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Vulnerability Database/CVE-2026-39109

CVE-2026-39109: Apartment Visitors Management SQLi Flaw

CVE-2026-39109 is a SQL injection vulnerability in Apartment Visitors Management System V1.1 that enables unauthenticated attackers to manipulate SQL queries and access sensitive data. This article covers technical details, impact, and mitigation.

Updated:

CVE-2026-39109 Overview

CVE-2026-39109 is a SQL injection vulnerability in PHP Gurukul's Apartment Visitors Management System version 1.1. The flaw resides in the username parameter of the login page (index.php). An unauthenticated remote attacker can inject crafted SQL syntax into the authentication query and manipulate backend database operations. Successful exploitation lets an attacker extract sensitive database records, bypass authentication, or alter stored data. The weakness is classified under CWE-89: Improper Neutralization of Special Elements used in an SQL Command.

Critical Impact

Unauthenticated network attackers can manipulate login SQL queries to read or modify database contents without credentials or user interaction.

Affected Products

  • PHP Gurukul Apartment Visitors Management System V1.1
  • index.php login component processing the username parameter
  • Deployments distributed via the PHP Gurukul Project Overview

Discovery Timeline

  • 2026-04-20 - CVE-2026-39109 published to NVD
  • 2026-04-20 - Last updated in NVD database

Technical Details for CVE-2026-39109

Vulnerability Analysis

The vulnerability exists in the authentication flow of the Apartment Visitors Management System. The application concatenates the username HTTP POST parameter directly into a SQL query executed against the MySQL backend. Because the parameter is neither parameterized nor sanitized, attackers can break out of the string literal and append arbitrary SQL clauses. An attacker submits a malicious payload to the login endpoint and observes authentication behavior or extracted output to enumerate the database. The vulnerability is reachable pre-authentication over the network, which expands the attack surface to any internet-exposed deployment. Given the EPSS score of 0.203% (percentile 42.156), active exploitation is not yet widespread, but the trivial attack chain makes opportunistic scanning likely.

Root Cause

The root cause is the absence of prepared statements or input validation in the login handler within index.php. User-controlled input is interpolated directly into the SQL SELECT statement that validates credentials, violating secure coding practices for database access.

Attack Vector

An unauthenticated attacker sends a crafted HTTP POST request to the login page with SQL metacharacters embedded in the username field. Classic payloads such as boolean-based or UNION-based injections allow the attacker to bypass authentication or exfiltrate data from tables containing visitor records, administrator credentials, and resident information. No user interaction is required, and exploitation can be automated using common tooling. Refer to the GitHub CVE Repository for additional technical context on the affected parameter.

Detection Methods for CVE-2026-39109

Indicators of Compromise

  • HTTP POST requests to /index.php containing SQL metacharacters such as ', --, UNION, OR 1=1, or SLEEP( in the username parameter
  • Web server access logs showing repeated login failures from a single source followed by successful authentication
  • Unexpected MySQL error messages or slow query log entries originating from the login handler
  • Outbound database connections or data egress patterns inconsistent with normal application use

Detection Strategies

  • Deploy web application firewall (WAF) rules that flag SQL injection signatures targeting the username parameter on index.php
  • Enable verbose application and database logging to capture full POST bodies and raw queries during authentication attempts
  • Correlate login endpoint anomalies with downstream database read volume spikes to identify data exfiltration

Monitoring Recommendations

  • Monitor authentication endpoints for high-entropy or syntactically anomalous username values
  • Alert on MySQL query errors referencing the login table during user-driven traffic
  • Track unauthenticated access patterns against index.php from new or low-reputation IP addresses

How to Mitigate CVE-2026-39109

Immediate Actions Required

  • Restrict network access to the Apartment Visitors Management System interface using firewall rules or VPN-only access until a patch is applied
  • Place the application behind a WAF configured with SQL injection rule sets and virtual patching for the username parameter
  • Audit database accounts used by the application and rotate credentials if compromise is suspected
  • Review web and database logs for prior exploitation attempts dating back to deployment

Patch Information

No vendor advisory or official patch has been published at the time of this writing. Administrators should monitor the PHP Gurukul Project Overview and the GitHub CVE Repository for fix releases. Until a patch is available, code maintainers should refactor the login handler to use parameterized queries (PDO or mysqli prepared statements) and apply strict input validation on all authentication parameters.

Workarounds

  • Replace dynamic SQL concatenation in index.php with prepared statements that bind the username and password parameters
  • Apply server-side input validation rejecting non-alphanumeric characters in the username field
  • Configure the database account used by the application with least-privilege permissions, limiting SELECT access to required tables only
  • Disable detailed MySQL error output in production to prevent error-based injection from leaking schema details
bash
# Example WAF rule (ModSecurity) blocking SQLi patterns in the username parameter
SecRule ARGS:username "@detectSQLi" \
    "id:1039109,phase:2,deny,status:403,\
    msg:'CVE-2026-39109 SQLi attempt on Apartment Visitors Management System login',\
    logdata:'Matched username=%{MATCHED_VAR}'"

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

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