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CVE Vulnerability Database

CVE-2026-2172: Fabian Admission System SQLi Vulnerability

CVE-2026-2172 is a SQL injection vulnerability in Fabian Online Application System for Admission 1.0 affecting the login endpoint. Attackers can exploit this remotely to manipulate database queries. This article covers technical details, affected versions, impact assessment, and mitigation strategies.

Published:

CVE-2026-2172 Overview

A SQL injection vulnerability has been identified in the Fabian Online Application System for Admission version 1.0. The vulnerability exists within the Login Endpoint functionality of the file enrollment/index.php. An attacker can exploit this flaw by manipulating input parameters to inject malicious SQL queries, potentially leading to unauthorized data access, modification, or deletion. The attack can be executed remotely without authentication, and the exploit has been publicly disclosed.

Critical Impact

Remote attackers can exploit this SQL injection vulnerability to bypass authentication, extract sensitive student admission data, or modify database contents without requiring any credentials.

Affected Products

  • Fabian Online Application System for Admission 1.0
  • enrollment/index.php Login Endpoint component

Discovery Timeline

  • 2026-02-08 - CVE-2026-2172 published to NVD
  • 2026-02-11 - Last updated in NVD database

Technical Details for CVE-2026-2172

Vulnerability Analysis

This vulnerability stems from improper input validation in the Login Endpoint of the enrollment system. The enrollment/index.php file fails to properly sanitize user-supplied input before incorporating it into SQL queries. This allows attackers to craft malicious input that alters the intended SQL query logic, enabling unauthorized database operations.

The vulnerability is classified under CWE-89 (Improper Neutralization of Special Elements used in an SQL Command) and CWE-74 (Improper Neutralization of Special Elements in Output Used by a Downstream Component). These weaknesses indicate that the application does not adequately filter or escape special characters in user input, allowing SQL syntax to be injected directly into database queries.

Root Cause

The root cause of this vulnerability is the lack of parameterized queries or prepared statements in the enrollment/index.php file. User-controlled input from the login form is directly concatenated into SQL queries without proper sanitization or escaping. This classic SQL injection pattern allows attackers to manipulate query structure by injecting SQL metacharacters such as single quotes, semicolons, and comment sequences.

Attack Vector

The vulnerability is exploitable remotely over the network without requiring any authentication or user interaction. An attacker can target the Login Endpoint by submitting specially crafted input through the login form fields. Common exploitation techniques include:

  • Authentication bypass by injecting conditions that always evaluate to true (e.g., ' OR '1'='1)
  • Union-based injection to extract data from other database tables
  • Error-based injection to enumerate database structure
  • Time-based blind injection when direct output is not available

The attack surface is significant as the login endpoint is typically exposed to unauthenticated users, making this vulnerability easily accessible to remote attackers. Additional technical details are available in the VulDB vulnerability entry.

Detection Methods for CVE-2026-2172

Indicators of Compromise

  • Unusual SQL error messages in application logs from enrollment/index.php
  • Login attempts containing SQL metacharacters (single quotes, double dashes, semicolons)
  • Abnormal database query patterns or unexpected query execution times
  • Unauthorized access to student admission records or administrative accounts

Detection Strategies

  • Deploy web application firewalls (WAF) with SQL injection detection rules targeting the /enrollment/index.php endpoint
  • Implement application-level logging to capture and analyze all input submitted to login forms
  • Configure database activity monitoring to detect anomalous queries or unauthorized data access
  • Use intrusion detection systems (IDS) with signatures for common SQL injection payloads

Monitoring Recommendations

  • Monitor HTTP request logs for patterns containing SQL keywords (SELECT, UNION, INSERT, DROP) in login parameters
  • Set up alerts for multiple failed login attempts followed by successful authentication
  • Track database query execution logs for queries originating from the enrollment application
  • Implement real-time alerting for any database errors related to malformed SQL syntax

How to Mitigate CVE-2026-2172

Immediate Actions Required

  • Restrict network access to the enrollment/index.php endpoint to trusted IP ranges if possible
  • Implement input validation to reject special characters in login form fields as a temporary measure
  • Deploy a web application firewall with SQL injection protection rules
  • Consider taking the affected application offline until a proper fix is implemented

Patch Information

No official vendor patch has been released at this time. The vulnerable software is a code-projects application, and administrators should monitor the Code Projects website for any updates. In the absence of an official patch, organizations should implement the workarounds described below or consider replacing the application with a more secure alternative.

Workarounds

  • Implement prepared statements or parameterized queries in the enrollment/index.php file to prevent SQL injection
  • Apply strict input validation using allowlists for acceptable characters in login fields
  • Use a web application firewall (WAF) to filter malicious SQL injection payloads
  • Implement the principle of least privilege for database accounts used by the application
bash
# Example WAF rule configuration for ModSecurity
# Add to modsecurity.conf to block common SQL injection patterns
SecRule ARGS "@detectSQLi" \
    "id:1001,\
    phase:2,\
    block,\
    msg:'SQL Injection Attempt Detected',\
    logdata:'Matched Data: %{MATCHED_VAR} found within %{MATCHED_VAR_NAME}',\
    severity:'CRITICAL'"

Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.

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