CVE-2024-10336 Overview
A critical SQL injection vulnerability has been identified in the SourceCodeHero Clothes Recommendation System version 1.0. This vulnerability exists in the Admin Login Page component, specifically within the /admin/index.php file. The flaw allows remote attackers to manipulate the t1 parameter to inject malicious SQL queries, potentially compromising the entire database backend and gaining unauthorized administrative access to the application.
Critical Impact
Unauthenticated attackers can exploit this SQL injection vulnerability remotely to bypass authentication, extract sensitive data, modify database contents, or potentially achieve further system compromise through database-level attacks.
Affected Products
- SourceCodeHero Clothes Recommendation System 1.0
- clothes_recommendation_system_project clothes_recommendation_system
Discovery Timeline
- 2024-10-24 - CVE-2024-10336 published to NVD
- 2024-10-28 - Last updated in NVD database
Technical Details for CVE-2024-10336
Vulnerability Analysis
This vulnerability is classified as CWE-89 (Improper Neutralization of Special Elements used in an SQL Command), commonly known as SQL Injection. The Admin Login Page at /admin/index.php fails to properly sanitize user-supplied input in the t1 parameter before incorporating it into SQL queries. This allows attackers to inject arbitrary SQL commands that will be executed by the underlying database engine.
The network-accessible nature of this vulnerability means that any attacker with network access to the application can attempt exploitation without requiring any prior authentication or user interaction. The exploit has been publicly disclosed, increasing the risk of widespread exploitation attempts against vulnerable installations.
Root Cause
The root cause of this vulnerability is improper input validation and lack of parameterized queries in the Admin Login Page. The application directly concatenates user-controlled input from the t1 parameter into SQL statements without proper sanitization or the use of prepared statements. This classic web application security flaw allows attackers to break out of the intended query structure and inject malicious SQL code.
Attack Vector
The attack can be initiated remotely over the network targeting the /admin/index.php endpoint. An attacker submits a crafted HTTP request containing SQL injection payloads in the t1 parameter. Since no authentication is required to reach the login page, any network-connected attacker can attempt exploitation.
The vulnerability is exploited by injecting SQL syntax into the t1 parameter of the Admin Login Page. Typical attack payloads may include authentication bypass sequences, UNION-based data extraction queries, or time-based blind injection techniques. The injected code executes within the context of the database user configured for the application, potentially allowing full database access. For detailed technical analysis, refer to the VulDB entry for this vulnerability.
Detection Methods for CVE-2024-10336
Indicators of Compromise
- Unusual or malformed requests to /admin/index.php containing SQL syntax characters such as single quotes, double dashes, semicolons, or UNION keywords in the t1 parameter
- Database error messages appearing in HTTP responses from the admin login endpoint
- Unexpected database queries or access patterns in database logs
- Multiple failed or suspicious login attempts to the admin panel from external IP addresses
Detection Strategies
- Deploy Web Application Firewall (WAF) rules to detect and block SQL injection patterns targeting the /admin/index.php endpoint
- Implement application-layer logging to capture all requests to the admin login page with full parameter details
- Configure database activity monitoring to alert on anomalous query patterns or error rates
- Use intrusion detection systems (IDS) with signatures for common SQL injection attack patterns
Monitoring Recommendations
- Monitor web server access logs for requests to /admin/index.php containing suspicious characters or SQL keywords
- Enable database query logging and alert on queries containing unexpected syntax or attempting to access sensitive tables
- Track authentication events and alert on successful admin logins from unusual source IP addresses
- Implement rate limiting on the admin login endpoint to slow down automated injection testing
How to Mitigate CVE-2024-10336
Immediate Actions Required
- If the Clothes Recommendation System is internet-facing, immediately restrict access to the /admin/index.php endpoint using firewall rules or web server configuration
- Implement IP-based access controls to limit admin panel access to trusted networks only
- Deploy a Web Application Firewall with SQL injection protection rules in front of the application
- Audit the database for signs of unauthorized access or data exfiltration
Patch Information
No official patch information is currently available from the vendor. Organizations using this software should contact SourceCodeHero for remediation guidance or consider implementing the workarounds below. For additional details and updates, refer to the VulDB submission.
Workarounds
- Restrict network access to the admin login page to trusted IP addresses only using firewall rules
- Implement a reverse proxy with SQL injection filtering capabilities in front of the application
- If source code access is available, modify the /admin/index.php file to use parameterized queries or prepared statements for the t1 parameter
- Consider disabling the admin functionality entirely until a proper fix is available
- Monitor and log all access attempts to the admin endpoint for forensic purposes
To restrict access to the admin panel, organizations should implement network-level controls. Using .htaccess for Apache servers, access can be limited to specific IP addresses. For nginx deployments, the allow and deny directives within the location block for /admin/ can achieve similar protection. Organizations should consult their specific web server documentation for proper implementation.
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

