CVE-2025-13585: Covid Tracking System SQLi Vulnerability

CVE-2025-13585 Overview

A SQL injection vulnerability has been identified in itsourcecode COVID Tracking System version 1.0. This vulnerability affects the /login.php file, where improper handling of the code argument allows attackers to inject malicious SQL statements. The vulnerability can be exploited remotely without authentication, potentially allowing unauthorized access to the underlying database and sensitive healthcare tracking data.

Critical Impact

Remote attackers can exploit this SQL injection vulnerability to bypass authentication, extract sensitive COVID tracking data, modify database records, or potentially gain unauthorized access to the system. Given the healthcare context, this could expose protected health information.

Affected Products

• itsourcecode COVID Tracking System 1.0
• Angeljudesuarez Covid Tracking System (cpe:2.3:a:angeljudesuarez:covid_tracking_system:1.0)

Discovery Timeline

• 2025-11-24 - CVE-2025-13585 published to NVD
• 2025-12-07 - Last updated in NVD database

Technical Details for CVE-2025-13585

Vulnerability Analysis

This SQL injection vulnerability (CWE-89) exists in the login functionality of the COVID Tracking System. The application fails to properly sanitize user-supplied input in the code parameter before incorporating it into SQL queries. This is a classic example of injection vulnerability (CWE-74) where untrusted data is sent to an interpreter as part of a command or query.

The vulnerability is remotely exploitable without requiring authentication, user interaction, or special privileges. While the immediate impact is assessed as limited to confidentiality, integrity, and availability of the vulnerable system, the nature of healthcare tracking systems means that successful exploitation could lead to exposure of sensitive personal health information. The exploit has been made public, increasing the risk of widespread exploitation attempts against unpatched installations.

Root Cause

The root cause of this vulnerability is the lack of proper input validation and parameterized queries in the /login.php file. The code argument is directly concatenated or interpolated into SQL queries without sanitization, allowing attackers to manipulate the query structure. This represents a failure to implement secure coding practices for database interactions, specifically the absence of prepared statements or parameterized queries that would separate SQL logic from user-supplied data.

Attack Vector

The attack vector is network-based, meaning the vulnerability can be exploited remotely over the internet without requiring local system access. An attacker can craft malicious HTTP requests to the /login.php endpoint, manipulating the code parameter to inject SQL commands.

The attacker does not need any prior authentication or special privileges to exploit this vulnerability. By injecting carefully crafted SQL payloads into the code parameter, an attacker could potentially bypass authentication checks, extract database contents, modify or delete records, or in some configurations, execute operating system commands on the underlying server.

Technical details and proof-of-concept information are available in the GitHub Issue on CVE and VulDB entry #333349.

Detection Methods for CVE-2025-13585

Indicators of Compromise

• Unusual or malformed requests to /login.php containing SQL syntax characters such as single quotes, semicolons, or SQL keywords in the code parameter
• Database query errors appearing in application logs or being returned in HTTP responses
• Unexpected database queries or data exfiltration patterns in database audit logs
• Failed login attempts followed by successful authentication with anomalous session characteristics

Detection Strategies

• Deploy Web Application Firewall (WAF) rules to detect and block SQL injection patterns in requests to /login.php
• Implement application-level logging to capture all authentication attempts and parameter values for forensic analysis
• Enable database query logging to identify suspicious queries containing injected SQL statements
• Use intrusion detection systems (IDS) with signatures for common SQL injection attack patterns

Monitoring Recommendations

• Monitor web server access logs for requests to /login.php with suspicious characters or encoded payloads in the code parameter
• Set up alerts for database errors related to SQL syntax in the COVID Tracking System database
• Track authentication success/failure ratios and alert on anomalies that may indicate authentication bypass
• Review database audit logs for unexpected data access patterns or privilege escalation attempts

How to Mitigate CVE-2025-13585

Immediate Actions Required

• Restrict network access to the COVID Tracking System to trusted IP addresses only until a patch is available
• Implement Web Application Firewall (WAF) rules to block SQL injection attempts targeting the code parameter
• Consider temporarily disabling or securing the /login.php functionality if not critical to operations
• Review database access logs for signs of prior exploitation and potential data breach

Patch Information

As of the last update on 2025-12-07, no official vendor patch has been released for this vulnerability. Organizations using the affected COVID Tracking System should contact itsourcecode for patch availability or consider the workarounds listed below. Monitor the IT Source Code Resource for potential updates. Given the public disclosure of this exploit, immediate mitigation steps are essential.

Workarounds

• Implement input validation and sanitization for the code parameter at the application level
• Modify the /login.php file to use parameterized queries or prepared statements for all database interactions
• Deploy a reverse proxy or WAF with SQL injection protection in front of the application
• Isolate the COVID Tracking System in a network segment with restricted access and enhanced monitoring

# Example WAF rule to block SQL injection attempts (ModSecurity)
SecRule ARGS:code "@detectSQLi" \
    "id:100001,\
    phase:2,\
    deny,\
    status:403,\
    log,\
    msg:'SQL Injection attempt detected in code parameter',\
    tag:'application-multi',\
    tag:'language-multi',\
    tag:'platform-multi',\
    tag:'attack-sqli'"