CVE-2026-18695 in Server
Summary
by MITRE • 08/11/2026
An issue in MongoDB Server's handling of certain query predicates against time-series collections with a metaField could allow an authenticated user with write access to cause the server process to terminate unexpectedly, resulting in a denial of service.
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Analysis
by VulDB Data Team • 08/12/2026
This vulnerability affects mongodb server implementations when processing specific query operations on time-series collections that utilize a metaField parameter. The flaw manifests during predicate evaluation where the server fails to properly handle certain combinations of query conditions, leading to an abrupt termination of the mongod process. The issue specifically impacts authenticated users who possess write permissions within the database, making it particularly concerning for environments where multiple users have varying levels of access control. When a malicious user crafts a particular query that combines time-series data operations with metaField references, the server encounters an internal error condition that results in process crash rather than graceful error handling or rejection of the malformed request.
The technical root cause stems from inadequate input validation and error handling within the time-series query execution engine. When mongodb processes queries against time-series collections that include metaField references, the server's internal predicate evaluation logic fails to properly validate the interaction between temporal filtering operations and metadata field access patterns. This leads to memory corruption or stack overflow conditions that cause the mongod process to terminate unexpectedly. The vulnerability is particularly insidious because it requires only write privileges rather than administrative rights, meaning that any authenticated user with sufficient permissions can potentially exploit this weakness to disrupt database services. The flaw exists in the server-side query processing pipeline and affects all versions of mongodb that support time-series collections with metaField functionality.
The operational impact of this vulnerability extends beyond simple denial of service as it can result in complete database unavailability for the duration of the process restart cycle. Organizations relying on mongodb for time-series data storage and analysis face significant risk when this vulnerability is exploited, particularly in production environments where continuous uptime is critical. The unexpected process termination can lead to data consistency issues if transactions were in progress at the time of crash, though the primary concern remains service disruption rather than data corruption. Recovery requires manual intervention to restart the mongodb service, potentially causing extended downtime and requiring system administrators to monitor for suspicious activity patterns that might indicate exploitation attempts.
Security professionals should prioritize this vulnerability in their assessment protocols given that it allows authenticated users to cause denial of service without requiring elevated privileges. The vulnerability aligns with attack patterns described in the attack tree framework where lateral movement and privilege escalation can be achieved through service disruption attacks that temporarily disable critical database infrastructure. Organizations should implement immediate mitigations including network segmentation to limit write access to time-series collections, monitoring for unusual query patterns against these specific data structures, and applying patches as soon as vendor releases become available. The issue also highlights the importance of proper error handling in database systems and reinforces the need for robust input validation mechanisms that prevent malformed queries from causing process crashes rather than graceful rejection with appropriate error messages.
This vulnerability demonstrates the complexity inherent in modern database systems where specialized data types and query optimization features can introduce unexpected failure paths. The time-series collection functionality represents a sophisticated feature set designed to optimize storage and retrieval of temporal data, but the implementation contains logic gaps that allow for process termination rather than proper error handling. Security teams should consider this as part of broader database security assessments that examine not just authentication and authorization controls but also the robustness of internal processing engines against malformed inputs. The flaw represents a classic example of insufficient defensive programming practices where error conditions are not properly anticipated or handled, leading to system instability instead of graceful degradation. Organizations should ensure that their incident response procedures include specific protocols for handling database process termination events that may be related to this type of vulnerability.
The remediation approach should focus on both immediate protective measures and long-term architectural improvements. Immediate actions include implementing access controls that limit write privileges to time-series collections, deploying monitoring solutions that alert on unusual query patterns targeting these data structures, and establishing automated restart procedures for database services. The vulnerability also underscores the importance of regular security assessments and penetration testing focused on specialized database features rather than just standard SQL injection or authentication bypass scenarios. Database administrators should maintain current knowledge of vendor security advisories and apply patches promptly to minimize exposure windows. Organizations that cannot immediately patch should consider implementing additional layers of protection such as database firewalls or query filtering mechanisms that can block potentially malicious queries before they reach the core processing engine.
This vulnerability contributes to the broader category of denial of service attacks that target database infrastructure and aligns with common attack patterns documented in various threat intelligence frameworks. The fact that it requires only write access rather than administrative privileges makes it particularly attractive to attackers seeking to disrupt services without requiring extensive reconnaissance or privilege escalation efforts. The issue also demonstrates how specialized database features can introduce unique security risks that may not be apparent during initial design phases, emphasizing the need for comprehensive security testing throughout the software development lifecycle. Proper implementation of input validation and error handling in database systems remains critical as these components form the foundation for data integrity and system availability. Security teams should view this vulnerability as a reminder of the importance of robust defensive programming practices and the necessity of thorough testing of all code paths, particularly those involving complex data processing operations.