CVE-2025-10765

Sept. 21, 2025, 7:15 a.m.

5.1
Medium

Description

A security flaw has been discovered in SeriaWei ZKEACMS up to 4.3. This vulnerability affects the function CheckPage/Suggestions in the library cms-v4.3\wwwroot\Plugins\ZKEACMS.SEOSuggestions\ZKEACMS.SEOSuggestions.dll of the component SEOSuggestions. Performing manipulation results in server-side request forgery. It is possible to initiate the attack remotely. The exploit has been released to the public and may be exploited. The vendor was contacted early about this disclosure but did not respond in any way.

Product(s) Impacted

Vendor Product Versions
Seriawei
  • Zkeacms
  • *, 4.3

Weaknesses

Common security weaknesses mapped to this vulnerability.

CWE-918
Server-Side Request Forgery (SSRF)
The web server receives a URL or similar request from an upstream component and retrieves the contents of this URL, but it does not sufficiently ensure that the request is being sent to the expected destination.

*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 seriawei zkeacms / / / / / / / /
a seriawei zkeacms 4.3 / / / / / / /

CVSS Score

5.1 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: HIGH
  • User Interaction: NONE
  • Scope:
  • Confidentiality Impact: LOW
  • Integrity Impact: LOW
  • Availability Impact: LOW
  • Exploit Maturity: PROOF_OF_CONCEPT
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:H/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/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: Sept. 21, 2025, 7:15 a.m.
Last Modified: Sept. 21, 2025, 7:15 a.m.

Status : Received

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.