CVE-2025-5410

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

5.3
Medium

Description

A vulnerability was found in Mist Community Edition up to 4.7.1. It has been declared as problematic. This vulnerability affects the function session_start_response of the file src/mist/api/auth/middleware.py. The manipulation leads to cross-site request forgery. The attack can 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 identified as 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-352
Cross-Site Request Forgery (CSRF)
The web application does not, or can not, sufficiently verify whether a well-formed, valid, consistent request was intentionally provided by the user who submitted the request.

*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

5.3 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: NONE
  • 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:N/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.