CVE-2024-8285

Oct. 1, 2024, 1:15 p.m.

5.9
Medium

Description

A flaw was found in Kroxylicious. When establishing the connection with the upstream Kafka server using a TLS secured connection, Kroxylicious fails to properly verify the server's hostname, resulting in an insecure connection. For a successful attack to be performed, the attacker needs to perform a Man-in-the-Middle attack or compromise any external systems, such as DNS or network routing configuration. This issue is considered a high complexity attack, with additional high privileges required, as the attack would need access to the Kroxylicious configuration or a peer system. The result of a successful attack impacts both data integrity and confidentiality.

Product(s) Impacted

Vendor Product Versions
Redhat
  • Kroxylicious
  • -

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-295
Improper Certificate Validation
The product does not validate, or incorrectly validates, a certificate.
CWE-297
Improper Validation of Certificate with Host Mismatch
The product communicates with a host that provides a certificate, but the product does not properly ensure that the certificate is actually associated with that host.

*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 redhat kroxylicious - / / / / / / /

CVSS Score

5.9 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: Aug. 30, 2024, 10:15 p.m.
Last Modified: Oct. 1, 2024, 1:15 p.m.

Status : Modified

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

More info

Source

secalert@redhat.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.