CVE-2024-45537

Oct. 1, 2024, 8:41 p.m.

6.5
Medium

Description

Apache Druid allows users with certain permissions to read data from other database systems using JDBC. This functionality allows trusted users to set up Druid lookups or run ingestion tasks. Druid also allows administrators to configure a list of allowed properties that users are able to provide for their JDBC connections. By default, this allowed properties list restricts users to TLS-related properties only. However, when configuration a MySQL JDBC connection, users can use a particularly-crafted JDBC connection string to provide properties that are not on this allow list. Users without the permission to configure JDBC connections are not able to exploit this vulnerability. CVE-2021-26919 describes a similar vulnerability which was partially addressed in Apache Druid 0.20.2. This issue is fixed in Apache Druid 30.0.1.

Product(s) Impacted

Vendor Product Versions
Apache
  • Druid
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-20
Improper Input Validation
The product receives input or data, but it does not validate or incorrectly validates that the input has the properties that are required to process the data safely and correctly.

*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 apache druid / / / / / / / /

CVSS Score

6.5 / 10

CVSS Data - 3.1

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Privileges Required: LOW
  • Scope: UNCHANGED
  • Confidentiality Impact: HIGH
  • Integrity Impact: NONE
  • Availability Impact: NONE
  • CVSS:3.1/AV:N/AC:L/PR:L/UI:N/S:U/C:H/I:N/A:N

    View Vector String

Timeline

Published: Sept. 17, 2024, 7:15 p.m.
Last Modified: Oct. 1, 2024, 8:41 p.m.

Status : Analyzed

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

More info

Source

security@apache.org

*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.