bloglovin.com Domain Breach Exposure Report
Risk Score
Massive event volume or critical assets compromised.
AI Findings Summary
The telemetry indicates a significant exposure event impacting bloglovin.com, with a total of 137,911 recorded events over the period of July 2025 to June 2026. The majority of these events, 85.4%, are attributed to historical data breaches, affecting 117,723 clients. Additionally, 20,188 infostealer events were observed, representing 14.6% of the total. Employee exposure is relatively low with 170 affected individuals, but client impact is substantial. The timeline shows a surge in client-related events starting in September 2025, peaking in March and April 2026, coinciding with increased employee exposure. Malware families like LummaC2, Rhadamanthys, and Redline are prominent in the infostealer logs, suggesting active credential harvesting and data exfiltration attempts targeting the bloglovin.com service.
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
170 compromised employee accounts pose an infrastructure risk, while 137,741 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.