CVE-2026-30867

April 3, 2026, 4:10 p.m.

5.7
Medium

Description

CocoaMQTT is a MQTT 5.0 client library for iOS and macOS written in Swift. Prior to version 2.2.2, a vulnerability exists in the packet parsing logic of CocoaMQTT that allows an attacker (or a compromised/malicious MQTT broker) to remotely crash the host iOS/macOS/tvOS application. If an attacker publishes the 4-byte malformed payload to a shared topic with the RETAIN flag set to true, the MQTT broker will persist the payload. Any time a vulnerable client connects and subscribes to that topic, the broker will automatically push the malformed packet. The app will instantly crash in the background before the user can even interact with it. This effectively "bricks" the mobile application (a persistent DoS) until the retained message is manually wiped from the broker database. This issue has been patched in version 2.2.2.

Product(s) Impacted

Vendor Product Versions
Mosquitto
  • Coacomqtt
  • *

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 mosquitto coacomqtt / / / / / / / /

CVSS Score

5.7 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: April 2, 2026, 2:16 p.m.
Last Modified: April 3, 2026, 4:10 p.m.

Status : Awaiting Analysis

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

More info

*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.