PHPGurukul Nipah Virus Testing Management System SQL Injection Vulnerability in Phlebotomist Editing Feature

Vulnerability

A critical SQL injection vulnerability has been identified in the PHPGurukul Nipah Virus Testing Management System version 1.0. The issue arises in the file '/edit-phlebotomist.php', where the 'mobilenumber' parameter is processed. This vulnerability allows remote attackers to inject malicious SQL queries, potentially leading to unauthorized database access, data manipulation, and disruption of services.

Impact

Exploitation of this vulnerability allows attackers to inject malicious SQL queries through the 'mobilenumber' parameter, leading to unauthorized database access and manipulation. This could include leaking sensitive data, altering or deleting database information, and in some cases, executing administrative operations on the database. The vulnerability could also be exploited to disrupt normal application services.

Reproduction

The vulnerability can be reproduced by sending a POST request to '/nipah/edit-phlebotomist.php' with the 'mobilenumber' parameter. The request should include a crafted SQL payload that exploits the application's SQL query handling. This can be done using tools like sqlmap, which automate the injection process and demonstrate the vulnerability by extracting database information.

Remediation

To address this vulnerability, it is recommended to implement prepared statements and parameter binding to prevent SQL injection. Additionally, input validation and filtering should be applied to ensure that user input meets expected formats, blocking malicious data. Finally, database user permissions should be minimized, granting only necessary access rights to the database.

Added: Jun 9, 2025, 7:46 PM
Updated: Jun 9, 2025, 7:46 PM

Vulnerability Rating

Custom Algorithm
spread
0.8
impact
5.0
exploitability
9.5
remediation
0.0
relevance
0.0
threat
6.4
urgency
2.9
incentive
10.0

Our algorithm analyzes dozens of metrics to generate these 8 key vulnerability categories, which are then combined to calculate the overall risk score.