CVE-2024-23185

Sept. 10, 2024, 3:50 p.m.

7.5
High

Description

Very large headers can cause resource exhaustion when parsing message. The message-parser normally reads reasonably sized chunks of the message. However, when it feeds them to message-header-parser, it starts building up "full_value" buffer out of the smaller chunks. The full_value buffer has no size limit, so large headers can cause large memory usage. It doesn't matter whether it's a single long header line, or a single header split into multiple lines. This bug exists in all Dovecot versions. Incoming mails typically have some size limits set by MTA, so even largest possible header size may still fit into Dovecot's vsz_limit. So attackers probably can't DoS a victim user this way. A user could APPEND larger mails though, allowing them to DoS themselves (although maybe cause some memory issues for the backend in general). One can implement restrictions on headers on MTA component preceding Dovecot. No publicly available exploits are known.

Product(s) Impacted

Product Versions
Dovecot

Weaknesses

CWE-770
Allocation of Resources Without Limits or Throttling
The product allocates a reusable resource or group of resources on behalf of an actor without imposing any restrictions on the size or number of resources that can be allocated, in violation of the intended security policy for that actor.

CVSS Score

7.5 / 10

CVSS Data

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

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

Date

  • Published: Sept. 10, 2024, 3:15 p.m.
  • Last Modified: Sept. 10, 2024, 3:50 p.m.

Status : Awaiting Analysis

CVE has been marked for Analysis. Normally once in this state the CVE will be analyzed by NVD staff within 24 hours.

More info

Source

security@open-xchange.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.