tiu.ru Domain Breach Exposure Report
Risk Score
Massive event volume or critical assets compromised.
AI Findings Summary
The domain tiu.ru has experienced a significant exposure event with a risk score of 81, primarily driven by 3,034 historical data breaches and 649 active infostealer logs. The timeline indicates a surge in client-related events starting in August 2025 and peaking in March 2026, with employee-related events also increasing during this period. Malware families such as Redline, Vidar, and Rhadamanthys are prevalent, suggesting credential harvesting and data exfiltration. The exposure is heavily concentrated in Russia, Estonia, and the United States, with targeted services including sign-in pages for my.tiu.ru and join-now pages for tiu.ru. The leak repository classification indicates that 98.3% of the exposure originates from combolist sources, highlighting a risk of credential stuffing attacks against users who reuse passwords.
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
160 compromised employee accounts pose an infrastructure risk, while 3,523 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.