CVE-2026-118510 in Laravel MongoDB
Summary
by MITRE • 10/28/2026
A type-handling flaw in the relationship query building of this MongoDB integration library can cause a check for the absence of a related record to be compiled with an identifier of the wrong data type. In an application that relies on such a check to decide which documents a request may see or act on, a user with basic privileges may be served, may change, or may remove documents that the check was intended to withhold. The failure is silent and produces no error.
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Analysis
by VulDB Data Team • 10/28/2026
The vulnerability described constitutes a critical type-handling flaw within the query construction logic of a MongoDB integration library, specifically affecting how relationships between data entities are queried. This issue arises when the system attempts to verify the absence or presence of related records by compiling a database query that includes an identifier field. Due to improper handling of data types during this compilation process, the resulting query may utilize an incorrect type for the identifier value being compared against stored documents in MongoDB. In many cases, this involves a mismatch between string representations and object identifiers (OIDs), or vice versa, which is particularly dangerous because MongoDB's query engine performs strict equality checks that can yield unexpected results when types do not match exactly as intended by the application logic.
From a technical perspective, this flaw allows for silent failures where no error message or exception is thrown to alert developers or system administrators of the misconfiguration. When an application relies on these relationship queries to enforce access control policies—such as determining whether a user has permission to view, modify, or delete specific documents—the incorrect type in the query can lead to false positives or negatives in authorization checks. For instance, if the library incorrectly casts a string identifier into a format that MongoDB interprets differently than an object ID, the database might return results indicating that no related record exists when one actually does, or vice versa. This discrepancy bypasses the intended security controls because the application logic proceeds based on flawed data returned from the database layer without any indication of the underlying error.
The operational impact of this vulnerability is severe, particularly in applications where document visibility and mutability are strictly governed by relationship-based permissions. A user with basic or low-level privileges could potentially access documents they should not see, alter records outside their authorized scope, or even delete critical data that was meant to be protected from them. Since the failure mode is silent, there is no immediate feedback loop for security monitoring systems or intrusion detection mechanisms to flag these unauthorized actions as anomalous based on query errors. This makes exploitation difficult to detect in real-time and allows attackers to escalate privileges or exfiltrate sensitive information over extended periods without triggering standard alerting thresholds associated with failed authentication or authorization attempts.
To mitigate this risk, developers must ensure that all identifiers passed into relationship queries are strictly typed according to the schema definitions expected by MongoDB. This involves validating input data types before constructing query objects and ensuring consistent use of ObjectIds versus strings throughout the application layer. Implementing strict type checking in the integration library or wrapping database calls with explicit casting mechanisms can prevent these mismatches. Additionally, adopting a defense-in-depth strategy is crucial; applications should not rely solely on single-point authorization checks performed via complex relationship queries but should also validate permissions at multiple layers of the stack. Regular security audits focusing on data access patterns and query construction logic are recommended to identify similar type-handling weaknesses before they can be exploited in production environments.
This vulnerability aligns with CWE-20, Improper Input Validation, as it stems from a failure to correctly interpret or validate the data types provided during query execution. It also relates to CWE-697, Incorrect Comparison, because the core issue lies in how values are compared within the database engine due to type discrepancies. From an offensive security perspective, this flaw can be leveraged through ATT&CK technique T1078, Valid Accounts, as it allows attackers with legitimate but limited credentials to bypass access controls and perform actions reserved for higher-privileged users or unauthorized entities. The silent nature of the failure further complicates incident response, emphasizing the need for comprehensive logging that captures not just successful queries but also their parameters and return values to detect subtle deviations in expected behavior.