Mirroring the overall growth of the cybersecurity landscape and the advancement of security tool capabilities, threat actors are continuously forced to keep pace. Today, threat actors are bringing novel malware into the wild, creating new attack vectors, and finding ways to avoid the detection of security tools.
One notable example of a constantly adapting type of malware can be seen with banking trojans, a type of malware designed to steal confidential information, such as banking credentials, used by attackers for financial gain. Gozi-ISFB is a widespread banking trojan that has previously been referred to as ‘the malware with a thousand faces’ and, as it name might suggest, has been known under various names such as Gozi, Ursnif, Papras and Rovnix to list a few.
Between November 2022 and January 2023, a rise in Gozi-ISFB malware related activity was observed across Darktrace customer environments and was investigated by the Darktrace Threat Research team. Leveraging its Self-Learning AI, Darktrace was able to identify activity related to this banking trojan, regardless of the attack vectors or delivery methods utilized by threat actors.
We have moderate to high confidence that the series of activities observed is associated with Gozi-ISFB malware and high confidence in the indicators of compromise identified which are related to the post-compromise activities from Gozi-ISFB malware.
Gozi-ISFB Background
The Gozi-ISFB malware was first observed in 2011, stemming from the source code of another family of malware, Gozi v1, which in turn borrowed source code from the Ursnif malware strain.
Typically, the initial access payloads of Gozi-ISFB would require an endpoint to enable a macro on their device, subsequently allowing a pre-compiled executable file (.exe) to be gathered from an attacker-controlled server, and later executed on the target device.
However, researchers have recently observed Gozi-ISFB actors using additional and more advanced capabilities to gain access to organizations networks. These capabilities range from credential harvest, surveilling user keystrokes, diverting browser traffic from banking websites, remote desktop access, and the use of domain generation algorithms (DGA) to create command-and-control (C2) domains to avoid the detection and blocking of traditional security tools.
Ultimately, the goal of Gozi-ISFB malware is to gather confidential information from infected devices by connecting to C2 servers and installing additional malware modules on the network.
Darktrace Coverage of Gozi-ISFB
Unlike traditional security approaches, Darktrace DETECT/Network™ can identify malicious activity because Darktrace models build an understanding of a device’s usual pattern of behavior, rather than using a static list of indicators of compromise (IoCs) or rules and signatures. As such, Darktrace is able to instantly detect compromised devices that deviate from their expected behavioral patterns, engaging in activity such as unusual SMB connections or connecting to newly created malicious endpoints or C2 infrastructure. In the event that Darktrace detects malicious activity, it would automatically trigger an alert, notifying the customer of an ongoing security concern.
Regarding the Gozi-ISFB attack process, initial attack vectors commonly include targeted phishing campaigns, where the recipient would receive an email with an attached Microsoft Office document containing macros or a Zip archive file. Darktrace frequently observes malicious emails like this across the customer base and is able to autonomously detect and action them using Darktrace/Email™. In the following cases, the clients who had Darktrace/Email did not have evidence of compromise through their corporate email infrastructure, suggesting devices were likely compromised via the access of personal email accounts. In other cases, the customers did not have Darktrace/Email enabled on their networks.
Upon downloading and opening the malicious attachment included in the phishing email, the payload subsequently downloads an additional .exe or dynamic link library (DLL) onto the device. Following this download, the malware will ultimately begin to collect sensitive data from the infected device, before exfiltrating it to the C2 server associated with Gozi-ISFB. Darktrace was able to demonstrate and detect the retrieval of Gozi-ISFB malware, as well as subsequent malicious communication on multiple customer environments.
In some attack chains observed, the infected device made SMB connections to the rare external endpoint ’62.173.138[.]28’ via port 445. Darktrace recognized that the device used unusual credentials for this destination endpoint and further identified it performing SMB reads on the share ‘\\62.173.138[.]28\Agenzia’. Darktrace also observed that the device downloaded the executable file ‘entrat.exe’ from this connection as can be seen in Figure 1.
Subsequently, the device performed a separate SMB login to the same external endpoint using a credential identical to the device's name. Shortly after, the device performed a SMB directory query from the root share drive for the file path to the same endpoint.
In Gozi-ISFB compromises investigated by the Threat Research team, Darktrace commonly observed model breaches for ‘Multiple HTTP POSTs to Rare Hostname’ and the use of the Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 10.0; Win64; x64)’ user agent.
Devices were additionally observed making external connections over port 80 (TCP, HTTP) to endpoints associated with Gozi-ISFB. Regarding these connections, C2 communication was observed used configurations of URI path and resource file extension that claimed to be related to images within connections that were actually GET or POST request URIs. This is a commonly used tactic by threat actors to go under the radar and evade the detection of security teams.
An example of this type of masqueraded URI can be seen below:
In another similar example investigated by the Threat Research team, Darktrace detected similar external connectivity associated with Gozi-ISFB malware. In this case, DETECT identified external connections to two separate hostnames, namely ‘gameindikdowd[.]ru’ and ‘jhgfdlkjhaoiu[.]su’, both of which have been associated to Gozi-ISFB by OSINT sources. This specific detection included HTTP beaconing connections to endpoint, gameindikdowd[.]ru .
Details observed from this event:
Destination IP: 134.0.118[.]203
Destination port: 80
ASN: AS197695 Domain names registrar REG.RU, Ltd
User agent: Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 10.0; Win64; x64
The same device later made anomalous HTTP POST requests to a known Gozi-ISFB endpoint, jhgfdlkjhaoiu[.]su.
Details observed:
Destination port: 80
ASN: AS197695 Domain names registrar REG.RU, Ltd
User agent: Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 10.0; Win64; x64
Conclusions
With constantly changing attack infrastructure and new methods of exploitation tested and leveraged hour upon hour, it is critical for security teams to employ tools that help them stay ahead of the curve to avoid critical damage from compromise.
Faced with a notoriously adaptive malware strain like Gozi-ISFB, Darktrace demonstrated its ability to autonomously detect malicious activity based upon more than just known IoCs and attack vectors. Despite the multitude of different attack vectors utilized by threat actors, Darktrace was able to detect Gozi-ISFB activity at various stages of the kill chain using its anomaly-based detection to identify unusual activity or deviations from normal patterns of life. Using its Self-Learning AI, Darktrace successfully identified infected devices and brought them to the immediate attention of customer security teams, ultimately preventing infections from leading to further compromise.
The Darktrace suite of products, including DETECT/Network, is uniquely placed to offer customers an unrivaled level of network security that can autonomously identify and respond to arising threats against their networks in real time, preventing suspicious activity from leading to damaging network compromises.
Credit to: Paul Jennings, Principal Analyst Consultant and the Threat Research Team
Appendices
List of IOCs
134.0.118[.]203 - IP Address - Gozi-ISFB C2 Endpoint
62.173.138[.]28 - IP Address - Gozi-ISFB C2 Endpoint
45.130.147[.]89 - IP Address - Gozi-ISFB C2 Endpoint
94.198.54[.]97 - IP Address - Gozi-ISFB C2 Endpoint
91.241.93[.]111 - IP Address - Gozi-ISFB C2 Endpoint
89.108.76[.]56 - IP Address - Gozi-ISFB C2 Endpoint
87.106.18[.]141 - IP Address - Gozi-ISFB C2 Endpoint
35.205.61[.]67 - IP Address - Gozi-ISFB C2 Endpoint
91.241.93[.]98 - IP Address - Gozi-ISFB C2 Endpoint
62.173.147[.]64 - IP Address - Gozi-ISFB C2 Endpoint
146.70.113[.]161 - IP Address - Gozi-ISFB C2 Endpoint
iujdhsndjfks[.]ru - Hostname - Gozi-ISFB C2 Hostname
reggy505[.]ru - Hostname - Gozi-ISFB C2 Hostname
apr[.]intoolkom[.]at - Hostname - Gozi-ISFB C2 Hostname
jhgfdlkjhaoiu[.]su - Hostname - Gozi-ISFB C2 Hostname
gameindikdowd[.]ru - Hostname - Gozi-ISFB Hostname
chnkdgpopupser[.]at - Hostname – Gozi-ISFB C2 Hostname
denterdrigx[.]com - Hostname – Gozi-ISFB C2 Hostname
entrat.exe - Filename – Gozi-ISFB Related Filename
Darktrace Model Coverage
Anomalous Connection / Multiple HTTP POSTs to Rare Hostname
Anomalous Connection / Posting HTTP to IP Without Hostname
Anomalous Connection / New User Agent to IP Without Hostname
Compromise / Agent Beacon (Medium Period)
Anomalous File / Application File Read from Rare Endpoint
Device / Suspicious Domain
Mitre Attack and Mapping
Tactic: Application Layer Protocol: Web Protocols
Technique: T1071.001
Tactic: Drive-by Compromise
Technique: T1189
Tactic: Phishing: Spearphishing Link
Technique: T1566.002
Model Detection
Anomalous Connection / Multiple HTTP POSTs to Rare Hostname - T1071.001
Anomalous Connection / Posting HTTP to IP Without Hostname - T1071.001
Anomalous Connection / New User Agent to IP Without Hostname - T1071.001
Compromise / Agent Beacon (Medium Period) - T1071.001
Anomalous File / Application File Read from Rare Endpoint - N/A
Device / Suspicious Domain - T1189, T1566.002
References
https://threatfox.abuse.ch/browse/malware/win.isfb/
https://www.cisa.gov/news-events/cybersecurity-advisories/aa22-216a
%201%20(1).avif)
