In September 2024, a new malicious campaign, dubbed Gecko Assault, was uncovered by researchers from SCILabs. This campaign is distributing two well-known malware families—Mekotio and Mispadu (also referred to as URSA/Mispadu)—with a focus on targeting users in the Latin American region. Both malware types are known for their abilities to steal sensitive financial information, including banking credentials, as well as in-browser stored data and various other credentials. This attack highlights the evolving nature of cyber threats aimed at compromising personal and financial data.
The Gecko Assault campaign employs a range of sophisticated techniques to deliver these malware payloads. One key method involves DLL hijacking, where attackers manipulate the legitimate GoToMeeting application to inject malicious DLL files. This tactic allows the malware to run undetected, bypassing security measures that typically monitor application behavior. Additionally, the campaign makes use of AutoIt scripts, a scripting language often abused for malicious purposes, to further automate and streamline the infection process.
Beyond the technical delivery methods, the campaign also takes advantage of various known vulnerabilities in systems to gain a foothold in victim networks. The attackers exploit these weaknesses to establish persistence, allowing them to execute the malware without triggering immediate detection. Once inside the system, Mekotio and Mispadu can exfiltrate sensitive data, including banking information, browser-stored passwords, and credentials for online accounts, posing a serious threat to individuals and organizations.
Leading security providers like Symantec and VMware Carbon Black have issued protection measures to counter this threat. Symantec, for instance, detects these malware variants under identifiers such as Trojan.Gen.MBT and Trojan.Mekotio, while VMware Carbon Black’s policies recommend blocking all types of malware executions, whether known or suspicious. These proactive steps, alongside leveraging advanced machine learning-based detection, are essential in mitigating the impact of the Gecko Assault campaign.
