CVE-2025-61330

Oct. 16, 2025, 8:15 p.m.

6.5
Medium

Description

A hard-coded weak password vulnerability has been discovered in all Magic-branded devices from Chinese network equipment manufacturer H3C. The vulnerability stems from the use of a hard-coded weak password for the root account in the /etc/shadow configuration or even the absence of any password at all. Some of these devices have the Telnet service enabled by default, or users can choose to enable the Telnet service in other device management interfaces (e.g. /debug.asp or /debug_telnet.asp). In addition, these devices have related interfaces called Virtual Servers, which can map the devices to the public network, posing the risk of remote attacks. Therefore, attackers can obtain the highest root privileges of the devices through the Telnet service using the weak password hardcoded in the firmware (or without a password), and remote attacks are possible.

Product(s) Impacted

Vendor Product Versions
H3c
  • Magic Branded Devices
  • *

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-259
Use of Hard-coded Password
The product contains a hard-coded password, which it uses for its own inbound authentication or for outbound communication to external components.

*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 h3c magic_branded_devices / / / / / / / /

CVSS Score

6.5 / 10

CVSS Data - 3.1

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

    View Vector String

Timeline

Published: Oct. 16, 2025, 6:15 p.m.
Last Modified: Oct. 16, 2025, 8:15 p.m.

Status : Received

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

More info

Source

cve@mitre.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.