CVE-2026-9749

June 10, 2026, 7:43 p.m.

7.1
High

Description

This issue can occur when running an aggregation pipeline that uses the internal $exchange stage configured with key-range partitioning and order-preserving delivery. If a single key range produces enough documents to fill its exchange buffer (that is, many results are routed to the same consumer), the server reaches the code path where a full per-consumer buffer is detected but the internal "high watermark" for that key range is not updated as intended.

Product(s) Impacted

Vendor Product Versions
Mongodb
  • Mongodb
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-617
Reachable Assertion
The product contains an assert() or similar statement that can be triggered by an attacker, which leads to an application exit or other behavior that is more severe than necessary.

*CPE(s)

Affected systems and software identified for this CVE.

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a mongodb mongodb / / / / / / / /

References

https://jira.mongodb.org/browse/SERVER-124031

Tags

CWE-617
[email protected]
2026-06-09
CVE-2026-9749

CVSS Score

7.1 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: NONE
  • Integrity Impact: NONE
  • Availability Impact: HIGH
  • Exploit Maturity: NOT_DEFINED

    • CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: June 9, 2026, 11:17 p.m.
Last Modified: June 10, 2026, 7:43 p.m.

Status : Awaiting Analysis

CVE has been recently published to the CVE List and has been received by the NVD.

More info

Source

[email protected]

*Disclaimer: Some vulnerabilities do not have an associated CPE. To enhance the data, we use AI to infer CPEs based on CVE details. This is an automated process and might not always be accurate.