CVE-2026-13072 in Server
Summary
by MITRE • 07/22/2026
When compute mode is enabled on a standalone mongod instance, insufficient validation of externally sourced BSON data during aggregation pipeline processing can result in memory corruption, potentially leading to process termination or other unintended behavior. This configuration is non-default and requires explicit enablement at startup.
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Analysis
by VulDB Data Team • 07/22/2026
This vulnerability occurs within the mongodb database system when compute mode is explicitly enabled on a standalone mongod instance, representing a critical security weakness that stems from inadequate validation of externally sourced data during aggregation pipeline operations. The flaw exists specifically in how the system processes bson formatted data that originates from external sources, creating a pathway for memory corruption that can manifest as process termination or unpredictable system behavior. The vulnerability requires a specific configuration state to be exploitable, making it non-default and dependent on explicit administrator action during system initialization, yet this targeted nature does not diminish its potential impact on database security.
The technical implementation of this flaw involves the aggregation pipeline processing mechanism failing to properly validate input data structures when compute mode is active, allowing malformed or malicious bson payloads to traverse the validation layers and directly influence memory management operations within the mongod process. This represents a classic buffer overread or memory corruption vulnerability that can be leveraged to execute arbitrary code or cause denial of service conditions, with the attack surface expanding significantly when external data sources are involved in aggregation operations. The issue specifically manifests during pipeline execution phases where bson documents are processed and transformed, creating opportunities for attackers to craft malicious inputs that bypass existing validation checks.
From an operational perspective, this vulnerability presents significant risks to database availability and integrity, particularly in environments where external data integration occurs through aggregation pipelines. The potential impact extends beyond simple service disruption to include possible privilege escalation scenarios and data exposure, especially when combined with other vulnerabilities within the mongodb ecosystem. Organizations utilizing compute mode configurations face heightened risk profiles, as this vulnerability essentially creates an attack vector that allows remote code execution or complete system compromise without requiring authentication for the initial exploitation phase.
Mitigation strategies should focus on immediate configuration review to disable compute mode on standalone instances where it is not strictly required, implementing strict input validation at multiple layers of the data processing pipeline, and establishing comprehensive monitoring for unusual aggregation behavior patterns. Security teams should also consider implementing network segmentation controls to limit external access to mongo instances and deploy intrusion detection systems capable of identifying anomalous bson payload patterns that may indicate exploitation attempts. The vulnerability aligns with CWE-129 and CWE-787 categories related to insufficient input validation and buffer overflow conditions, while also mapping to ATT&CK techniques involving privilege escalation and execution through database systems.
Organizations should prioritize patching affected versions of mongodb and implementing configuration management policies that explicitly prevent compute mode activation on standalone instances without proper security controls in place. Regular security assessments should include verification of compute mode usage across all database deployments, with particular attention to aggregation pipeline configurations that process external data sources. Additionally, incident response procedures should incorporate specific detection criteria for memory corruption indicators during aggregation operations, as these may serve as early warning signs of exploitation attempts targeting this vulnerability class.