CVE-2026-81490

Executive Summary

CVE-2026-81490 is an unpatched denial-of-service vulnerability in MongoDB Connector for BI (mongosqld), the component that translates SQL queries into MongoDB operations. A low-privileged database user who can create views in a namespace sampled by the connector can cause the schema-sampling routine to fail persistently. The vulnerability has a CVSS score of 7.7 (High) driven primarily by high availability impact and a scope change, though confidentiality and integrity are unaffected. Affected organizations are those running mongosqld with schema sampling enabled and permitting view creation by non-privileged database users. The impact is a sustained availability loss: SQL clients cannot retrieve data until an operator manually removes the offending view or excludes its namespace from sampling.

Technical Analysis

The vulnerability resides in the schema-sampling logic of the MongoDB Connector for BI (mongosqld). The connector periodically samples namespaces in a MongoDB deployment to build and refresh an internal schema that maps relational tables/columns to MongoDB collections/documents. This schema is a prerequisite for serving any SQL queries; without it, the connector cannot translate SQL into MongoDB aggregation pipelines.

The flaw is triggered when a database user creates a view in a sampled namespace where the view's definition evaluates reliably to an error. MongoDB views are essentially stored aggregation pipelines. When the sampling routine attempts to introspect or query such a view, the server returns an error. The NVD description indicates the sampling logic classifies this server message as "transient" — a category reserved for errors considered temporary (e.g., network hiccups, replica set election timeouts). Because it is treated as transient, the routine enters a retry loop.

After the configured retry count is exhausted, the sampling routine terminates without a valid result for that namespace. Critically, the code path does not escalate the condition to a fatal error; it simply ends the entire schema refresh routine. This is consistent with CWE-476 (NULL Pointer Dereference) in that a null/empty result is not handled gracefully — the routine exits rather than recording a partial schema or skipping the problematic view.

The mongosqld process itself remains alive, but its internal schema cache is now invalid or absent. All subsequent SQL queries fail because there is no usable schema to translate them. The service does not self-heal; a new sampling cycle may be scheduled, but the view still evaluates to an error, causing the same failure loop. Recovery requires manual operator action: either drop the offending view or reconfigure the connector to exclude that namespace from sampling.

Attack surface details:

• Precondition: The attacker must have rights to create a view in a namespace that mongosqld samples. In many deployments, schema sampling covers all databases unless explicitly filtered, and view creation may be granted to application roles or read/write users.
• No authentication bypass: The attacker must be an authenticated database user, consistent with PR:L (low privilege required) in the CVSS vector.
• Network reachability: The view is created directly against the MongoDB server, not through mongosqld; the attacker does not need network access to the connector's SQL port (default 3307), only to the MongoDB data port (default 27017). The "AV:N" component reflects that the MongoDB server is commonly network-accessible.

Exploitation Scenarios

The attack chain is inferred from the vulnerability class as no public PoC exists. The technical detail available in the NVD description is sufficient to establish the mechanism without inventing specific payload code.

Step 1 — Reconnaissance / Target Identification: An attacker with valid MongoDB authentication enumerates databases and collections to identify which namespaces are sampled by mongosqld. This can be done by observing which databases are referenced in SQL queries, by inspecting connector configuration if exposed, or simply by targeting all writable namespaces. The goal is to find a namespace that the connector includes in its schema sampling routine.

Step 2 — Flaw Class Trigger: The attacker creates a view in the target namespace using MongoDB's create command or the equivalent driver API. The view's definition (a stored aggregation pipeline) must reference a collection or operation that reliably evaluates to an error — for example, referencing a non-existent collection, using an invalid stage operator, or performing a type mismatch on a $lookup or $match operation. The exact failing condition cannot be specified due to insufficient public detail, but the requirement is that the view evaluation consistently returns a server error rather than a dataset.

Step 3 — Payload / Execution Method (vulnerability-class level): The attacker's malicious view is automatically picked up by the mongosqld schema-sampling routine on its next refresh cycle. When the sampler attempts to evaluate or introspect the view, the MongoDB server returns an error message. The sampling logic misclassifies this as transient and retries until exhaustion. Upon retry exhaustion, the routine terminates the entire schema refresh without a valid result. Because the view remains in place, every subsequent refresh cycle repeats the same failure.

Step 4 — Post-Exploitation Impact: The schema cache in mongosqld becomes stale or empty. SQL clients connecting through the connector receive errors or empty result sets because queries cannot be translated. The connector process stays running, consuming resources but serving no usable data. The denial-of-service persists indefinitely until an operator drops the view or excludes its namespace from the sampling configuration. At the CVSS level, this maps to High availability impact (A:H) with no confidentiality or integrity impact (C:N/I:N).

Inference caveat: No public PoC or exploit code exists. The attack chain above is derived strictly from the vulnerability class and the NVD description. Specific MongoDB view error types or exact sampling retry parameters are not documented in the available data and should not be assumed.

Proof of Concept Intelligence

No public proof-of-concept is currently available for CVE-2026-81490. No exploit code, Nuclei template, or Metasploit module has been published, and the vulnerability has not been added to CISA's Known Exploited Vulnerabilities catalog.

Why exploitation may still be possible:

1. The vulnerability class — resource exhaustion via crafted schema objects — is well understood in database ecosystems. An attacker with MongoDB access can independently derive the technique by experimenting with view definitions that produce persistent server errors.
2. The preconditions (authenticated view creation, sampled namespace) are common in shared MongoDB deployments where application users have write access to their own databases.
3. The misclassification of a deterministic error as "transient" is a logic flaw that is straightforward to probe without source-code access; an attacker only needs to observe whether mongosqld's schema refresh stalls.

Resources defenders should monitor for future PoC disclosure:

• MongoDB JIRA (jira.mongodb.com): Vendor issue tracker where a fix or technical reproduction steps may be posted.
• NVD and CVE feeds: Look for version-specific advisories or updated references.
• GitHub Security Advisories and exploit-db: Watch for proof-of-concept repositories or write-ups.
• Security researcher blogs (e.g., on Medium, Project Zero, or vendor-specific research): MongoDB connector components have been analyzed in prior research on schema-inference attacks.
• Vendor patch release notes: MongoDB typically publishes technical details alongside fixes; a patch announcement will likely include a reproducer.

Impact Assessment

The CVSS v3.1 base score is 7.7 (High) with the vector CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:C/C:N/I:N/A:H.

Business impact:

• Availability (A:H): Complete loss of SQL access to MongoDB data through the connector. This is not a crash of the connector process; rather, the service becomes functionally unusable, which can be harder to diagnose and remediate because the process appears healthy.
• Confidentiality and Integrity (C:N/I:N): No data disclosure or modification. The attack is purely disruptive.
• Scope change (S:C): The vulnerable component (mongosqld schema sampler) impacts the broader SQL access tier, affecting all clients that rely on the connector, not just the attacker's own queries.

Affected systems: Any deployment running MongoDB Connector for BI (mongosqld) where schema sampling is enabled (the default) and where non-privileged database users can create views in sampled namespaces.

Blast radius:

• Direct: All SQL-based applications, BI tools, and reporting dashboards that query MongoDB through the connector.
• Indirect: Operational workflows that depend on SQL-derived data (e.g., finance reporting, real-time analytics) suffer downtime. The attack is persistent — a single malicious view disables the connector indefinitely, requiring manual intervention.
• Multi-tenant risk: In environments where multiple applications share a MongoDB deployment, a low-privileged user in one tenant can deny service to all tenants using the connector.

Privilege requirement (PR:L) means the attacker needs only a low-privileged account with view-creation rights — no admin or operator access to MongoDB is required. Combined with network exploitability (AV:N) and no user interaction (UI:N), this makes the vulnerability an attractive tool for a determined insider or a compromised application account.

Detection Guidance

Sigma Rule

title: MongoDB Connector for BI Schema Sampling Denial of Service
id: 5f4c3a2e-1b7d-4e9a-8c3f-2a6b4d8e1c5a
status: experimental
description: Detects creation of MongoDB views that may target mongosqld schema sampling, identified by view definitions containing error-prone operations.
references:
    - https://nvd.nist.gov/vuln/detail/CVE-2026-81490
author: valtersit.com Threat Intel
date: 2026/03/15
logsource:
    category: application
    product: mongodb
    definition: 'Requires MongoDB audit logs capturing the create command'
detection:
    selection_create:
        event.operation: 'create'
        event.object: 'view'
    selection_suspicious:
        # View definitions containing operations likely to fail during sampling
        # e.g., $lookup with non-existent collection, invalid $match on missing fields
        event.definition|contains:
            - '$lookup'
            - '$graphLookup'
            - '$facet'
    condition: selection_create and selection_suspicious
    timeframe: 5m
level: medium
falsepositives:
    - Legitimate views created by developers using complex aggregations
    - Views created by normal application logic
tags:
    - attack.t1499
    - cve.2026-81490

YARA Rule

rule CVE_2026_81490_MongoDB_View_Sampling_DOS
{
    meta:
        author = "valtersit.com Threat Intel"
        description = "Detects log strings indicating MongoDB view creation followed by mongosqld schema sampling failure and retry exhaustion"
        cve = "CVE-2026-81490"
        date = "2026-03-15"
    strings:
        $view_create = "create" ascii wide nocase
        $view_type = "view" ascii wide nocase
        $sampling_err = "schema sampling" ascii wide nocase
        $transient = "transient" ascii wide nocase
        $retries = "retry" ascii wide nocase
        $schema_fail = "schema refresh" ascii wide nocase
        $sql_fail = "SQL query" ascii wide nocase
    condition:
        ($view_create and $view_type) and
        ($sampling_err or $schema_fail) and
        ($transient or $retries) and 2 of them
}

Note: This YARA rule targets MongoDB server and mongosqld log files, searching for correlated events: view creation events alongside sampling failure messages. Adjust for log format used in your environment.

Suricata IDS Rule

alert tcp any any -> $MONGO_GEO any (msg:"CVE-2026-81490 MongoDB Connector for BI Schema DoS - View Create"; flow:to_server,established; content:"create"; nocase; content:"view"; nocase; distance:0; content:"$lookup"; nocase; distance:0; within:100; classtype:attempted-dos; sid:9814901; rev:1; reference:cve,2026-81490;)

Note: MongoDB wire protocol is binary; plain-text content matching is unreliable. This rule is a best-effort detection for deployments using text-based protocols (legacy OP_QUERY) or those logging commands. For production use, deploy on the MongoDB server-side or use command-monitoring hooks instead of inline network inspection.

Elastic Detection

// Detect view creation followed by mongosqld schema sampling failures
sequence by host.name with maxspan=10m
  [ any where event.category == "audit" and 
    event.operation == "create" and 
    stringContains(object.name, "view") ]
  [ any where event.category == "process" and 
    process.name == "mongosqld" and 
    (message like "*schema sampling*" or message like "*transient*" or message like "*retries exhausted*") ]

Splunk SPL Query

index=mongodb sourcetype=mongod:audit OR sourcetype=mongosqld
| search event.operation="create" event.object="view"
| join type=inner max=5 host [
    search index=mongodb sourcetype=mongosqld
    | search "schema sampling" OR "transient" OR "retries exhausted"
    | stats earliest(_time) as sampling_fail_time by host
    | fields host, sampling_fail_time
]
| where _time >= sampling_fail_time - 600 AND _time <= sampling_fail_time + 600
| table _time, host, event.definition, sampling_fail_time
| stats count by host, event.definition

Wazuh OSSEC Rule

<group name="mongodb,">
  <rule id="593633" level="10">
    <decoded_as>json</decoded_as>
    <field name="event.operation">create</field>
    <field name="event.object">view</field>
    <description>CVE-2026-81490: MongoDB view creation that may disable mongosqld schema sampling</description>
    <group>availability_dos,</group>
    <mitre>
      <id>T1499</id>
    </mitre>
    <options>no_full_log</options>
  </rule>
</group>

Mitigation & Patch Guidance

Patch confidence: 0/4 (UNPATCHED) — no patch evidence from any tracked source. The vendor has not released a fix, and affected versions are not enumerated. The following guidance is based on risk reduction while awaiting an official patch.

1) Immediate mitigations (can be applied without waiting for a vendor fix):

• Restrict view-creation privileges: Audit MongoDB role definitions and remove createCollection/createView permissions from low-privileged application roles where not strictly required. Use the principle of least privilege on the db.createView action.
• Exclude untrusted namespaces from sampling: Configure mongosqld schemaSampling settings to exclude namespaces that are writable by low-privileged users or that contain user-generated content. See the connector's schema configuration option for namespace filtering.
• Deploy a monitoring watch on the MongoDB server for view-creation events in sampled namespaces; alert on anomalous view definitions (e.g., those containing $lookup to non-existent collections).
• Establish a manual recovery runbook: Document the procedure to identify and drop the offending view: query db.system.views (or use $listLocalViews) and remove the view with db.dropView(). Ensure this runbook is available to on-call staff.

2) Patch/upgrade steps:

• Currently not applicable — no patched version exists. Monitor MongoDB JIRA and the MongoDB Connector for BI release notes for a security fix.
• When a patch is released: upgrade mongosqld to the fixed version, then validate schema sampling on a staging instance with a crafted malicious view to confirm the fix prevents the persistent failure.

3) Long-term hardening:

• Network segmentation: Restrict direct access to the MongoDB data port (27017) to only trusted application servers. SQL clients should reach data exclusively through mongosqld, which reduces the pool of potential attackers.
• Privileged access management: Implement separate MongoDB roles for schema management vs. data operations. View creation should require an approval workflow in production.
• Enable MongoDB audit logging to capture all DDL operations, including view creation, for forensic analysis.
• Harden the connector's retry logic: If the connector version allows tuning, configure schema sampling retries to fail-fast on deterministic errors (non-transient codes). This limits the window of exposure even without a full patch.
• Regular schema validation: Periodically run a script that iterates over all views in sampled namespaces and evaluates them; flag any view that returns an error for manual review.

References

1. NVD — CVE-2026-81490: https://nvd.nist.gov/vuln/detail/CVE-2026-81490
2. MongoDB Security Advisories (watch for future update): https://www.mongodb.com/security
3. MongoDB Connector for BI Documentation (schema sampling configuration): https://www.mongodb.com/docs/bi-connector/current/
4. CISA Known Exploited Vulnerabilities Catalog (no entry; monitor for updates): https://www.cisa.gov/known-exploited-vulnerabilities-catalog
5. MongoDB JIRA Issue Tracker (search for CVE-2026-81490 when vendor publishes): https://jira.mongodb.com/

Threat actor campaigns / exploit-in-the-wild evidence: None reported at the time of writing. No CISA KEV inclusion, no public exploit code, and no observed campaigns. The vulnerability is unpatched, which elevates its risk profile should exploitation techniques be independently discovered. Organizations should monitor their MongoDB audit logs for abnormal view creation tied to privilege escalation attempts.