CVE-2025-69563 Overview
CVE-2025-69563 is a SQL Injection vulnerability affecting code-projects Mobile Shop Management System version 1.0. The vulnerability exists in the /ExLogin.php file and can be exploited through the Password parameter. This flaw allows unauthenticated attackers to inject malicious SQL queries, potentially leading to unauthorized access to the underlying database, data exfiltration, data manipulation, and complete system compromise.
Critical Impact
Unauthenticated attackers can exploit this SQL Injection vulnerability to bypass authentication, extract sensitive data, modify database records, or potentially gain complete control over the affected system.
Affected Products
- code-projects Mobile Shop Management System 1.0
- /ExLogin.php endpoint (Password parameter)
Discovery Timeline
- 2026-01-27 - CVE-2025-69563 published to NVD
- 2026-01-29 - Last updated in NVD database
Technical Details for CVE-2025-69563
Vulnerability Analysis
This SQL Injection vulnerability (CWE-89) occurs due to improper neutralization of special elements used in SQL commands within the login functionality. The /ExLogin.php file fails to properly sanitize or parameterize user-supplied input from the Password field before incorporating it into SQL queries. This allows attackers to manipulate the query structure by injecting malicious SQL syntax through the authentication form.
The vulnerability is particularly severe because it affects the authentication mechanism, meaning successful exploitation could allow attackers to bypass login controls entirely, access administrative functions, or extract sensitive customer and business data from the database.
Root Cause
The root cause of this vulnerability is insufficient input validation and the use of unsanitized user input directly within SQL query construction. The application appears to concatenate the Password parameter directly into SQL statements without implementing prepared statements, parameterized queries, or adequate input filtering. This classic SQL Injection pattern represents a fundamental secure coding failure that has been well-documented for decades.
Attack Vector
The attack vector is network-based and requires no authentication or user interaction, making it highly accessible to remote attackers. An adversary can craft malicious HTTP POST requests to the /ExLogin.php endpoint, injecting SQL payloads through the Password parameter. Common attack techniques include:
- Authentication bypass using payloads like ' OR '1'='1 or ' 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
- Stacked queries (if supported) to execute arbitrary SQL commands
Technical details regarding exploitation can be found in the referenced GitHub Gist and Gitee Issue Report.
Detection Methods for CVE-2025-69563
Indicators of Compromise
- Unusual SQL error messages in web server logs originating from /ExLogin.php
- HTTP POST requests to /ExLogin.php containing SQL keywords such as UNION, SELECT, OR, AND, --, or encoded equivalents in the Password parameter
- Unexpected database queries or access patterns in database audit logs
- Failed login attempts followed by successful authentication without valid credentials
- Anomalous data extraction patterns or bulk database queries
Detection Strategies
- Deploy Web Application Firewall (WAF) rules to detect and block SQL Injection patterns targeting the /ExLogin.php endpoint
- Implement intrusion detection signatures for common SQL Injection payloads in HTTP POST request bodies
- Enable database query logging and monitor for suspicious query patterns including UNION SELECT, comment sequences, or excessive OR conditions
- Configure application-level logging to capture authentication attempts with malformed or suspicious input
Monitoring Recommendations
- Monitor web server access logs for repeated requests to /ExLogin.php with varying payloads
- Set up alerts for SQL syntax errors or database exceptions triggered by the login endpoint
- Track successful authentications that occur without corresponding valid credential entries in authentication audit trails
- Implement rate limiting on authentication endpoints to slow automated exploitation attempts
How to Mitigate CVE-2025-69563
Immediate Actions Required
- Take the Mobile Shop Management System offline if it is internet-facing and cannot be immediately patched
- Implement Web Application Firewall rules to filter SQL Injection payloads targeting /ExLogin.php
- Review database access logs for evidence of prior exploitation
- Restrict network access to the application to trusted IP addresses only
Patch Information
No vendor patch information is currently available for this vulnerability. The code-projects Mobile Shop Management System appears to be an open-source or educational project. Organizations using this software should review the GitHub Gist and Gitee Issue Report for additional technical details and potential fixes.
Workarounds
- Modify /ExLogin.php to use parameterized queries or prepared statements instead of direct string concatenation for SQL queries
- Implement server-side input validation to reject Password values containing SQL metacharacters
- Deploy a reverse proxy or WAF configured to sanitize input to the vulnerable endpoint
- Consider replacing the vulnerable application with a more actively maintained alternative that follows secure coding practices
- If the application must remain in use, isolate it on a segmented network with restricted access
# Example WAF rule concept for ModSecurity
SecRule ARGS:Password "@detectSQLi" \
"id:100001,\
phase:2,\
block,\
msg:'SQL Injection attempt detected in Password parameter',\
logdata:'Matched Data: %{MATCHED_VAR}',\
severity:'CRITICAL'"
Disclaimer: This content was generated using AI. While we strive for accuracy, please verify critical information with official sources.
