CVE-2024-10335: Sadat Garbage Collection SQLi Flaw

CVE-2024-10335 Overview

A critical SQL injection vulnerability has been identified in SourceCodester Garbage Collection Management System version 1.0. This vulnerability exists in the login.php file and allows unauthenticated attackers to manipulate the username and password parameters to inject malicious SQL queries. The vulnerability can be exploited remotely without any prior authentication, potentially allowing attackers to bypass authentication, extract sensitive data from the database, or compromise the entire application.

Critical Impact

This SQL injection vulnerability enables remote attackers to bypass authentication mechanisms, access or modify database contents, and potentially gain unauthorized administrative access to the Garbage Collection Management System.

Affected Products

• SourceCodester Garbage Collection Management System 1.0
• Sadat Garbage Collection Management System 1.0

Discovery Timeline

• 2024-10-24 - CVE-2024-10335 published to NVD
• 2024-10-28 - Last updated in NVD database

Technical Details for CVE-2024-10335

Vulnerability Analysis

This vulnerability represents a classic SQL injection flaw in the authentication mechanism of the Garbage Collection Management System. The login.php file fails to properly sanitize user-supplied input in both the username and password parameters before incorporating them into SQL queries. This improper input validation allows attackers to inject arbitrary SQL statements that are then executed by the database server with the same privileges as the application.

The initial researcher advisory specifically identified the username parameter as vulnerable, but security analysis indicates that the password parameter is likely affected as well due to similar handling patterns. This type of vulnerability is classified under CWE-89 (Improper Neutralization of Special Elements used in an SQL Command).

Root Cause

The root cause of this vulnerability is the lack of proper input sanitization and parameterized queries in the login authentication logic. The application directly concatenates user-supplied input into SQL query strings without using prepared statements or escaping special characters. This allows SQL metacharacters submitted by attackers to be interpreted as part of the SQL query rather than as literal data values.

Attack Vector

The attack can be initiated remotely over the network without requiring any authentication or user interaction. An attacker can craft a malicious HTTP request containing SQL injection payloads in the username or password fields of the login form. By injecting specially crafted SQL syntax, an attacker can manipulate the authentication query to return a true condition, effectively bypassing authentication. Additionally, time-based or union-based injection techniques could be used to extract database contents including user credentials, personal information, and system configuration data.

Typical SQL injection payloads for authentication bypass might include patterns such as ' OR '1'='1 or admin'-- that alter the query logic to always return a valid authentication result.

Detection Methods for CVE-2024-10335

Indicators of Compromise

• Unusual or malformed login attempts containing SQL metacharacters (single quotes, double dashes, semicolons)
• Multiple failed login attempts followed by successful authentication from the same source IP
• Database error messages appearing in HTTP responses or application logs
• Unexpected database queries in SQL server logs, particularly those containing UNION SELECT, OR 1=1, or comment sequences

Detection Strategies

• Deploy Web Application Firewall (WAF) rules to detect and block common SQL injection patterns in POST parameters
• Monitor application logs for authentication anomalies including unusual characters in username/password fields
• Implement SQL query logging at the database level to identify suspicious query patterns
• Use intrusion detection systems (IDS) with signatures for SQL injection attack payloads

Monitoring Recommendations

• Enable detailed logging for the login.php endpoint including all POST parameters
• Set up alerts for database errors or exceptions originating from authentication queries
• Monitor for unusual data exfiltration patterns or increased database read operations
• Track authentication success rates and investigate anomalous spikes in successful logins

How to Mitigate CVE-2024-10335

Immediate Actions Required

• Restrict network access to the Garbage Collection Management System to trusted IP addresses only
• Implement a Web Application Firewall (WAF) with SQL injection protection rules in front of the application
• Disable or remove the vulnerable application from production environments until patched
• Review database logs for evidence of exploitation and audit user accounts for unauthorized access

Patch Information

As of the last update on 2024-10-28, no official vendor patch has been released for this vulnerability. Organizations using SourceCodester Garbage Collection Management System 1.0 should contact the vendor for remediation guidance. For additional technical details, refer to the GitHub vulnerability documentation and the VulDB entry.

Workarounds

• Deploy a reverse proxy or WAF to filter SQL injection patterns in HTTP requests to login.php
• Implement IP-based access restrictions to limit who can access the login page
• If source code access is available, modify login.php to use prepared statements with parameterized queries
• Consider migrating to an alternative garbage collection management solution that follows secure coding practices

# Example WAF configuration (ModSecurity)
SecRule ARGS:username "@detectSQLi" "id:1001,phase:2,deny,status:403,msg:'SQL Injection detected in username parameter'"
SecRule ARGS:password "@detectSQLi" "id:1002,phase:2,deny,status:403,msg:'SQL Injection detected in password parameter'"