CVE-2025-5411

June 2, 2025, 5:32 p.m.

5.1
Medium

Description

A vulnerability was found in Mist Community Edition up to 4.7.1. It has been rated as problematic. This issue affects the function tag_resources of the file src/mist/api/tag/views.py. The manipulation of the argument tag leads to cross site scripting. The attack may be initiated remotely. The exploit has been disclosed to the public and may be used. Upgrading to version 4.7.2 is able to address this issue. The patch is named db10ecb62ac832c1ed4924556d167efb9bc07fad. It is recommended to upgrade the affected component.

Product(s) Impacted

Vendor Product Versions
Mist
  • Community Edition
  • <=4.7.1

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-79
Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting')
The product does not neutralize or incorrectly neutralizes user-controllable input before it is placed in output that is used as a web page that is served to other users.

*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 mist community_edition <=4.7.1 / / / / / / /

CVSS Score

5.1 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • User Interaction: PASSIVE
  • Scope:
  • Confidentiality Impact: NONE
  • Integrity Impact: LOW
  • Availability Impact: NONE
  • Exploit Maturity: NOT_DEFINED
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:L/UI:P/VC:N/VI:L/VA:N/SC:N/SI:N/SA:N/E:X/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X

    View Vector String

Timeline

Published: June 1, 2025, 11:15 p.m.
Last Modified: June 2, 2025, 5:32 p.m.

Status : Awaiting Analysis

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

More info

Source

cna@vuldb.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.