CVE-2026-57869 in MicroRealEstate
Summary
by MITRE • 07/07/2026
Broken object-level access controls and the use of a deterministic pattern during random ID generation in MicroRealEstate allows attackers to access documents uploaded by landlords or tenants without authorization.
This issue affects MicroRealEstate: through 1.0.0-alpha3.
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Analysis
by VulDB Data Team • 07/07/2026
This vulnerability represents a critical access control flaw that undermines the fundamental security posture of the MicroRealEstate platform. The system's object-level access controls have been compromised, allowing unauthorized users to gain access to sensitive documents uploaded by landlords and tenants. This weakness stems from the predictable nature of the random ID generation algorithm used within the application, creating a deterministic pattern that attackers can exploit to navigate the system's document repository.
The technical implementation of this vulnerability involves the use of non-cryptographically secure random number generators or predictable seeding mechanisms during ID creation processes. When applications generate identifiers using such methods, they create sequences that can be reverse-engineered or guessed by malicious actors. This flaw directly maps to CWE-330, which addresses the use of insufficiently random values in security-sensitive contexts. The deterministic pattern allows attackers to systematically enumerate valid document IDs without requiring legitimate authentication credentials.
The operational impact of this vulnerability extends beyond simple unauthorized access to encompass potential data breaches involving sensitive personal and financial information. Landlords and tenants may have their private documents including lease agreements, identification documents, financial records, and communication logs exposed to unauthorized parties. This creates significant privacy violations and potential legal implications for the platform operator. The attack surface becomes particularly dangerous when considering that multiple users can access each other's data through simple pattern recognition or brute force techniques.
From an adversarial perspective, this vulnerability aligns with ATT&CK technique T1078 which covers legitimate credentials usage and privilege escalation through unauthorized access to system resources. Attackers can leverage this flaw to perform reconnaissance activities, gather intelligence about users, and potentially escalate their privileges within the system. The deterministic ID generation pattern creates a predictable attack vector that requires minimal computational resources to exploit effectively.
Mitigation strategies should focus on implementing cryptographically secure random number generators for all identifier creation processes, particularly those related to document storage and access control. Organizations must ensure that generated IDs are sufficiently long and unpredictable to prevent enumeration attacks. Additional controls should include proper access control enforcement at the application layer, implementation of role-based access control mechanisms, and regular security testing of ID generation algorithms. The platform should also implement rate limiting and monitoring for suspicious access patterns to detect potential exploitation attempts. Compliance with security standards such as NIST SP 800-90A for random number generation and OWASP Top Ten protections against insecure design practices would significantly reduce the risk exposure from this vulnerability class.
The vulnerability demonstrates how seemingly minor implementation flaws in core system components can create substantial security risks. Proper input validation, secure coding practices, and adherence to established security frameworks are essential for preventing such issues in future development cycles. Regular penetration testing and code reviews focusing on random number generation and access control mechanisms would help identify similar weaknesses before they can be exploited by malicious actors.