UpGuard Uncovers Massive Data Exposure at India’s Largest Real Estate Platform.

Leave a Comment / Cybersecurity, Data Protection, Enterprise Technology, Industry News / By cxojunction

A major security lapse has exposed one of the largest known AI-related data leaks after an unauthenticated server connected to India’s largest real estate platform left millions of sensitive customer and employee records accessible online.

The exposed system was a Model Context Protocol (MCP) server, an emerging technology that enables AI assistants to connect with databases and external tools. While MCP itself is not inherently vulnerable, servers deployed without authentication can expose the data they access. In this case, an internet-facing DBHub instance provided unrestricted access to Square Yards’ internal databases, marking the largest reported exposure of sensitive personal information linked to an unauthenticated MCP server.

UpGuard researchers discovered the publicly accessible DBHub MCP server on May 28, 2026, and notified Square Yards the following day after confirming the presence of sensitive information. The company secured the exposed database shortly afterward but did not respond to UpGuard’s disclosure.

The database contained 2,178 tables totaling more than 650 GB of data, covering customer relationship management, HR and payroll, property transactions, KYC documentation, broker management, and financial payouts. Samples showed the database was actively updated and contained records spanning several years.

Impact

The exposed records included extensive personal information belonging to both customers and employees.

Customer datasets contained millions of lead records with names, phone numbers, and email addresses. Individuals involved in property transactions had additional information exposed, including PAN, Aadhaar, and passport numbers, along with CIBIL credit scores and financial details collected during KYC verification.

Employee records were equally sensitive. A users table with over 124,000 entries included employee names, API access tokens, and hashed passwords. The employee table stored personal details such as names, addresses, dates of birth, and email addresses. More concerning, the candidate_joining_information table contained Aadhaar numbers, PAN numbers, passport details, and bank account numbers in plaintext. Other records also exposed employee payout information and internal leadership feedback.

Risks

The combination of identity documents and financial information creates significant risks of identity theft, financial fraud, and unauthorized account creation.

Combined with names, contact information, employer details, property transaction history, salaries, and credit scores, the exposed data could also enable highly targeted phishing attacks and convincing impersonation attempts, increasing the likelihood of financial scams.

Recommendations

Researchers said the incident resulted from a configuration error rather than a vulnerability in MCP or DBHub. Organizations should secure MCP deployments by enabling authentication, restricting public access through network controls, and applying the same security standards used for internet-facing APIs and cloud services.

Continuous monitoring of external assets is equally important, as publicly exposed MCP servers can often be identified and secured before attackers exploit them.

Conclusion

The Square Yards incident highlights how AI integration is creating new security challenges. As MCP servers become increasingly important for connecting AI assistants with enterprise data, organizations must ensure they are protected with authentication, network segmentation, least-privilege access, logging, and continuous monitoring. Applying these established security practices to AI infrastructure will be critical to preventing future large-scale data exposures.

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Source: Open House: How an Unauthenticated MCP Server Exposed India’s Largest Real Estate Platform | UpGuard | https://www.upguard.com/breaches/open-house-how-an-unauthenticated-mcp-server-exposed-indias-largest-real-estate-platform