cosmopolitan.com Domain Breach Exposure Report
Risk Score
Massive event volume or critical assets compromised.
AI Findings Summary
The domain cosmopolitan.com has experienced a significant number of data breaches, totaling 1241 events, and 106 infostealer events over the period of July 2025 to June 2026. The majority of these events, 92.1%, are historical data breaches, while 7.9% are active infostealer logs. A notable surge in employee-related events occurred in January 2026, with 799 incidents, followed by a rise in client-related events in March 2026 (89 incidents). Malware families associated with these events include Redline (9.4%), LummaC2 (6.6%), Acreed (1.9%), and Rhadamanthys (0.9%). The data suggests a high risk of credential compromise and potential data exfiltration, impacting both employees and clients. The primary sources of leaked data appear to be database dumps (67.9%) and combolist sources (32.1%).
Total Events
Employee Affected Events
Client Affected Events
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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
952 compromised employee accounts pose an infrastructure risk, while 395 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.