CVE-2025-7759

July 18, 2025, 3:15 p.m.

5.3
Medium

Description

A vulnerability, which was classified as critical, was found in thinkgem JeeSite up to 5.12.0. This affects an unknown part of the file modules/core/src/main/java/com/jeesite/common/ueditor/ActionEnter.java of the component UEditor Image Grabber. The manipulation of the argument Source leads to server-side request forgery. It is possible to initiate the attack remotely. The exploit has been disclosed to the public and may be used. The identifier of the patch is 1c5e49b0818037452148e0f8ff69ed04cb8fefdc. It is recommended to apply a patch to fix this issue.

Product(s) Impacted

Vendor Product Versions
Thinkgem
  • Jeesite
  • 5.12.0

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 thinkgem jeesite 5.12.0 / / / / / / /

CVSS Score

5.3 / 10

CVSS Data - 4.0

  • Attack Vector: NETWORK
  • Attack Complexity: LOW
  • Attack Requirements: NONE
  • Privileges Required: LOW
  • 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:L/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: July 17, 2025, 10:15 p.m.
Last Modified: July 18, 2025, 3:15 p.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.