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high threat

FIN7 DGA Command and Control Behavior Detection

This rule detects command and control activity associated with the FIN7 threat group, which is known to use domain generation algorithms (DGA) to maintain persistence in their target's network by identifying network traffic using TLS or HTTP protocols to domains with a specific pattern.

This threat brief focuses on detecting command and control (C2) behavior associated with the FIN7 threat group, known for its financially motivated cybercrimes. FIN7 employs domain generation algorithms (DGAs) to create numerous domain names, allowing them to maintain persistent communication channels with compromised hosts, even if some domains are blocked or sinkholed. This technique is a key element in their operational security, enabling them to evade traditional detection methods and sustain long-term access to victim networks. The domains generated by the DGA follow a specific pattern, aiding in their identification. Defenders must recognize and mitigate this DGA-based C2 activity to disrupt FIN7’s operations. The campaign has been observed since at least 2018.

Attack Chain

  1. Initial compromise occurs through an as-yet unspecified vector.
  2. Malware is deployed on the victim machine, establishing persistence.
  3. The malware executes a DGA to generate a list of potential C2 domain names.
  4. The malware attempts to resolve the generated domain names via DNS queries.
  5. Upon successful resolution, the malware initiates a TCP connection to the C2 server using either HTTP or TLS.
  6. The compromised host establishes a secure communication channel with the C2 server for command execution and data exfiltration.
  7. FIN7 operators use the C2 channel to deliver additional payloads, conduct lateral movement, and steal sensitive information.
  8. Exfiltrated data is used for financial gain, such as fraudulent transactions or sale on the dark web.

Impact

Successful exploitation and C2 establishment can lead to significant financial losses, data breaches, and reputational damage. FIN7’s targeting is global, affecting organizations across various sectors, including retail, hospitality, and finance. A successful attack can result in the theft of sensitive financial data, disruption of business operations, and significant recovery costs. Historical incidents attributed to FIN7 have resulted in millions of dollars in losses for victim organizations.

Recommendation

  • Deploy the Sigma rule Detect FIN7 DGA Domains to your SIEM to identify potential C2 communication attempts.
  • Inspect network traffic logs for outbound connections to domains matching the pattern described in the rule query (destination.domain:/[a-zA-Z]{4,5}\.(pw|us|club|info|site|top)/) .
  • Whitelist legitimate domains like zoom.us in your detection rules to reduce false positives.
  • Enable network traffic logging (logs-network_traffic.*) and PAN-OS logs (logs-panw.panos*) to provide the necessary data sources for the detection rules.
  • Monitor DNS queries for resolutions to suspicious domains, as this is a key step in the DGA process.

Detection coverage 3

Detect FIN7 DGA Domains

high

Detects network traffic to domains generated by a FIN7-associated domain generation algorithm (DGA).

sigma tactics: command_and_control techniques: T1071.001, T1568.002 sources: network_connection, windows

Detect FIN7 DGA TLS Connections

high

Detects TLS connections to domains generated by a FIN7-associated domain generation algorithm (DGA).

sigma tactics: command_and_control techniques: T1071.001, T1568.002 sources: network_connection, windows

Detect FIN7 DGA HTTP Connections

high

Detects HTTP connections to domains generated by a FIN7-associated domain generation algorithm (DGA).

sigma tactics: command_and_control techniques: T1071.001, T1568.002 sources: network_connection, windows

Detection queries are kept inside the platform. Get full rules →