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CVE Vulnerability Database
Vulnerability Database/CVE-2025-11038

CVE-2025-11038: Online Clinic Management System SQLi Flaw

CVE-2025-11038 is a SQL injection vulnerability in Online Clinic Management System 1.0 affecting the /details.php file. Attackers can exploit the ID parameter remotely to compromise the database and extract sensitive data.

Published:

CVE-2025-11038 Overview

CVE-2025-11038 is a SQL injection vulnerability in itsourcecode Online Clinic Management System 1.0. The flaw resides in the /details.php?action=post endpoint, where the ID parameter is passed directly into a backend SQL query without proper sanitization. An authenticated remote attacker with low privileges can manipulate this parameter to inject arbitrary SQL syntax. Public exploit details describe a union-based SQL injection technique that allows extraction of data from the underlying database. The vulnerability is tracked as [CWE-74] (Improper Neutralization of Special Elements in Output Used by a Downstream Component).

Critical Impact

Exploitation enables unauthorized read access to clinic database contents, potentially exposing patient records, credentials, and operational data.

Affected Products

  • itsourcecode Online Clinic Management System 1.0
  • angeljudesuarez:online_clinic_management_system:1.0
  • /details.php component with the action=post parameter

Discovery Timeline

  • 2025-09-26 - CVE-2025-11038 published to NVD
  • 2026-04-29 - Last updated in NVD database

Technical Details for CVE-2025-11038

Vulnerability Analysis

The vulnerability stems from unsanitized handling of the ID GET parameter in /details.php when invoked with action=post. The application concatenates user-supplied input directly into a SQL statement, allowing query structure manipulation. Public analysis describes the flaw as a union-based SQL injection, which lets attackers append UNION SELECT statements to retrieve arbitrary columns from any accessible table. Successful exploitation yields confidentiality, integrity, and availability impact on the database tier. Because Online Clinic Management System is a healthcare-oriented application, exposed records may include personally identifiable information and clinical data.

Root Cause

The root cause is missing input validation and the absence of parameterized queries. The ID parameter received from the HTTP request is interpolated into a SQL string without type enforcement, escaping, or use of prepared statements. This is a classic instance of [CWE-74] manifesting as SQL injection.

Attack Vector

The attack is remote and requires network access to the application along with low-privilege authentication. An attacker crafts a malicious value for the ID parameter in a request to /details.php?action=post and observes the resulting SQL behavior. Exploit details have been publicly disclosed, lowering the barrier for opportunistic abuse.

The vulnerability manifests when the ID parameter is passed unmodified into a database query. See the Notion SQL Injection Analysis and VulDB entry #325985 for technical details.

Detection Methods for CVE-2025-11038

Indicators of Compromise

  • HTTP requests to /details.php?action=post containing SQL keywords such as UNION, SELECT, ORDER BY, or INFORMATION_SCHEMA in the ID parameter.
  • Web server access logs showing unusually long ID parameter values or URL-encoded SQL syntax (%20UNION%20SELECT).
  • Database error messages or 500 responses correlated with crafted ID values.
  • Unexpected outbound queries against mysql.user, information_schema.tables, or other sensitive tables.

Detection Strategies

  • Deploy web application firewall (WAF) signatures that flag SQL injection payloads targeting details.php.
  • Enable database query logging and alert on UNION SELECT patterns originating from the clinic application user.
  • Correlate web access logs with database audit logs to identify parameter-driven query anomalies.

Monitoring Recommendations

  • Monitor authentication events for low-privilege accounts performing high volumes of requests against /details.php.
  • Track response size variance on the details.php endpoint, which often indicates successful union-based extraction.
  • Alert on database service accounts accessing tables outside their expected scope.

How to Mitigate CVE-2025-11038

Immediate Actions Required

  • Restrict network exposure of the Online Clinic Management System to trusted networks or place it behind a VPN.
  • Deploy a WAF rule set that blocks SQL injection payloads, particularly on /details.php with the action=post parameter.
  • Audit application accounts and revoke unnecessary low-privilege access used to reach the vulnerable endpoint.
  • Review web and database logs for prior exploitation attempts referencing the ID parameter.

Patch Information

No vendor-supplied patch has been published for itsourcecode Online Clinic Management System 1.0 at the time of CVE assignment. Refer to the IT Source Code project page and the VulDB advisory for any future updates. Organizations running this application should evaluate code-level remediation by replacing string-concatenated SQL with parameterized queries or prepared statements.

Workarounds

  • Modify details.php to cast the ID parameter to an integer before use in any SQL statement.
  • Replace inline SQL with PDO prepared statements or mysqli_prepare() bound parameters.
  • Apply least-privilege permissions to the database account used by the application, removing access to tables not required for runtime operation.
  • Consider taking the application offline until secure code changes can be validated, given the healthcare data exposure risk.
bash
# Example: enforce integer casting on the ID parameter in PHP
# Original vulnerable pattern:
# $id = $_GET['ID'];
# $sql = "SELECT * FROM records WHERE id = $id";

# Hardened pattern using prepared statements:
$id = filter_input(INPUT_GET, 'ID', FILTER_VALIDATE_INT);
if ($id === false) { http_response_code(400); exit; }
$stmt = $pdo->prepare('SELECT * FROM records WHERE id = :id');
$stmt->execute([':id' => $id]);

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

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