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CVE Vulnerability Database

CVE-2025-3188: E-diary Management System SQLi Vulnerability

CVE-2025-3188 is a critical SQL injection flaw in PHPGurukul E-diary Management System 1.0 affecting the add-notes.php file. Attackers can exploit this remotely to compromise databases. This article covers technical details, affected versions, impact, and mitigation strategies.

Published:

CVE-2025-3188 Overview

A SQL injection vulnerability has been discovered in PHPGurukul e-Diary Management System version 1.0. The vulnerability exists in the /add-notes.php file, where the Category parameter is not properly sanitized before being used in SQL queries. This allows remote attackers to inject malicious SQL commands, potentially compromising the underlying database and sensitive user information.

Critical Impact

Remote attackers can exploit this SQL injection vulnerability to extract sensitive data, modify database contents, or potentially execute arbitrary commands on the underlying database server without authentication.

Affected Products

  • PHPGurukul e-Diary Management System 1.0
  • Web applications using vulnerable /add-notes.php endpoint

Discovery Timeline

  • 2025-04-04 - CVE-2025-3188 published to NVD
  • 2025-04-08 - Last updated in NVD database

Technical Details for CVE-2025-3188

Vulnerability Analysis

This SQL injection vulnerability affects the /add-notes.php file in PHPGurukul e-Diary Management System. The application fails to properly sanitize user-supplied input in the Category parameter before incorporating it into SQL queries. This classic input validation flaw allows attackers to manipulate SQL statements executed by the backend database.

The vulnerability can be exploited remotely over the network without requiring any authentication or user interaction, making it particularly dangerous for internet-facing deployments of this application. Successful exploitation could lead to unauthorized access to stored diary entries, user credentials, and other sensitive information maintained in the database.

Root Cause

The root cause of this vulnerability is improper input validation (CWE-89: SQL Injection, CWE-74: Injection). The application directly concatenates user-supplied data from the Category parameter into SQL queries without proper sanitization, parameterized queries, or prepared statements. This allows specially crafted input containing SQL metacharacters to alter the intended query logic.

Attack Vector

The attack vector is network-based, allowing remote exploitation. An attacker can send malicious HTTP requests to the /add-notes.php endpoint with a crafted Category parameter containing SQL injection payloads. The exploit has been publicly disclosed, increasing the risk of widespread exploitation. The attack requires no authentication and no user interaction, as the vulnerable endpoint processes the malicious input directly.

The vulnerability mechanism involves the unsanitized Category parameter being passed directly to SQL query construction, allowing attackers to break out of the intended query context and inject arbitrary SQL commands. For technical details, refer to the GitHub Issue Discussion.

Detection Methods for CVE-2025-3188

Indicators of Compromise

  • Unusual SQL error messages in application or web server logs referencing /add-notes.php
  • HTTP requests to /add-notes.php containing SQL metacharacters such as single quotes, UNION, SELECT, or -- comment sequences in the Category parameter
  • Database query logs showing malformed or unexpected queries originating from the e-Diary application
  • Evidence of data exfiltration or unauthorized database access attempts

Detection Strategies

  • Deploy Web Application Firewall (WAF) rules to detect and block SQL injection patterns targeting the Category parameter
  • Monitor HTTP access logs for suspicious requests to /add-notes.php containing encoded or plaintext SQL injection payloads
  • Implement database activity monitoring to detect anomalous query patterns or unauthorized data access
  • Configure intrusion detection systems with signatures for common SQL injection attack vectors

Monitoring Recommendations

  • Enable verbose logging for the web application and database to capture detailed request and query information
  • Set up alerts for failed database queries or SQL syntax errors that may indicate injection attempts
  • Monitor network traffic for data exfiltration patterns following SQL injection attempts
  • Regularly review access logs for the /add-notes.php endpoint for suspicious activity patterns

How to Mitigate CVE-2025-3188

Immediate Actions Required

  • Restrict access to the PHPGurukul e-Diary Management System to trusted networks or users until a patch is available
  • Implement input validation and sanitization for all user-supplied parameters, especially the Category field
  • Deploy a Web Application Firewall with SQL injection protection rules in front of the application
  • Review database permissions to ensure the application uses least-privilege access

Patch Information

As of the last update on 2025-04-08, no official vendor patch has been released for this vulnerability. Organizations should monitor the PHP Gurukul Blog for security updates. In the absence of an official patch, implement the recommended workarounds and consider replacing the vulnerable component with a more secure alternative.

Workarounds

  • Implement prepared statements or parameterized queries in the /add-notes.php file to prevent SQL injection
  • Add server-side input validation to sanitize the Category parameter, rejecting any input containing SQL metacharacters
  • Temporarily disable or restrict access to the /add-notes.php functionality until proper fixes can be implemented
  • Use a reverse proxy or WAF to filter malicious requests before they reach the application
bash
# Example Apache ModSecurity rule to block SQL injection attempts
SecRule ARGS:Category "@detectSQLi" \
    "id:1001,\
    phase:2,\
    block,\
    log,\
    msg:'SQL Injection attempt detected in Category parameter',\
    severity:'CRITICAL'"

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

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