Skip to main content
CVE Vulnerability Database
Vulnerability Database/CVE-2025-11662

CVE-2025-11662: Best Salon Management System SQLi Flaw

CVE-2025-11662 is a SQL injection vulnerability in Mayurik Best Salon Management System 1.0 affecting the booking.php file. Attackers can exploit the serv_id parameter remotely to execute malicious SQL queries.

Published:

CVE-2025-11662 Overview

A SQL injection vulnerability has been discovered in SourceCodester Best Salon Management System version 1.0. The vulnerability exists in the /booking.php file where the serv_id parameter is not properly sanitized before being used in SQL queries. This flaw allows remote attackers to inject malicious SQL statements through the vulnerable parameter, potentially enabling unauthorized access to sensitive database information, data manipulation, or complete database compromise.

Critical Impact

Remote attackers can exploit this SQL injection vulnerability to extract sensitive customer data, modify booking records, or potentially gain unauthorized access to the underlying database system without authentication.

Affected Products

  • Mayurik Best Salon Management System 1.0
  • SourceCodester Best Salon Management System (all versions prior to patch)

Discovery Timeline

  • 2025-10-13 - CVE-2025-11662 published to NVD
  • 2025-10-17 - Last updated in NVD database

Technical Details for CVE-2025-11662

Vulnerability Analysis

This SQL injection vulnerability (CWE-89) affects the booking functionality of the Best Salon Management System. The application fails to properly validate and sanitize user-supplied input in the serv_id parameter within the /booking.php endpoint. When a user submits a booking request, the serv_id value is directly incorporated into SQL queries without adequate input validation or parameterized queries, creating a classic injection point.

The vulnerability is classified under both CWE-74 (Improper Neutralization of Special Elements in Output Used by a Downstream Component) and CWE-89 (SQL Injection), indicating the application does not properly neutralize special SQL characters before incorporating user input into database queries.

Root Cause

The root cause of this vulnerability is improper input validation in the /booking.php file. The serv_id parameter is directly concatenated into SQL query strings without proper sanitization, escaping, or the use of parameterized queries (prepared statements). This allows attackers to break out of the intended SQL query structure and inject arbitrary SQL commands.

Attack Vector

The attack can be executed remotely over the network without requiring authentication. An attacker can craft malicious HTTP requests to the /booking.php endpoint with specially crafted serv_id parameter values containing SQL injection payloads. The injection can be used to:

  • Extract sensitive data from the database using UNION-based or error-based techniques
  • Bypass authentication mechanisms
  • Modify or delete database records
  • Potentially execute operating system commands if database permissions allow

The vulnerability is publicly documented and exploit details have been disclosed on GitHub, making exploitation accessible to attackers with basic SQL injection knowledge.

Detection Methods for CVE-2025-11662

Indicators of Compromise

  • Unusual or malformed requests to /booking.php containing SQL syntax characters such as single quotes ('), double dashes (--), semicolons (;), or UNION keywords
  • Database error messages appearing in application logs or responses
  • Unexpected database queries or data access patterns in database logs
  • Anomalous traffic patterns targeting the booking functionality

Detection Strategies

  • Implement Web Application Firewall (WAF) rules to detect SQL injection patterns in the serv_id parameter
  • Monitor HTTP request logs for suspicious payloads containing SQL keywords (SELECT, UNION, INSERT, DELETE, DROP)
  • Enable database query logging and alert on queries containing injection signatures
  • Deploy intrusion detection systems (IDS) with SQL injection detection rules

Monitoring Recommendations

  • Configure real-time alerting for requests to /booking.php containing SQL metacharacters
  • Implement database activity monitoring to detect unusual query patterns or unauthorized data access
  • Review web server access logs regularly for evidence of exploitation attempts
  • Monitor for data exfiltration indicators such as unusual outbound traffic volumes

How to Mitigate CVE-2025-11662

Immediate Actions Required

  • Restrict public access to the /booking.php endpoint until a patch is applied
  • Implement WAF rules to block SQL injection attempts targeting the serv_id parameter
  • Review and audit all database access logs for signs of prior exploitation
  • Consider taking the affected application offline if it contains sensitive customer data

Patch Information

No official vendor patch has been released at this time. Organizations using SourceCodester Best Salon Management System should monitor SourceCodester for security updates. Additional technical details about this vulnerability are available at VulDB #328081.

Workarounds

  • Implement input validation to sanitize the serv_id parameter, allowing only numeric values
  • Modify the application code to use parameterized queries (prepared statements) instead of string concatenation
  • Deploy a Web Application Firewall (WAF) with SQL injection protection rules
  • Apply the principle of least privilege to database user accounts used by the application
bash
# Example WAF rule to block SQL injection in serv_id parameter
# For ModSecurity-based WAF
SecRule ARGS:serv_id "@detectSQLi" \
    "id:1001,\
    phase:2,\
    deny,\
    status:403,\
    msg:'SQL Injection attempt detected in serv_id parameter',\
    logdata:'Matched Data: %{MATCHED_VAR}'"

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

Default Legacy - Prefooter | Experience the World’s Most Advanced Cybersecurity Platform

Experience the Most Advanced Cybersecurity Platform

See how the world’s most intelligent, autonomous cybersecurity platform can protect your organization today and into the future.