CVE-2026-1850: MongoDB Query Planner DoS Vulnerability

CVE-2026-1850 Overview

A resource exhaustion vulnerability exists in MongoDB's Query Planner component that can lead to an Out-Of-Memory (OOM) crash when processing complex queries. The vulnerability is classified under CWE-770 (Allocation of Resources Without Limits or Throttling), indicating that the Query Planner fails to properly limit memory allocation during query planning operations, allowing specially crafted complex queries to consume excessive system memory.

Critical Impact

Authenticated attackers with network access can cause MongoDB instances to crash through memory exhaustion, resulting in denial of service conditions affecting database availability.

Affected Products

• MongoDB Server (specific versions pending vendor confirmation)

Discovery Timeline

• 2026-02-10 - CVE CVE-2026-1850 published to NVD
• 2026-02-10 - Last updated in NVD database

Technical Details for CVE-2026-1850

Vulnerability Analysis

This vulnerability resides in MongoDB's Query Planner, the component responsible for analyzing queries and determining optimal execution strategies. When processing complex queries with numerous conditions, joins, or nested structures, the Query Planner allocates memory to evaluate potential execution plans. The flaw occurs because the planner lacks adequate safeguards to limit memory consumption during this evaluation phase.

The attack requires low privileges (authentication required) but no user interaction, making it exploitable by any authenticated database user with query execution permissions. The impact is limited to availability—there is no direct path to data confidentiality or integrity compromise, but the denial of service condition can be severe for production environments relying on MongoDB for critical operations.

Root Cause

The root cause is CWE-770: Allocation of Resources Without Limits or Throttling. The MongoDB Query Planner does not implement sufficient memory bounds checking when evaluating complex query plans. This allows the planning algorithm to allocate unbounded amounts of memory when processing queries with high combinatorial complexity, such as those with many OR conditions, deeply nested documents, or multiple index candidates requiring evaluation.

Attack Vector

The attack is network-based and requires only low-level privileges (authenticated access). An attacker with valid MongoDB credentials can submit specially crafted queries designed to trigger excessive memory allocation in the Query Planner. These queries exploit the combinatorial explosion of possible query plans that the planner must evaluate.

The attack does not require user interaction and can be executed remotely against any network-accessible MongoDB instance. The attacker constructs queries with characteristics known to increase planning complexity—such as numerous alternative conditions, complex aggregation pipelines, or queries that force evaluation of many index combinations. When the Query Planner attempts to process these queries, it exhausts available memory and causes the MongoDB process to crash.

Technical details and tracking information are available via the MongoDB Issue Tracker Entry.

Detection Methods for CVE-2026-1850

Indicators of Compromise

• Sudden MongoDB process termination with OOM (Out-Of-Memory) error messages in logs
• Unusual spike in memory consumption by mongod process preceding crashes
• Query logs showing unusually complex queries with many conditions or deeply nested structures
• Repeated service restarts or recovery operations in MongoDB replica sets

Detection Strategies

• Monitor MongoDB server memory usage patterns and establish baseline thresholds for alerting
• Implement query profiling to identify and log queries exceeding complexity thresholds
• Configure system-level OOM killer logging to capture MongoDB process terminations
• Review slow query logs for queries with excessive planning time or resource consumption

Monitoring Recommendations

• Enable MongoDB profiler at level 1 or 2 to capture slow operations and analyze query patterns
• Implement real-time memory monitoring with alerts at 80% and 90% utilization thresholds
• Configure centralized logging to aggregate MongoDB logs for anomaly detection
• Monitor replica set health metrics for unexpected primary elections caused by OOM crashes

How to Mitigate CVE-2026-1850

Immediate Actions Required

• Apply vendor patches as soon as they become available from MongoDB
• Implement query complexity limits using MongoDB's maxTimeMS parameter to prevent long-running queries
• Review and restrict database user privileges to limit query execution capabilities where possible
• Consider implementing connection-level resource limits using MongoDB's configuration options

Patch Information

Patch information is being tracked via the MongoDB Issue Tracker Entry. Organizations should monitor MongoDB security advisories and apply updates as they become available. Consult the MongoDB release notes for specific version fixes addressing this vulnerability.

Workarounds

• Configure operationProfiling.slowOpThresholdMs to identify and investigate resource-intensive queries
• Implement application-level query validation to reject overly complex queries before they reach MongoDB
• Use MongoDB's $maxTimeMS aggregation operator to enforce query execution time limits
• Consider deploying MongoDB behind an application proxy that can enforce query complexity policies
• Increase system memory monitoring and implement automated restart procedures as a temporary measure

# Configuration example
# Add to mongod.conf to enable profiling and identify problematic queries
operationProfiling:
  mode: slowOp
  slowOpThresholdMs: 100
  slowOpSampleRate: 1.0

# Set memory limits at the OS level (Linux example)
# /etc/security/limits.conf
# mongodb soft memlock unlimited
# mongodb hard memlock unlimited
# mongodb soft nofile 64000
# mongodb hard nofile 64000