CVE-2026-93760 in Mongoid
Summary
by MITRE • 09/18/2026
Mongoid does not restrict which query operators may come from caller-supplied filter data when an application hands that data to its query-building methods. In an application that forwards externally supplied filter parameters in this way, a party with no credentials may influence how the database evaluates the query. This may result in unintended disclosure of stored field values and in reduced database performance.
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Analysis
by VulDB Data Team • 09/18/2026
The vulnerability described involves a critical insecure direct object reference or injection flaw within the Mongoid Object-Document Mapper for Ruby applications. The core technical issue stems from the failure to sanitize or restrict specific query operators that are derived directly from user-supplied input data before being passed into database query construction methods. In typical web application architectures, filter parameters such as search terms, sort orders, or pagination limits often originate from HTTP request headers, query strings, or JSON bodies submitted by clients. When an application blindly forwards these externally supplied values to Mongoid without validating the allowed set of operators, it creates a pathway for attackers to manipulate the underlying MongoDB queries executed against the database backend.
This lack of input validation allows unauthenticated actors to inject arbitrary MongoDB query operators into the filter criteria. By manipulating fields such as $where, $regex, or comparison operators like $gt and $lt in unexpected ways, an attacker can alter the logic of how the database evaluates the search conditions. This capability effectively bypasses intended access controls because the application assumes that the structure of the query is safe simply because it was generated by its own code, failing to recognize that the content within those structures has been tampered with by a malicious client. The result is a form of NoSQL injection where the attacker gains significant control over data retrieval operations without possessing valid authentication credentials for the application itself.
The operational impact of this vulnerability is twofold, affecting both confidentiality and availability. On the side of confidentiality, an attacker can exploit these manipulated queries to perform unauthorized data disclosure. By crafting specific query payloads, it may be possible to extract stored field values that were not intended to be visible to unauthenticated users, such as internal identifiers, sensitive personal information, or administrative flags. This leads to a direct violation of the principle of least privilege and results in unintended exposure of private data. Furthermore, if the application logic relies on these queries for access control decisions, bypassing them could lead to further escalation of privileges within the system context.
Regarding availability and performance, the exploitation of this vulnerability can significantly degrade database performance. Attackers can construct complex or computationally expensive query expressions that force the MongoDB engine to perform full collection scans or execute resource-intensive operations like JavaScript evaluation via $where operators. This leads to increased CPU usage, memory consumption, and latency for all users interacting with the application. In severe cases, this constitutes a denial of service condition where legitimate traffic is starved of resources due to the maliciously crafted queries consuming excessive backend processing power. The reduced database performance impacts the overall responsiveness and stability of the hosted services.
From a classification perspective, this vulnerability aligns closely with CWE-943 Improper Neutralization of Special Elements used in an SQL Command or its NoSQL equivalent, often categorized under CWE-564 if considered as HTTP Parameter Pollution leading to injection, but more accurately fits CWE-770 Allocation of Resources Without Limits or Throttling when focusing on the performance aspect, and CWE-284 Improper Access Control regarding the unauthorized data disclosure. In terms of the MITRE ATT&CK framework, this behavior corresponds to T1190 Exploit Public-Facing Application, specifically leveraging injection techniques against a database interface exposed through an application layer. The attack vector is typically Network with Low Complexity and requires no user interaction beyond submitting malicious HTTP requests, placing it at High severity in terms of exploitability despite the lack of authentication requirements for the initial access step.
To mitigate this vulnerability, developers must implement strict allow-listing strategies for all query operators that are derived from external input. Instead of passing raw user-supplied strings directly into Mongoid query methods, applications should map these inputs to predefined, safe operations or validate them against a whitelist of permitted values and structures. Input validation should occur at the application layer before any data reaches the database abstraction layer. Additionally, employing parameterized queries where supported by the ORM can help separate code from data, although in NoSQL contexts this is often less straightforward than in SQL environments. Implementing rate limiting on API endpoints that accept complex filter parameters can also reduce the risk of successful exploitation and mitigate performance impacts. Regular security testing including dynamic application security testing focused on injection flaws is essential to detect such misconfigurations before they are exploited in production environments.