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CVE Vulnerability Database

CVE-2025-7492: Vehicle Parking Management System SQLi Flaw

CVE-2025-7492 is a critical SQL injection vulnerability in PHPGurukul Vehicle Parking Management System 1.13 affecting the manage-incomingvehicle.php file. This article covers technical details, attack vectors, and mitigation.

Published:

CVE-2025-7492 Overview

CVE-2025-7492 is a SQL injection vulnerability in PHPGurukul Vehicle Parking Management System version 1.13. The flaw resides in the /admin/manage-incomingvehicle.php endpoint, where the del parameter is passed directly into a database query without proper sanitization. Authenticated attackers can manipulate the parameter to inject arbitrary SQL statements remotely. The exploit details have been publicly disclosed, increasing the risk of opportunistic abuse against exposed installations. The weakness is tracked under CWE-74 for improper neutralization of special elements in output used by a downstream component.

Critical Impact

Remote attackers with low-privilege admin access can extract, modify, or delete database contents through SQL injection against the del parameter.

Affected Products

  • PHPGurukul Vehicle Parking Management System 1.13
  • Deployments exposing /admin/manage-incomingvehicle.php
  • Installations using the unpatched upstream PHPGurukul codebase

Discovery Timeline

  • 2025-07-12 - CVE-2025-7492 published to the National Vulnerability Database
  • 2026-04-29 - Last updated in NVD database

Technical Details for CVE-2025-7492

Vulnerability Analysis

The vulnerability exists in the administrative interface of PHPGurukul Vehicle Parking Management System 1.13. The manage-incomingvehicle.php script accepts a del argument via HTTP request and uses the value within a SQL statement. Because the application does not validate or parameterize the input, an attacker can append SQL syntax that the database engine executes. Successful exploitation enables unauthorized read and write operations against backend tables storing vehicle, user, and transaction data. The attack requires network reachability to the admin interface and low-privilege authentication.

Root Cause

The root cause is improper neutralization of user-supplied input passed to a SQL interpreter, classified as [CWE-74]. The del parameter is concatenated into a query string instead of being bound through prepared statements. PHPGurukul applications historically rely on the deprecated mysqli query patterns without parameter binding, which propagates this class of bug across multiple endpoints.

Attack Vector

The attack vector is network-based and requires no user interaction beyond the attacker. An authenticated user with admin panel access submits a crafted HTTP request to /admin/manage-incomingvehicle.php with a malicious del value. Payloads can include UNION-based extraction, boolean blind injection, or stacked queries depending on the database driver configuration. Because the exploit has been disclosed publicly via the GitHub Issue Tracker and VulDB #316142, automated scanners may incorporate it.

No verified proof-of-concept code is reproduced here. Refer to the VulDB entry for documented exploitation details.

Detection Methods for CVE-2025-7492

Indicators of Compromise

  • HTTP requests to /admin/manage-incomingvehicle.php containing SQL meta-characters such as ', --, UNION, or SLEEP( in the del parameter
  • Unusual database errors logged by the application referencing the del argument
  • Unexpected DELETE, UNION SELECT, or INFORMATION_SCHEMA queries in MySQL/MariaDB logs originating from the application user
  • Administrative session activity from unfamiliar IP addresses targeting the incoming vehicle management page

Detection Strategies

  • Deploy web application firewall signatures that flag SQL syntax in the del query parameter of PHPGurukul endpoints
  • Enable MySQL general query logging temporarily to identify malformed or chained statements originating from manage-incomingvehicle.php
  • Correlate authentication events with admin page access patterns to detect compromised low-privilege accounts being abused for injection

Monitoring Recommendations

  • Alert on repeated 500-series HTTP responses from /admin/manage-incomingvehicle.php, which often accompany blind injection probing
  • Monitor outbound database traffic for anomalous result-set sizes that could indicate data exfiltration
  • Track failed and successful logins to the admin panel and flag accounts performing destructive operations outside normal hours

How to Mitigate CVE-2025-7492

Immediate Actions Required

  • Restrict network access to the /admin/ directory using IP allowlists or VPN-gated access until a patched build is available
  • Rotate credentials for all admin accounts on the Vehicle Parking Management System
  • Review database audit logs for evidence of del-parameter abuse and unauthorized record modifications
  • Place the application behind a web application firewall configured to block SQL injection patterns

Patch Information

No official vendor patch has been published for CVE-2025-7492 at the time of writing. Administrators should monitor the PHPGurukul Homepage for updates and apply fixes that introduce prepared statements for the del parameter and similar inputs across the application.

Workarounds

  • Manually patch /admin/manage-incomingvehicle.php to cast $_GET['del'] to an integer before use in the SQL query
  • Apply parameterized queries using mysqli prepared statements or PDO with bound parameters across the codebase
  • Disable or remove the incoming vehicle management feature if it is not required for operations
  • Take the application offline if it is internet-exposed and not actively maintained, given the public disclosure of exploit details
bash
# Example WAF rule (ModSecurity) to block SQLi against the del parameter
SecRule REQUEST_URI "@contains /admin/manage-incomingvehicle.php" \
  "chain,phase:2,deny,status:403,id:1007492,msg:'Block CVE-2025-7492 SQLi attempt'"
  SecRule ARGS:del "@rx (?i)(union|select|sleep\(|--|';|/\*)" "t:none,t:urlDecodeUni"

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

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