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CVE Vulnerability Database

CVE-2026-2706: Patient Record Management System SQLi Flaw

CVE-2026-2706 is a SQL injection vulnerability in Patient Record Management System 1.0 affecting the /fecalysis_not.php file. Attackers can exploit the comp_id parameter remotely to compromise database integrity.

Published:

CVE-2026-2706 Overview

A SQL injection vulnerability has been discovered in code-projects Patient Record Management System version 1.0. The vulnerability exists in the /fecalysis_not.php file, where improper handling of the comp_id parameter allows attackers to inject malicious SQL commands. This flaw enables remote attackers with low-level privileges to manipulate database queries, potentially leading to unauthorized data access, modification, or deletion of sensitive patient records.

Critical Impact

Healthcare systems containing sensitive patient data are at risk. Successful exploitation could allow attackers to extract protected health information (PHI), modify medical records, or compromise the integrity of the patient management database.

Affected Products

  • code-projects Patient Record Management System 1.0
  • /fecalysis_not.php endpoint with vulnerable comp_id parameter

Discovery Timeline

  • 2026-02-19 - CVE-2026-2706 published to NVD
  • 2026-02-19 - Last updated in NVD database

Technical Details for CVE-2026-2706

Vulnerability Analysis

This SQL injection vulnerability (CWE-74: Improper Neutralization of Special Elements in Output Used by a Downstream Component) occurs due to insufficient input validation in the Patient Record Management System. The vulnerable endpoint /fecalysis_not.php accepts a comp_id parameter that is directly incorporated into SQL queries without proper sanitization or parameterization.

The attack can be initiated remotely over the network with low attack complexity. An authenticated attacker with minimal privileges can exploit this vulnerability to read, modify, or delete data within the application's database. The vulnerability affects confidentiality, integrity, and availability of the system, though the scope is limited to the vulnerable component itself.

Root Cause

The root cause of this vulnerability is the lack of proper input validation and the use of unsanitized user-supplied input in SQL query construction. The comp_id parameter in /fecalysis_not.php is directly concatenated into SQL statements rather than being handled through prepared statements or parameterized queries. This allows special SQL characters and commands to be interpreted as part of the query structure rather than as data values.

Attack Vector

The vulnerability is exploitable remotely via network access. An attacker sends a crafted HTTP request to the /fecalysis_not.php endpoint with a maliciously constructed comp_id parameter value. This value contains SQL syntax that, when processed by the server, alters the intended query logic. The attacker can leverage standard SQL injection techniques such as UNION-based injection, boolean-based blind injection, or time-based blind injection to extract data or manipulate database contents.

The exploit has been publicly disclosed and may be actively used. Technical details and proof-of-concept information are available through the GitHub SQL CVE Repository and VulDB CTI Report #346652.

Detection Methods for CVE-2026-2706

Indicators of Compromise

  • Unusual SQL error messages in application logs referencing /fecalysis_not.php
  • Anomalous database queries containing SQL metacharacters in the comp_id parameter
  • Unexpected database access patterns or large data extraction from patient-related tables
  • Web server access logs showing requests to /fecalysis_not.php with encoded or suspicious parameter values

Detection Strategies

  • Implement Web Application Firewall (WAF) rules to detect SQL injection patterns in HTTP parameters
  • Configure application logging to capture all requests to /fecalysis_not.php with full parameter values
  • Deploy database activity monitoring to alert on unusual query patterns or data access volumes
  • Use intrusion detection systems (IDS) with signatures for common SQL injection attack strings

Monitoring Recommendations

  • Enable verbose logging for the Patient Record Management System web application
  • Monitor database query logs for syntax errors or unexpected UNION, SELECT, or DELETE statements
  • Set up alerts for multiple failed authentication attempts combined with SQL injection indicators
  • Review access logs regularly for requests containing common SQL injection payloads like single quotes, double dashes, or OR 1=1 patterns

How to Mitigate CVE-2026-2706

Immediate Actions Required

  • Restrict network access to the Patient Record Management System to trusted IP ranges only
  • Implement input validation on the comp_id parameter to accept only expected numeric values
  • Deploy a Web Application Firewall (WAF) with SQL injection protection rules
  • Audit database access logs for signs of prior exploitation
  • Consider taking the application offline if patient data integrity cannot be verified

Patch Information

No official vendor patch has been identified in the available CVE data. Organizations using code-projects Patient Record Management System 1.0 should contact the vendor or monitor the Code Projects Resource Hub for security updates. Additional technical details are available through VulDB #346652.

Workarounds

  • Implement prepared statements with parameterized queries in the vulnerable /fecalysis_not.php file
  • Add server-side input validation to reject non-numeric values for the comp_id parameter
  • Deploy network segmentation to isolate the healthcare application from untrusted networks
  • Enable database account restrictions to limit the privileges of the application's database user
bash
# Example WAF rule configuration for ModSecurity
# Block SQL injection attempts on vulnerable parameter
SecRule ARGS:comp_id "@detectSQLi" \
    "id:1001,\
    phase:2,\
    deny,\
    status:403,\
    msg:'SQL Injection attempt detected in comp_id parameter',\
    log,\
    auditlog"

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

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