anthropologie.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 anthropologie.com, with 12,079 historical data breaches and 817 active infostealer logs observed over the period of July 2025 to June 2026. The majority of these events, 93.7%, are attributed to historical data breaches, while 6.3% are active infostealer logs. A notable surge in employee-related events occurred in January 2026, with 5,342 incidents, alongside a substantial increase in client-related events in March 2026, totaling 2,219. Malware families such as Redline, LummaC2, and Rhadamanthys are prevalent, suggesting a focus on credential harvesting and data exfiltration. The data originates primarily from combolist sources and database dumps, with the United States being the most frequently observed geography.
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
5,772 compromised employee accounts pose an infrastructure risk, while 7,124 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.