened to facilitate credential theft by serving fake overlays.

Cybersecurity

The disclosure comes amid campaigns where threat actors are exploiting the ubiquity of WhatsApp in Brazil to distribute a worm named SORVEPOTEL via the messaging platform’s desktop web version. The attack hinges on abusing previously authenticated chats to deliver malicious lures directly to victims, ultimately resulting in the deployment of banking malware such as Maverick, Casbaneiro, or Astaroth.

“A single WhatsApp message delivered through a hijacked SORVEPOTEL session was sufficient to draw a victim into a multi-stage chain that ultimately resulted in an Astaroth implant running fully in memory,” Blackpoint Cyber said.

“The combination of local automation tooling, unsupervised browser drivers, and user-writable runtimes created an unusually permissive environment, allowing both the worm and the final payload to establish themselves with minimal friction.”

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