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CVE Vulnerability Database

CVE-2024-0496: Kashipara Billing Software SQLi Vulnerability

CVE-2024-0496 is a critical SQL injection vulnerability in Kashipara Billing Software 1.0 affecting the item_list_edit.php file. Attackers can exploit this remotely. This article covers technical details, impact, and mitigation.

Published:

CVE-2024-0496 Overview

A critical SQL injection vulnerability has been identified in Kashipara Billing Software version 1.0. The vulnerability exists in the item_list_edit.php file within the HTTP POST Request Handler component, where improper handling of the id parameter allows attackers to inject malicious SQL commands. This flaw enables remote attackers to execute arbitrary SQL queries against the underlying database without authentication, potentially leading to complete database compromise.

Critical Impact

Remote attackers can exploit this SQL injection vulnerability to extract, modify, or delete sensitive billing data, customer information, and potentially gain unauthorized access to the underlying system.

Affected Products

  • Kashipara Billing Software 1.0

Discovery Timeline

  • 2024-01-13 - CVE-2024-0496 published to NVD
  • 2024-11-21 - Last updated in NVD database

Technical Details for CVE-2024-0496

Vulnerability Analysis

This SQL injection vulnerability is classified as CWE-89 (Improper Neutralization of Special Elements used in an SQL Command). The flaw resides in the item_list_edit.php file, which processes HTTP POST requests without properly sanitizing user-supplied input. When the id parameter is manipulated with SQL metacharacters, the application fails to validate or escape the input before incorporating it into database queries.

The vulnerability can be exploited remotely without any authentication requirements, making it particularly dangerous for publicly accessible billing software installations. Successful exploitation could allow attackers to bypass authentication mechanisms, access sensitive financial records, modify billing data, or potentially execute operating system commands if the database permissions allow.

Root Cause

The root cause of this vulnerability is the lack of input validation and parameterized queries in the item_list_edit.php file. The application directly concatenates user-supplied data from the id parameter into SQL queries without proper sanitization or the use of prepared statements. This classic SQL injection pattern allows attackers to break out of the intended query structure and inject their own SQL commands.

Attack Vector

The attack is initiated remotely via network access to the vulnerable application. An attacker can craft malicious HTTP POST requests to the item_list_edit.php endpoint with SQL injection payloads in the id parameter. The attack requires no privileges or user interaction, making it easily exploitable.

The vulnerability affects the confidentiality, integrity, and availability of the application data. Attackers can read sensitive information from the database, modify or delete records, and potentially cause denial of service by corrupting critical data structures.

For detailed technical information about this vulnerability, refer to the GitHub SQL Injection Vulnerability Document and VulDB #250601.

Detection Methods for CVE-2024-0496

Indicators of Compromise

  • Unusual database query patterns or errors in application logs indicating malformed SQL syntax
  • Unexpected access to item_list_edit.php with abnormally long or encoded id parameter values
  • Database audit logs showing unauthorized data access, modifications, or privilege escalation attempts
  • Suspicious POST requests containing SQL keywords (UNION, SELECT, INSERT, DROP) in parameter values

Detection Strategies

  • Deploy Web Application Firewalls (WAF) with SQL injection detection rules targeting the item_list_edit.php endpoint
  • Implement database activity monitoring to detect anomalous query patterns or unauthorized data access
  • Enable detailed logging for HTTP POST requests to the affected component and analyze for injection patterns
  • Use intrusion detection systems (IDS) configured with signatures for common SQL injection payloads

Monitoring Recommendations

  • Monitor web server access logs for requests to item_list_edit.php with suspicious id parameter values
  • Configure database audit logging to track queries executed against sensitive billing tables
  • Set up alerts for database errors related to SQL syntax violations or unexpected query structures
  • Regularly review authentication logs for unauthorized access attempts following potential SQL injection exploitation

How to Mitigate CVE-2024-0496

Immediate Actions Required

  • Restrict network access to the Kashipara Billing Software to trusted IP addresses only
  • Implement a Web Application Firewall (WAF) to filter SQL injection attempts targeting the vulnerable endpoint
  • Review and audit all database accounts for least privilege access principles
  • Back up critical billing data and implement database integrity monitoring

Patch Information

At the time of publication, no official patch from Kashipara has been documented in the available references. Organizations using Kashipara Billing Software 1.0 should contact the vendor directly for security updates or implement the workarounds described below.

Workarounds

  • Deploy a WAF rule to block requests containing SQL metacharacters in the id parameter of item_list_edit.php
  • Implement network segmentation to isolate the billing software from untrusted networks
  • If source code access is available, modify item_list_edit.php to use prepared statements with parameterized queries
  • Consider restricting access to the billing software through VPN-only connections until a patch is available
bash
# Example WAF rule for ModSecurity to block SQL injection in the vulnerable parameter
SecRule ARGS:id "@detectSQLi" \
    "id:100001,\
    phase:2,\
    deny,\
    status:403,\
    log,\
    msg:'SQL Injection attempt detected in item_list_edit.php id parameter',\
    tag:'CVE-2024-0496'"

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

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