CVE-2026-13069 in MongoDB
Summary
by MITRE • 07/22/2026
An authenticated user can cause excessive CPU consumption or out-of-memory conditions on a MongoDB server by sending a crafted Queryable Encryption find payload containing an unvalidated field used to control an internal computation loop. The resulting resource exhaustion degrades availability for other operations.
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Analysis
by VulDB Data Team • 07/22/2026
This vulnerability represents a critical resource exhaustion flaw in MongoDB's queryable encryption implementation that can be exploited through authenticated user sessions. The technical weakness stems from insufficient validation of user-supplied data within the encryption framework, specifically targeting fields that control internal computation loops during query processing. When an authenticated attacker crafts a malicious find payload containing unvalidated fields, the system processes these inputs without adequate bounds checking or sanitization, leading to uncontrolled resource consumption patterns.
The operational impact of this vulnerability extends beyond simple performance degradation to potentially complete service disruption through either excessive cpu utilization or memory exhaustion. Attackers can construct queries that trigger iterative processing loops within MongoDB's encryption layer, causing the server to consume disproportionate system resources. This type of attack directly violates the principle of least privilege and resource isolation, as legitimate operations become starved of computational resources while malicious payloads consume system capacity.
The vulnerability aligns with CWE-400, which catalogs improper resource management issues, and demonstrates characteristics consistent with CWE-254, representing security weaknesses in resource management. From an attack framework perspective, this flaw maps to techniques described in the MITRE ATT&CK matrix under T1496 for resource exhaustion attacks and potentially T1078 for legitimate credential abuse. The authenticated requirement reduces the attack surface but does not eliminate the threat since compromised accounts or insider threats could exploit this weakness.
MongoDB's queryable encryption feature introduces additional complexity to the data processing pipeline by requiring encryption and decryption operations to occur during query execution, creating multiple potential entry points for malicious input manipulation. The vulnerability specifically targets internal computation loops that are designed to handle legitimate user requests but become exploitable when attacker-controlled fields control loop parameters or iteration counts. This design flaw demonstrates inadequate input validation and bounds checking mechanisms within the encryption subsystem.
Mitigation strategies should include implementing strict parameter validation for all fields used in internal computation loops, establishing resource limits and timeouts for query processing operations, and applying the principle of least privilege to encryption key management. Database administrators should consider implementing monitoring solutions that can detect unusual resource consumption patterns and establish automated alerting for potential exploitation attempts. The most effective long-term solution involves updating MongoDB implementations to include comprehensive input validation and bounds checking for all user-controlled parameters within encryption processing pipelines, ensuring that loop parameters cannot be manipulated to cause unbounded resource consumption.
Organizations should conduct thorough security assessments of their database environments to identify similar vulnerabilities in other encryption or decryption components, as this pattern of flawed resource management could exist in related systems. Regular vulnerability scanning and penetration testing should specifically target encryption frameworks to identify potential exploitation vectors before they can be leveraged by malicious actors. The security community should also consider this vulnerability as a case study for implementing proper input validation in complex cryptographic systems where user-supplied data interacts with internal processing loops.