CVE-2024-8013

Oct. 31, 2024, 1:33 p.m.

3.3
Low

Description

A bug in query analysis of certain complex self-referential $lookup subpipelines may result in literal values in expressions for encrypted fields to be sent to the server as plaintext instead of ciphertext. Should this occur, no documents would be returned or written. This issue affects mongocryptd binary (v5.0 versions prior to 5.0.29, v6.0 versions prior to 6.0.17, v7.0 versions prior to 7.0.12 and v7.3 versions prior to 7.3.4) and mongo_crypt_v1.so shared libraries (v6.0 versions prior to 6.0.17, v7.0 versions prior to 7.0.12 and v7.3 versions prior to 7.3.4) released alongside MongoDB Enterprise Server versions.

Product(s) Impacted

Vendor Product Versions
Mongodb
  • Mongo Crypt V1.so
  • Mongocryptd
  • *
  • *

Weaknesses

CWE-319
Cleartext Transmission of Sensitive Information
The product transmits sensitive or security-critical data in cleartext in a communication channel that can be sniffed by unauthorized actors.

*CPE(s)

Type Vendor Product Version Update Edition Language Software Edition Target Software Target Hardware Other Information
a mongodb mongo_crypt_v1.so / / / / / mongodb / /
a mongodb mongo_crypt_v1.so / / / / / mongodb / /
a mongodb mongo_crypt_v1.so / / / / / mongodb / /
a mongodb mongocryptd / / / / / mongodb / /
a mongodb mongocryptd / / / / / mongodb / /
a mongodb mongocryptd / / / / / mongodb / /
a mongodb mongocryptd / / / / / mongodb / /

CVSS Score

3.3 / 10

CVSS Data

  • Attack Vector: LOCAL
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: UNCHANGED
  • Confidentiality Impact: LOW
  • Integrity Impact: NONE
  • Availability Impact: NONE
  • View Vector String

    CVSS:3.1/AV:L/AC:L/PR:L/UI:N/S:U/C:L/I:N/A:N

Date

  • Published: Oct. 28, 2024, 1:15 p.m.
  • Last Modified: Oct. 31, 2024, 1:33 p.m.

Status : Analyzed

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

More info

Source

cna@mongodb.com

*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.