google.com.ly Domain Breach Exposure Report
Risk Score
Massive event volume or critical assets compromised.
AI Findings Summary
The domain google.com.ly has been associated with a significant number of historical data breaches (310 events) and active infostealer logs (112 events) over the past year, indicating a high risk of credential compromise. The majority of these events, 73.5%, are attributed to historical data breaches, with the remaining 26.5% being active infostealer logs. The timeline shows a notable increase in employee and client-related events starting in March 2026, with a peak in April 2026, suggesting a period of heightened exploitation. Malware families such as Redline and LummaC2 were observed, commonly associated with credential theft. The exposure primarily targets services related to Google login and home pages, with a concentration of affected users in the United States.
Total Events
Employee Affected Events
Client Affected Events
Free Community Account
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12-Month Events Timeline
Event volume by breach date, employee VS client
Infostealers VS Data Breaches
Live stealer logs VS data breaches
135 compromised employee accounts pose an infrastructure risk, while 287 leaked client credentials create regulatory liability.
Antivirus Distribution
Security Tools on Infected Endpoints
No Data Available
Malware Families Distribution
Distribution of Active Stealer Strains
Top Login URLs
Top exposed services found in the event results
Infostealer By Geography
Shows the distribution of Infostealer-related credential exposure events across different geographic regions. The location is determined by analyzing the metadata of the infected machines associated with each event.
Country Breakdown
Services Classification Distribution
Blast radius - closer to core = more critical infrastructure, size = credential volume
Operating System Distribution
Distribution of compromised endpoint builds
Leak Repository Classification
Where the exposed records currently reside
Disclaimer: This report includes AI-generated content. AI can make mistakes, so verify important findings independently before taking action.