CVE-2024-7369 Overview
A critical SQL injection vulnerability has been identified in SourceCodester Simple Realtime Quiz System version 1.0. This vulnerability exists in the Login component, specifically in the /ajax.php?action=login endpoint. An unauthenticated attacker can exploit improper input validation in the username parameter to inject malicious SQL queries, potentially leading to unauthorized access, data exfiltration, or database manipulation.
Critical Impact
Unauthenticated attackers can remotely exploit this SQL injection vulnerability in the login function to bypass authentication, extract sensitive data from the database, or modify database contents without authorization.
Affected Products
- SourceCodester Simple Realtime Quiz System 1.0
- oretnom23 simple_realtime_quiz_system (all deployments using version 1.0)
Discovery Timeline
- 2024-08-01 - CVE-2024-7369 published to NVD
- 2024-08-07 - Last updated in NVD database
Technical Details for CVE-2024-7369
Vulnerability Analysis
This SQL injection vulnerability (CWE-89) resides in the login functionality of the Simple Realtime Quiz System. The application fails to properly sanitize user-supplied input in the username parameter before incorporating it into SQL queries. When a user submits login credentials, the application constructs a database query using the provided username value without adequate validation or parameterization.
The vulnerable endpoint /ajax.php?action=login processes authentication requests and directly concatenates user input into SQL statements. This allows attackers to craft malicious input that alters the intended query logic. The vulnerability can be exploited remotely without any prior authentication, making it particularly dangerous for internet-facing deployments.
Successful exploitation could enable attackers to bypass authentication mechanisms entirely, retrieve sensitive information including user credentials and quiz data, modify or delete database records, or potentially escalate to more severe attacks depending on database privileges and server configuration.
Root Cause
The root cause of this vulnerability is insufficient input validation and the use of unsanitized user input in SQL query construction. The application lacks proper parameterized queries or prepared statements when handling the username parameter during the login process. This classic SQL injection pattern occurs when dynamic SQL queries are built by concatenating user-controlled input directly into the query string without escaping or validating the input.
Attack Vector
The attack can be initiated remotely over the network without requiring authentication. An attacker targets the login endpoint by sending a specially crafted HTTP request to /ajax.php?action=login with a malicious payload in the username parameter.
The exploitation technique involves injecting SQL syntax that modifies the query logic. For example, an attacker could inject payload strings that evaluate to true conditions, bypassing password verification entirely. More sophisticated payloads could use UNION-based injection to extract data from other tables, time-based blind injection to enumerate the database structure, or stacked queries to execute additional SQL commands.
Technical details and proof-of-concept information are available via the GitHub Gist PoC and VulDB entry #273353.
Detection Methods for CVE-2024-7369
Indicators of Compromise
- Unusual login attempts with SQL syntax characters in the username field (e.g., single quotes, double dashes, UNION keywords)
- HTTP requests to /ajax.php?action=login containing encoded SQL injection payloads
- Database error messages in application logs indicating malformed SQL queries
- Unexpected successful authentication events from unknown sources
Detection Strategies
- Implement Web Application Firewall (WAF) rules to detect SQL injection patterns in POST data targeting the login endpoint
- Monitor application logs for SQL syntax errors or unusual query patterns originating from the authentication module
- Deploy intrusion detection signatures for common SQL injection payloads in HTTP POST requests
- Analyze authentication success/failure ratios for anomalies that may indicate injection-based bypass attempts
Monitoring Recommendations
- Enable detailed logging for all authentication attempts including full request parameters
- Set up alerts for multiple failed login attempts followed by sudden success from the same source
- Monitor database query logs for SELECT statements with unusual WHERE clause structures
- Implement real-time alerting on database errors related to syntax issues in the authentication workflow
How to Mitigate CVE-2024-7369
Immediate Actions Required
- Restrict network access to the Simple Realtime Quiz System to trusted IP ranges only
- Deploy a Web Application Firewall with SQL injection protection rules in front of the application
- Consider taking the application offline if it processes sensitive data until a proper fix is implemented
- Review database logs for evidence of prior exploitation attempts
Patch Information
As of the last NVD update on 2024-08-07, no official vendor patch has been released for this vulnerability. The application is developed by SourceCodester (oretnom23) and users should monitor the vendor's distribution channels for security updates. Given the publicly disclosed nature of this exploit, immediate protective measures are essential.
Workarounds
- Implement input validation at the application level to reject username inputs containing SQL metacharacters
- Deploy a reverse proxy or WAF configured to filter requests containing SQL injection patterns
- Modify the application code to use parameterized queries or prepared statements for the login functionality
- Restrict database user privileges to minimize the impact of successful SQL injection attacks
# Example WAF rule for ModSecurity to block SQL injection in login requests
SecRule REQUEST_URI "/ajax\.php\?action=login" "id:1001,phase:2,deny,status:403,chain"
SecRule ARGS:username "@detectSQLi" "log,msg:'SQL Injection attempt blocked in login'"
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.


