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CVE Vulnerability Database
Vulnerability Database/CVE-2025-13264

CVE-2025-13264: Online Magazine Management System SQLi Flaw

CVE-2025-13264 is a SQL injection vulnerability in Oretnom23 Online Magazine Management System 1.0 affecting the view_magazine.php file. This article covers technical details, attack vectors, and mitigation strategies.

Published:

CVE-2025-13264 Overview

CVE-2025-13264 is a SQL injection vulnerability in SourceCodester Online Magazine Management System 1.0, developed by oretnom23. The flaw resides in the /view_magazine.php script, where the ID parameter is incorporated into a database query without proper sanitization. Attackers can manipulate the ID argument to inject arbitrary SQL statements. The vulnerability is remotely exploitable and requires low privileges with no user interaction. A public proof-of-concept has been released, increasing the likelihood of opportunistic exploitation against exposed instances.

Critical Impact

Remote attackers with low privileges can manipulate database queries through the ID parameter in /view_magazine.php, potentially exposing magazine content, user records, and other database contents.

Affected Products

  • SourceCodester Online Magazine Management System 1.0
  • Vendor: oretnom23
  • CPE: cpe:2.3:a:oretnom23:online_magazine_management_system:1.0

Discovery Timeline

  • 2025-11-17 - CVE-2025-13264 published to NVD
  • 2026-06-17 - Last updated in NVD database

Technical Details for CVE-2025-13264

Vulnerability Analysis

The vulnerability is classified under [CWE-89] (Improper Neutralization of Special Elements used in an SQL Command) and [CWE-74] (Improper Neutralization of Special Elements in Output Used by a Downstream Component). The affected component is the /view_magazine.php endpoint, which accepts an ID parameter intended to retrieve a specific magazine record. The application passes this user-supplied value directly into a SQL query without parameterization or input filtering. As a result, attackers can append SQL syntax such as UNION SELECT clauses or blind boolean conditions to manipulate query logic.

The referenced public proof-of-concept demonstrates a blind SQL injection technique, indicating that error output may not be returned but data can still be extracted through inferential payloads. The EPSS score sits at 0.307%, reflecting limited observed scanning activity, though this can change rapidly after PoC disclosure.

Root Cause

The root cause is the absence of prepared statements or input validation when constructing SQL queries from the ID GET parameter. The application concatenates the user-controlled value directly into a query string. This allows injected SQL fragments to be parsed and executed by the database engine.

Attack Vector

The attack is conducted over the network against the HTTP interface of the affected application. An attacker sends a crafted GET request to /view_magazine.php?ID=<payload> where the payload contains SQL injection syntax. Exploitation requires only authenticated low-privilege access. Successful exploitation enables data extraction from the underlying database, including potentially sensitive user credentials and administrative data.

// Vulnerable request pattern (illustrative, see public PoC for details)
GET /view_magazine.php?ID=1' AND SLEEP(5)-- -

For technical exploitation details, refer to the public proof-of-concept on GitHub and the VulDB entry #332599.

Detection Methods for CVE-2025-13264

Indicators of Compromise

  • HTTP requests to /view_magazine.php containing SQL keywords such as UNION, SELECT, SLEEP, BENCHMARK, or comment markers like -- and # within the ID parameter.
  • Repeated requests to /view_magazine.php with incrementing or time-delayed payloads indicating blind SQL injection probing.
  • Unusual database query latency or error rates originating from the magazine viewing endpoint.

Detection Strategies

  • Inspect web server access logs for query strings on /view_magazine.php containing encoded SQL metacharacters such as %27 (single quote) or %20OR%20.
  • Deploy web application firewall (WAF) signatures targeting SQL injection patterns against the affected URI.
  • Correlate database query errors with corresponding HTTP requests to identify probing activity.

Monitoring Recommendations

  • Enable verbose logging on the database server to capture syntactically anomalous queries originating from the application user.
  • Monitor outbound traffic from the application host for signs of data exfiltration following suspicious request patterns.
  • Alert on access spikes to /view_magazine.php from single source IPs, which may indicate automated SQLi tooling such as sqlmap.

How to Mitigate CVE-2025-13264

Immediate Actions Required

  • Restrict access to the application to trusted networks until a vendor fix is available.
  • Deploy a WAF rule that blocks SQL injection payloads targeting the ID parameter on /view_magazine.php.
  • Audit existing database accounts used by the application and enforce least-privilege permissions to limit the impact of successful injection.

Patch Information

No official vendor patch is currently listed in the NVD references for CVE-2025-13264. Organizations operating SourceCodester Online Magazine Management System 1.0 should monitor the SourceCodester project page for updates and consider applying source-level fixes by replacing direct query concatenation with parameterized queries (mysqli_prepare or PDO prepared statements).

Workarounds

  • Modify view_magazine.php to cast the ID parameter to an integer using intval($_GET['ID']) before passing it to the SQL query.
  • Replace string-concatenated queries with parameterized prepared statements using PDO or MySQLi.
  • Restrict database account privileges to read-only on the specific tables required by the magazine viewing functionality.
bash
# Example PHP remediation snippet replacing concatenation with PDO prepared statement
$stmt = $pdo->prepare("SELECT * FROM magazines WHERE id = :id");
$stmt->bindValue(':id', (int)$_GET['ID'], PDO::PARAM_INT);
$stmt->execute();

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

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