Product Overview – MongoDB Server

Vendor: MongoDB
Product: MongoDB Server (Community & Enterprise)
Service Process: mongod
Default Port: 27017
Architecture: Standalone, Replica Set, Sharded Cluster
Storage Engine: WiredTiger

MongoDB is widely used in web platforms, APIs, fintech systems, SaaS backends, and analytics workloads. Because it handles flexible document structures and dynamic indexing, certain boundary conditions in query planning, memory handling, recursion control, and index validation may expose availability risks if not properly constrained.

The vulnerabilities listed below primarily impact availability and may lead to memory exhaustion, deadlock conditions, or process termination.

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CVE-2026-25611

Vulnerability Overview

Field	Details
CVE ID	CVE-2026-25611
Vulnerability Type	Memory Exhaustion
Affected Component	Aggregation Pipeline Engine
CVSS Score	7.5 (High)
Severity	High
Attack Vector	Remote (Authenticated)
Impact	Server crash (OOM kill)
Exploit Availability	No public weaponized exploit observed

Uncontrolled memory growth was observed when complex aggregation pipelines were executed. Memory limits were not properly enforced during intermediate stage expansion.

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Technical Description

It was identified that deeply nested $lookup, $group, $facet, and $sort stages could trigger excessive allocation in RAM when disk spilling was disabled. The aggregation framework allowed intermediate results to expand without early boundary enforcement.

Under sustained execution, system memory was exhausted and the mongod process was terminated by the operating system.

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Exploitation Method (Educational)

The issue could be triggered using:

• Deeply nested $lookup pipelines
• Recursive pipeline references
• Large $group accumulators
• Disabled allowDiskUse

Example pattern:

db.collection.aggregate([
  {
    $lookup: {
      from: "collection",
      pipeline: [
        { $lookup: { from: "collection", pipeline: [ ... repeated ... ], as: "nested" } }
      ],
      as: "result"
    }
  }
], { allowDiskUse: false })

Repeated execution under concurrency increases impact.

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MITRE ATT&CK Mapping

• T1499 – Endpoint Denial of Service
• T1499.004 – Application Resource Exhaustion

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Detection and Monitoring

Log Sources

• MongoDB diagnostic log
• Linux syslog (/var/log/messages)
• dmesg (OOM killer logs)
• Kubernetes pod events
• Cloud VM monitoring

Indicators of Compromise

• Rapid increase in RSS memory of mongod
• Out of memory entries in logs
• Unexpected process restart
• Surge in aggregation operations

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Detection Rules (Elastic Example)

process.name:"mongod" AND message:"Out of memory"

mongodb.log.message:"aggregation" AND mongodb.log.message:"memory"

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Splunk Query

index=mongodb_logs "Out of memory" OR "Killed process mongod"

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Remediation

Upgrade to the latest patched release:

https://www.mongodb.com/try/download/community

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CVE-2026-25612

Vulnerability Overview

Field	Details
CVE ID	CVE-2026-25612
Vulnerability Type	Lock Collision / Deadlock
CVSS Score	6.8
Severity	Medium
Attack Vector	Remote (Authenticated)
Impact	Service stall / availability loss
Exploit Availability	No public exploit released

Improper lock escalation handling was identified during concurrent write operations and index rebuild events.

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Technical Description

Under high concurrency, lock upgrade paths from collection-level to global-level locks were not consistently synchronized. It was observed that certain write-heavy workloads could cause thread starvation or deadlock conditions.

The service did not immediately crash but became unresponsive.

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Exploitation Conditions

• Concurrent writes + index rebuild
• Heavy transaction usage
• Simultaneous createIndex and write operations
• Replica set synchronization under stress

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MITRE Mapping

• T1499 – Endpoint DoS
• T1499.003 – Resource Locking

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Detection

Indicators

• Long lock wait times
• LockTimeout errors
• Increase in replication lag
• Stuck threads in db.currentOp()

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Elastic Query

mongodb.log.message:"LockTimeout" OR mongodb.log.message:"lock wait"

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Splunk Query

index=mongodb_logs "LockTimeout" OR "deadlock"

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Remediation

Apply latest MongoDB security update:

https://www.mongodb.com/try/download/community

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CVE-2026-1850

Vulnerability Overview

Field	Details
CVE ID	CVE-2026-1850
Vulnerability Type	Query Planner OOM
Severity	High
Impact	Crash
Exploit Availability	No public PoC

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Technical Description

The query planner attempted to generate excessive candidate plans when multiple index combinations and complex $or clauses were provided. Memory growth occurred due to inadequate pruning logic.

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Exploitation (Educational)

Pattern:

db.collection.find({
  $or: [
    {field1: {$regex: ".*"}},
    {field2: {$regex: ".*"}},
    {field3: {$regex: ".*"}}
  ]
}).hint({compound_index:1})

Repeated queries forced planner expansion.

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Detection

Indicators

• High CPU during query parsing
• Query planner memory allocation errors
• Repeated regex-based search queries

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Elastic Query

mongodb.log.message:"query planner" AND "memory"

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Splunk Query

index=mongodb_logs "planner" AND "memory"

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Remediation

Upgrade to patched MongoDB version:

https://www.mongodb.com/try/download/community

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CVE-2026-1849

Vulnerability Overview

Field	Details
CVE ID	CVE-2026-1849
Vulnerability Type	Deep Recursion OOM
Severity	High
Impact	Stack overflow / crash
Exploit Availability	No public exploit

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Technical Description

Improper depth validation was observed during recursive BSON parsing. Extremely nested document structures could exhaust stack memory.

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Exploitation Example (Educational)

{"a":{"a":{"a":{"a":{"a":{ ... repeated thousands of times ... }}}}}}

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Detection

Indicators

• Crash during document insertion
• Stack overflow entries
• BSON validation warnings

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Elastic Query

mongodb.log.message:"stack overflow" OR mongodb.log.message:"BSON depth"

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Remediation

Install latest secure MongoDB version:

https://www.mongodb.com/try/download/community

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CVE-2026-25613

Vulnerability Overview

Field	Details
CVE ID	CVE-2026-25613
Vulnerability Type	Invalid Wildcard Index
Severity	Medium
Impact	Server disable on restart

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Technical Description

Improper metadata validation was identified during wildcard index creation. Corrupted index catalog entries prevented normal startup validation.

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Detection

Indicators

• Index catalog corruption
• Node stuck in RECOVERING state
• Startup validation failure

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Splunk Query

index=mongodb_logs "Index catalog corruption"

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Remediation

Upgrade MongoDB from official source:

https://www.mongodb.com/try/download/community

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CVE-2026-25610

Vulnerability Overview

Field	Details
CVE ID	CVE-2026-25610
Vulnerability Type	Invalid geoNear Index Crash
Severity	High
Impact	Segmentation fault
Exploit Availability	No confirmed public exploit

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Technical Description

Insufficient bounds validation was observed when malformed 2dsphere or 2d indexes were used with $geoNear. Improper coordinate handling caused memory access violation.

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Exploitation (Educational)

db.collection.aggregate([
  {
    $geoNear: {
      near: { type: "Point", coordinates: [9999,9999] },
      distanceField: "distance"
    }
  }
])

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Detection

Indicators

• Crash during geo query
• Core dump referencing geo module
• Log message containing geoNear planner failure

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Elastic Query

mongodb.log.message:"geoNear" AND "error"

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Remediation

Apply official patch by upgrading MongoDB:

https://www.mongodb.com/try/download/community

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Final Takeaway

• Immediate upgrade to latest supported MongoDB version
• Enforce authentication and role separation
• Restrict index creation privileges
• Configure maxTimeMS and memory limits
• Enable monitoring alerts for memory spikes and lock waits
• Disable public exposure of MongoDB port

All listed vulnerabilities are availability-focused and should be treated as production-impacting risks in internet-facing or multi-tenant environments.

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