metrolyrics.com Domain Breach Exposure Report
Risk Score
Massive event volume or critical assets compromised.
AI Findings Summary
The domain metrolyrics.com has experienced a significant number of data breaches and infostealer events over the past year, with 544 historical data breaches and 111 active infostealer logs. The majority of these exposures, 83.1%, are attributed to historical data breaches, while 16.9% are linked to active infostealer logs. The timeline shows a notable increase in both employee and client exposures starting in September 2025, peaking in April 2026 with 68 employee and 123 client exposures. Malware families such as Redline and LummaC2 are present, and the data indicates that 97.6% of leaks originate from combolist sources, suggesting credential stuffing or account takeover attempts. The primary targeted service is metrolyrics.com itself, with a concentration of exposures 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
141 compromised employee accounts pose an infrastructure risk, while 514 leaked client credentials create regulatory liability.
Antivirus Distribution
Security Tools on Infected Endpoints
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.