CVE-2025-63711
Nov. 10, 2025, 3:15 p.m.
7.1
High
Description
A Cross-Site Request Forgery (CSRF) vulnerability in the SourceCodester Client Database Management System 1.0 allows an attacker to cause an authenticated administrative user to perform user deletion actions without their consent. The application's user deletion endpoint (e.g., superadmin_user_delete.php) accepts POST requests containing a user_id parameter and does not enforce request origin or anti-CSRF tokens. Because the endpoint lacks proper authentication/authorization checks and CSRF protections, a remote attacker can craft a malicious page that triggers deletion when visited by an authenticated admin, resulting in arbitrary removal of user accounts.
Product(s) Impacted
| Vendor | Product | Versions |
|---|---|---|
| Sourcecodester |
|
|
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 | sourcecodester | client_database_management_system | 1.0 | / | / | / | / | / | / | / |
Tags
CVSS Score
CVSS Data - 3.1
- Attack Vector: NETWORK
- Attack Complexity: LOW
- Privileges Required: NONE
- Scope: UNCHANGED
- Confidentiality Impact: NONE
- Integrity Impact: HIGH
- Availability Impact: LOW
CVSS:3.1/AV:N/AC:L/PR:N/UI:R/S:U/C:N/I:H/A:L
Timeline
Published: Nov. 10, 2025, 3:15 p.m.
Last Modified: Nov. 10, 2025, 3:15 p.m.
Last Modified: Nov. 10, 2025, 3:15 p.m.
Status : Received
CVE has been recently published to the CVE List and has been received by the NVD.
More infoSource
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.