CVE-2025-11434: Student Transcript System SQLi Vulnerability

CVE-2025-11434 Overview

A SQL injection vulnerability has been identified in itsourcecode Student Transcript Processing System version 1.0. The vulnerability affects the /login.php file, where manipulation of the uname parameter allows attackers to inject malicious SQL queries. This weakness enables remote attackers to potentially bypass authentication, extract sensitive data, or manipulate database records without requiring any authentication or user interaction.

Critical Impact

Remote attackers can exploit this SQL injection flaw to bypass authentication mechanisms, extract student records and transcript data, or potentially gain unauthorized administrative access to the student management system.

Affected Products

• Fabian Student Transcript Processing System 1.0
• itsourcecode Student Transcript Processing System /login.php component

Discovery Timeline

• 2025-10-08 - CVE-2025-11434 published to NVD
• 2026-02-24 - Last updated in NVD database

Technical Details for CVE-2025-11434

Vulnerability Analysis

This vulnerability is classified under CWE-89 (SQL Injection) and CWE-74 (Improper Neutralization of Special Elements in Output Used by a Downstream Component). The flaw exists in the login functionality of the Student Transcript Processing System, specifically in how the application handles the uname parameter submitted to /login.php.

When a user submits credentials through the login form, the application fails to properly sanitize or parameterize the username input before incorporating it into SQL queries. This allows an attacker to craft malicious input that modifies the intended query structure, potentially granting unauthorized access or exposing database contents.

The exploit has been made publicly available, increasing the risk of widespread attacks against unpatched installations. Educational institutions using this system may be particularly at risk due to the sensitive nature of student transcript data.

Root Cause

The root cause of this vulnerability is improper input validation and the use of unsanitized user input directly in SQL query construction. The /login.php file does not employ prepared statements or parameterized queries when processing the uname argument, allowing special SQL characters and commands to be interpreted as part of the query rather than as literal string values.

Attack Vector

The attack can be launched remotely over the network without requiring authentication. An attacker simply needs to access the login page and submit a crafted payload in the username field. The attack requires no user interaction and can be automated using common SQL injection tools.

A typical attack scenario involves an attacker submitting specially crafted input in the uname field that modifies the authentication query logic. For example, injecting SQL syntax that always evaluates to true can bypass password verification entirely. The attacker could also use UNION-based injection to extract data from other database tables, potentially accessing all student records, grades, and personal information stored in the system.

For detailed technical analysis and proof-of-concept information, refer to the GitHub Issue Discussion and VulDB entry #327371.

Detection Methods for CVE-2025-11434

Indicators of Compromise

• Unusual or malformed login attempts containing SQL syntax characters such as single quotes, double dashes, or semicolons in the uname parameter
• Database error messages appearing in web server logs or being returned to clients
• Unexpected database queries or data access patterns in database audit logs
• Multiple failed login attempts followed by successful authentication from the same source

Detection Strategies

• Implement Web Application Firewall (WAF) rules to detect and block common SQL injection patterns in HTTP POST requests to /login.php
• Configure intrusion detection systems to alert on SQL injection signatures in network traffic
• Enable database query logging and monitor for anomalous queries originating from the web application
• Review web server access logs for requests containing encoded or obfuscated SQL injection payloads

Monitoring Recommendations

• Enable verbose logging on the web server and database server to capture all authentication attempts
• Set up real-time alerting for database errors or exceptions generated during login operations
• Monitor for data exfiltration patterns such as unusually large response sizes from the login endpoint
• Implement rate limiting on the login endpoint to slow automated attack attempts

How to Mitigate CVE-2025-11434

Immediate Actions Required

• Restrict network access to the Student Transcript Processing System to trusted IP ranges only
• Place a Web Application Firewall in front of the application with SQL injection protection rules enabled
• Consider taking the application offline if it contains highly sensitive data until a proper fix can be implemented
• Review database logs for evidence of prior exploitation and audit user accounts for unauthorized access

Patch Information

No official vendor patch information is currently available for this vulnerability. System administrators should check the IT Source Code website for updates or consider implementing the source code fixes described in the workarounds section. Monitor the VulDB entry and GitHub issue for additional remediation guidance.

Workarounds

• Modify the /login.php source code to use prepared statements with parameterized queries for all database operations involving user input
• Implement input validation to reject or sanitize special characters in the uname field before processing
• Deploy a reverse proxy with ModSecurity or similar WAF capabilities configured to block SQL injection attempts
• Restrict database user permissions used by the web application to minimum required privileges

# Example: Restrict access to the vulnerable endpoint using Apache .htaccess
# Place this in the web root directory

<Files "login.php">
    Order Deny,Allow
    Deny from all
    Allow from 192.168.1.0/24
    Allow from 10.0.0.0/8
</Files>

# Enable ModSecurity SQL injection protection if available
# SecRuleEngine On
# SecRule ARGS "@detectSQLi" "id:1,deny,status:403,msg:'SQL Injection Detected'"