CVE-2026-5669 Overview
A SQL injection vulnerability has been identified in the Cyber-III Student-Management-System affecting the /login.php component. The vulnerability exists in the Parameter Handler where improper sanitization of the Password argument allows attackers to inject malicious SQL commands. This flaw enables remote attackers to manipulate database queries without authentication, potentially leading to unauthorized data access, data manipulation, or complete database compromise.
Critical Impact
Remote attackers can exploit this SQL injection vulnerability to bypass authentication, extract sensitive student data, or manipulate database contents without any prior access to the system.
Affected Products
- Cyber-III Student-Management-System (up to commit 1a938fa61e9f735078e9b291d2e6215b4942af3f)
- All rolling release versions prior to patching
Discovery Timeline
- 2026-04-06 - CVE-2026-5669 published to NVD
- 2026-04-07 - Last updated in NVD database
Technical Details for CVE-2026-5669
Vulnerability Analysis
This vulnerability is classified under CWE-74 (Improper Neutralization of Special Elements in Output Used by a Downstream Component), commonly known as injection. The flaw resides in the login functionality of the Student-Management-System, specifically within the /login.php file's Parameter Handler component.
When processing user authentication requests, the application fails to properly sanitize the Password parameter before incorporating it into SQL queries. This allows an attacker to craft malicious input that breaks out of the intended SQL statement structure and executes arbitrary database commands. The vulnerability is exploitable remotely over the network without requiring any authentication or user interaction.
The exploit has been publicly disclosed, increasing the risk of widespread exploitation. The project maintainers were notified through a GitHub Issue (#240) but have not yet responded to the security report.
Root Cause
The root cause of this vulnerability is the absence of proper input validation and parameterized queries in the authentication logic. The Password parameter is directly concatenated into SQL statements without escaping special characters or using prepared statements. This classic SQL injection pattern allows attackers to inject SQL metacharacters that alter the query's intended logic.
Attack Vector
The attack can be executed remotely over the network by submitting a specially crafted POST request to the /login.php endpoint. An attacker can manipulate the Password field with SQL injection payloads to bypass authentication checks, extract database contents using UNION-based or error-based techniques, or execute administrative database operations. No authentication is required to exploit this vulnerability, and the attack does not require any user interaction.
Common exploitation techniques for this type of vulnerability include:
- Authentication bypass using payloads like ' OR '1'='1
- Data exfiltration through UNION SELECT statements
- Blind SQL injection using time-based or boolean-based inference
- Potential database manipulation or destruction via stacked queries (if supported)
Detection Methods for CVE-2026-5669
Indicators of Compromise
- Unusual login attempts containing SQL metacharacters (', ", --, ;, OR, UNION) in POST request bodies
- Web server logs showing repeated requests to /login.php with malformed or suspicious parameter values
- Database logs indicating failed or unusual query patterns, especially those containing SQL keywords in unexpected contexts
- Evidence of data exfiltration or unauthorized database access following authentication anomalies
Detection Strategies
- Deploy Web Application Firewall (WAF) rules to detect and block common SQL injection patterns in the Password parameter
- Implement intrusion detection signatures for SQL injection payloads targeting /login.php
- Configure application logging to capture full request bodies for authentication endpoints
- Monitor for database errors that indicate SQL syntax issues resulting from injection attempts
Monitoring Recommendations
- Enable detailed logging on web servers and database systems to capture authentication-related activity
- Set up alerts for multiple failed login attempts or unusual query execution patterns
- Periodically review database audit logs for unauthorized data access or schema changes
- Monitor network traffic for unusual outbound data transfers that may indicate data exfiltration
How to Mitigate CVE-2026-5669
Immediate Actions Required
- Restrict network access to the Student-Management-System to trusted IP addresses only
- Deploy a Web Application Firewall (WAF) with SQL injection protection in front of the application
- Disable or take offline the vulnerable /login.php endpoint if possible until a patch is available
- Review database logs for evidence of prior exploitation attempts
Patch Information
As of the last update, the Cyber-III project has not released an official patch for this vulnerability. The project uses a rolling release model, and version details for affected and updated releases are not available. The vulnerability was reported via GitHub Issue #240, but the maintainers have not yet responded.
Organizations using this software should monitor the GitHub repository for updates and consider implementing the workarounds below until an official fix is released.
Workarounds
- Implement input validation at the application level to reject SQL metacharacters in the Password field
- Modify the codebase to use prepared statements with parameterized queries for all database interactions
- Deploy a reverse proxy with SQL injection filtering capabilities in front of the application
- Consider implementing a custom authentication middleware that sanitizes all user inputs before processing
# Example WAF rule configuration (ModSecurity)
# Block SQL injection attempts on login.php Password parameter
SecRule ARGS:Password "@detectSQLi" \
"id:100001,\
phase:2,\
deny,\
status:403,\
log,\
msg:'SQL Injection attempt detected in Password parameter',\
tag:'attack-sqli'"
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.


