CVE-2024-3445: Laundry Shop Management System SQLi Flaw

CVE-2024-3445 Overview

A critical SQL injection vulnerability has been identified in SourceCodester Laundry Management System version 1.0. This vulnerability exists in the /karyawan/laporan_filter file where improper handling of the data_karyawan parameter allows attackers to inject malicious SQL commands. The vulnerability can be exploited remotely without authentication, potentially allowing attackers to access, modify, or delete sensitive database contents.

Critical Impact
Unauthenticated remote attackers can execute arbitrary SQL commands against the backend database, potentially leading to complete database compromise, unauthorized data access, data manipulation, and system takeover.

Affected Products

SourceCodester Laundry Management System 1.0
Oretnom23 Laundry Shop Management System 1.0

Discovery Timeline

2024-04-08 - CVE CVE-2024-3445 published to NVD
2025-01-17 - Last updated in NVD database

Technical Details for CVE-2024-3445

Vulnerability Analysis

This SQL injection vulnerability stems from inadequate input validation in the employee reporting functionality of the Laundry Management System. The application fails to properly sanitize user-supplied input passed through the data_karyawan parameter before incorporating it into SQL queries. This allows attackers to craft malicious input that breaks out of the intended query structure and execute arbitrary SQL commands against the underlying database.

The vulnerability is particularly severe because it requires no authentication or user interaction to exploit. An attacker can simply send crafted HTTP requests to the vulnerable endpoint and manipulate the database directly. This could result in unauthorized access to sensitive customer information, employee data, financial records, and potentially allow complete control over the application's data layer.

Root Cause

The root cause of this vulnerability is a classic input validation failure where user-controlled data (the data_karyawan parameter) is concatenated directly into SQL queries without proper sanitization, parameterization, or use of prepared statements. The application does not employ adequate defensive coding practices to prevent SQL injection attacks, leaving the database exposed to malicious manipulation.

Attack Vector

The attack can be initiated remotely over the network by sending specially crafted HTTP requests to the /karyawan/laporan_filter endpoint. The attacker manipulates the data_karyawan parameter to inject SQL syntax that alters the intended query behavior.

Typical exploitation scenarios include:

Data Exfiltration: Using UNION-based injection to extract sensitive data from other database tables
Authentication Bypass: Manipulating queries to bypass login mechanisms
Data Manipulation: Inserting, updating, or deleting records in the database
Privilege Escalation: Modifying user roles or creating administrative accounts
Database Enumeration: Extracting database schema, table names, and column information

The exploit has been publicly disclosed, with proof-of-concept details available in the GitHub PoC Repository, increasing the risk of widespread exploitation.

Detection Methods for CVE-2024-3445

Indicators of Compromise

Unusual HTTP requests to /karyawan/laporan_filter containing SQL syntax characters such as single quotes ('), double dashes (--), semicolons (;), or UNION statements
Database error messages appearing in application logs or HTTP responses indicating malformed SQL queries
Unexpected database queries or query patterns in database audit logs, particularly those involving system tables or multiple table joins
Evidence of data exfiltration or unauthorized data access in application or network logs

Detection Strategies

Deploy Web Application Firewall (WAF) rules to detect and block common SQL injection patterns targeting the data_karyawan parameter
Enable comprehensive logging for all requests to the /karyawan/laporan_filter endpoint and monitor for suspicious payloads
Implement database activity monitoring to alert on unusual query patterns, including queries against system tables or excessive UNION operations
Use intrusion detection systems (IDS) with signatures for SQL injection attack patterns

Monitoring Recommendations

Monitor HTTP request logs for requests containing SQL metacharacters or injection keywords targeting vulnerable endpoints
Enable database audit logging to track all queries executed, particularly those involving sensitive tables
Set up alerts for database errors that may indicate exploitation attempts
Review network traffic for unusual patterns of requests to the Laundry Management System application

How to Mitigate CVE-2024-3445

Immediate Actions Required

Take the Laundry Management System offline or restrict network access until remediation is complete
Implement input validation and sanitization for the data_karyawan parameter as an interim measure
Deploy WAF rules to block SQL injection attempts targeting the vulnerable endpoint
Review database logs for evidence of prior exploitation and assess potential data breach impact
Consider implementing IP allowlisting to restrict access to trusted networks only

Patch Information

As of the last update, no official vendor patch has been released by SourceCodester/Oretnom23 for this vulnerability. Organizations using this software should contact the vendor for remediation guidance or consider the following alternatives:

Upgrade to a newer version if one becomes available that addresses this vulnerability
Apply custom code fixes to implement prepared statements and parameterized queries
Consider migrating to an alternative, actively maintained laundry management solution

For additional technical details, refer to the VulDB Entry #259702 and VulDB CTI Entry.

Workarounds

Modify the application source code to use parameterized queries or prepared statements for all database interactions involving user input
Implement strict input validation to reject any input containing SQL metacharacters in the data_karyawan parameter
Deploy a Web Application Firewall with SQL injection protection rules in front of the application
Restrict network access to the application to trusted IP addresses or VPN-only access
Run the database with least-privilege permissions to limit the impact of potential exploitation

bash

# Example WAF rule configuration (ModSecurity)
# Block SQL injection patterns in data_karyawan parameter
SecRule ARGS:data_karyawan "@detectSQLi" \
    "id:1001,\
    phase:2,\
    deny,\
    status:403,\
    log,\
    msg:'SQL Injection attempt detected in data_karyawan parameter',\
    tag:'CVE-2024-3445'"