Ransom.Win32.LOCKBIT.YEBGW is a ransomware variant linked to the LockBit family, a group notorious for high-impact cyberattacks worldwide. Although its current distribution is limited (rated Low risk), its encryption capabilities pose a High damage potential, particularly in enterprise environments. This analysis provides actionable insights for security teams, covering infection vectors, detection rules, and mitigation strategies.
Infection Mechanisms and Behavioral Patterns
The malware primarily spreads through two methods: being dropped by other malware (e.g., loaders or trojans) or via user-initiated downloads from compromised websites. Once executed, it encrypts files while strategically excluding certain extensions—likely to maintain system stability for ransom negotiations. Post-encryption, it deletes itself to evade forensic analysis, a hallmark of LockBit’s operational security.
Detection and Indicators of Compromise (IOCs)
Security teams can leverage the following YARA/Sigma rule to detect file drops associated with Ransom.Win32.LOCKBIT.YEBGW:
title: Ransom.Win32.LOCKBIT.YEBGW File Detection
description: Detects ransomware file drops
author: Threat Intel
logsource:
product: windows
service: file_event
detection:
selection:
OriginalFileName|contains:
- 'Lockbit'
- 'YEBGW'
condition: selection
Key IOCs include aliases such as Ransom:Win32/Lockbit.AA!MTB (Microsoft) and W32/Lockbit.C2F8!tr.ransom (Fortinet). For additional context, refer to Trend Micro’s Threat Encyclopedia.
Mitigation and Proactive Defense
To mitigate risks, organizations should prioritize patch management, user training to prevent phishing-driven downloads, and maintain offline backups. Law enforcement disruptions of LockBit’s infrastructure in February 2024 (Europol) highlight the need for continuous monitoring of emerging variants like YEBGW.
Conclusion
While Ransom.Win32.LOCKBIT.YEBGW currently exhibits low prevalence, its alignment with LockBit’s destructive framework warrants vigilance. Security teams should monitor for behavioral anomalies and update detection rules to reflect evolving TTPs.
