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Vulnerability Database/CVE-2025-11396

CVE-2025-11396: Simple Food Ordering System SQLi Flaw

CVE-2025-11396 is a SQL injection vulnerability in Simple Food Ordering System 1.0 affecting the product.php file. Attackers can exploit this remotely to manipulate databases. This article covers technical details, impact, and mitigations.

Published:

CVE-2025-11396 Overview

A SQL Injection vulnerability has been identified in code-projects Simple Food Ordering System version 1.0. The vulnerability exists in the /product.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 leading to unauthorized data access, data manipulation, or complete database compromise.

Critical Impact

Remote attackers can exploit this SQL injection vulnerability to extract sensitive data, modify database contents, or potentially gain unauthorized access to the underlying system through database-level attacks.

Affected Products

  • Fabian Simple Food Ordering System 1.0

Discovery Timeline

  • 2025-10-07 - CVE-2025-11396 published to NVD
  • 2025-10-09 - Last updated in NVD database

Technical Details for CVE-2025-11396

Vulnerability Analysis

This vulnerability is classified as SQL Injection (CWE-89) and falls under the broader category of Injection vulnerabilities (CWE-74). The flaw exists in the /product.php file where user-supplied input through the Category parameter is directly incorporated into SQL queries without proper sanitization or parameterization.

The vulnerability can be exploited remotely without requiring authentication, making it accessible to any attacker with network access to the application. The exploit has been publicly disclosed, increasing the risk of widespread exploitation against vulnerable installations.

Root Cause

The root cause of this vulnerability is improper input validation and lack of parameterized queries in the /product.php file. When the application receives the Category parameter, it appears to directly concatenate this user-controlled input into SQL query strings rather than using prepared statements or proper input sanitization techniques. This classic SQL injection pattern allows attackers to break out of the intended query context and inject arbitrary SQL commands.

Attack Vector

The attack is network-based and requires no user interaction or prior authentication. An attacker can craft malicious HTTP requests containing SQL injection payloads in the Category parameter of requests to /product.php.

The exploitation mechanism involves sending specially crafted input values that include SQL syntax characters and commands. When processed by the vulnerable application, these payloads modify the intended SQL query behavior, allowing the attacker to extract data from other tables, bypass authentication logic, modify or delete database records, or potentially execute operating system commands if database permissions allow.

Technical details and proof-of-concept information are available through the GitHub Issue CVE Discussion and the VulDB Entry #327333.

Detection Methods for CVE-2025-11396

Indicators of Compromise

  • Unusual SQL syntax characters in HTTP request parameters targeting /product.php, including single quotes, double quotes, semicolons, and SQL keywords
  • Error messages in application logs indicating SQL syntax errors or database query failures
  • Unexpected database queries or access patterns in database audit logs
  • Web server access logs showing requests to /product.php with abnormally long or encoded Category parameter values

Detection Strategies

  • Deploy a Web Application Firewall (WAF) with SQL injection detection rules specifically monitoring the /product.php endpoint
  • Implement database activity monitoring to detect anomalous query patterns or unauthorized data access attempts
  • Configure intrusion detection systems (IDS) to alert on common SQL injection attack signatures in HTTP traffic
  • Enable verbose application and database logging to capture potential exploitation attempts

Monitoring Recommendations

  • Review web server access logs for requests containing SQL injection patterns in the Category parameter
  • Monitor database query logs for unexpected queries, UNION statements, or administrative commands
  • Set up alerts for authentication failures or unusual data access patterns that may indicate successful exploitation
  • Track application error rates as increased SQL errors may indicate active exploitation attempts

How to Mitigate CVE-2025-11396

Immediate Actions Required

  • Take the Simple Food Ordering System offline or restrict network access if it is exposed to untrusted networks
  • Implement a Web Application Firewall (WAF) with SQL injection blocking rules in front of the application
  • Review database accounts used by the application and restrict privileges to minimum required access
  • Audit database contents for signs of unauthorized access or data manipulation

Patch Information

No official patch information is currently available from the vendor. Organizations using Simple Food Ordering System 1.0 should monitor the Code Projects Security Resource for any security updates. Given the nature of this project, users may need to implement their own fixes or consider alternative solutions.

Workarounds

  • Modify the /product.php source code to use prepared statements or parameterized queries for all database interactions
  • Implement input validation to reject any Category parameter values containing SQL metacharacters
  • Deploy the application behind a reverse proxy with SQL injection filtering capabilities
  • Restrict database user privileges so the application account cannot execute dangerous operations like DROP, DELETE, or access sensitive tables
bash
# Example WAF rule for Apache ModSecurity
SecRule ARGS:Category "@rx (\b(SELECT|UNION|INSERT|UPDATE|DELETE|DROP|EXEC|EXECUTE)\b|--|;|'|\"|\/\*)" \
    "id:100001,phase:2,deny,status:403,log,msg:'SQL Injection attempt on Category parameter'"

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

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