morningstar.com Domain Breach Exposure Report
Risk Score
Massive event volume or critical assets compromised.
AI Findings Summary
The telemetry indicates a significant exposure event affecting morningstar.com, with a total of 45,247 recorded events between July 2025 and June 2026. The majority of these events, 87.7%, are classified as historical data breaches, impacting 39,695 entities, while 12.3% are active infostealer logs, affecting 5,552 entities. The timeline shows a sharp increase in employee and client-related events in January 2026, suggesting a potential peak in compromise activity during that period. The data also highlights the prevalence of infostealer malware families such as Redline, LummaC2, and Rhadamanthys, commonly associated with credential harvesting. The primary sources of leaked data appear to be combolist sources and database dumps, indicating a high risk of credential stuffing and account takeover.
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
11,056 compromised employee accounts pose an infrastructure risk, while 34,191 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.