CVE-2025-4870 Overview
A critical SQL Injection vulnerability has been identified in itsourcecode Restaurant Management System version 1.0. This vulnerability exists in the /admin/menu_save.php file where the menu parameter is not properly sanitized, allowing attackers to inject malicious SQL queries. The vulnerability can be exploited remotely without authentication, potentially compromising the database integrity, confidentiality, and availability of the affected system.
Critical Impact
Unauthenticated remote attackers can exploit this SQL Injection vulnerability to extract, modify, or delete sensitive data from the restaurant management database, potentially compromising customer information, financial records, and administrative credentials.
Affected Products
- Adonesevangelista Restaurant Management System 1.0
- itsourcecode Restaurant Management System 1.0
Discovery Timeline
- May 18, 2025 - CVE-2025-4870 published to NVD
- May 21, 2025 - Last updated in NVD database
Technical Details for CVE-2025-4870
Vulnerability Analysis
This SQL Injection vulnerability (CWE-89) occurs due to improper neutralization of special elements used in SQL commands within the /admin/menu_save.php endpoint. The menu parameter accepts user-supplied input that is directly incorporated into database queries without adequate sanitization or parameterization. This classic injection flaw falls under CWE-74 (Improper Neutralization of Special Elements in Output Used by a Downstream Component).
The vulnerability is network-accessible and requires no privileges or user interaction to exploit, making it particularly dangerous for internet-facing deployments of this restaurant management application. Successful exploitation could allow attackers to bypass authentication mechanisms, access sensitive customer and business data, modify menu pricing and inventory records, or potentially achieve full database compromise.
Root Cause
The root cause stems from the application's failure to implement proper input validation and parameterized queries in the menu_save.php file. User-supplied data in the menu argument is concatenated directly into SQL statements rather than being treated as data through prepared statements or stored procedures. This lack of input sanitization allows attackers to break out of the intended SQL context and execute arbitrary database commands.
Attack Vector
The attack can be initiated remotely over the network against the administrative interface. An attacker crafts malicious input containing SQL metacharacters and injects it through the menu parameter in requests to /admin/menu_save.php. Since the exploit has been publicly disclosed, attackers with basic SQL Injection knowledge can leverage this vulnerability. The attack does not require authentication or any special privileges, and no user interaction is needed for successful exploitation.
The vulnerability allows attackers to perform various SQL Injection techniques including:
- Union-based injection to extract data from other tables
- Boolean-based blind injection to enumerate database contents
- Time-based blind injection for data exfiltration
- Potential stacked queries depending on database configuration
Detection Methods for CVE-2025-4870
Indicators of Compromise
- Unusual SQL error messages in web server logs related to /admin/menu_save.php
- HTTP requests to /admin/menu_save.php containing SQL metacharacters such as single quotes, semicolons, or UNION keywords in the menu parameter
- Database audit logs showing unexpected query patterns, failed authentication attempts, or bulk data access
- Anomalous administrative account creation or privilege modifications in the restaurant management system
Detection Strategies
- Deploy Web Application Firewall (WAF) rules to detect and block common SQL Injection patterns in requests to the menu management endpoint
- Implement application-level logging to capture and alert on suspicious parameter values containing SQL syntax
- Configure database activity monitoring to detect unusual query execution patterns or unauthorized data access
- Use intrusion detection systems with signatures for SQL Injection attack payloads
Monitoring Recommendations
- Enable detailed access logging for the /admin/ directory and review logs for suspicious activity patterns
- Monitor database connection logs for unusual client connections or query volumes
- Set up alerts for HTTP 500 errors from the menu_save.php endpoint which may indicate exploitation attempts
- Implement rate limiting on administrative endpoints to slow potential automated exploitation
How to Mitigate CVE-2025-4870
Immediate Actions Required
- Restrict network access to the /admin/ directory to trusted IP addresses only
- Implement a Web Application Firewall with SQL Injection protection rules in front of the application
- Disable or remove the Restaurant Management System if not critical to operations until a patch is available
- Review database accounts used by the application and apply principle of least privilege
Patch Information
No official vendor patch has been released at this time. Monitor the IT Source Code website for security updates. Organizations should consider implementing manual code fixes by modifying the menu_save.php file to use prepared statements with parameterized queries for all database operations involving the menu parameter.
For additional technical details and community discussion, refer to the GitHub CVE Issue Discussion and VulDB #309412.
Workarounds
- Implement input validation to reject or sanitize SQL metacharacters in the menu parameter before processing
- Add a reverse proxy or WAF layer that filters malicious SQL Injection payloads from incoming requests
- Restrict access to administrative functions using network-level access controls or VPN requirements
- Consider replacing direct SQL queries with ORM-based database access or stored procedures with strict input typing
# Example: Restrict access to admin directory via Apache .htaccess
<Directory "/var/www/html/admin">
Require ip 192.168.1.0/24
Require ip 10.0.0.0/8
</Directory>
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

