CVE-2025-10833: Bookstore Management System SQLi Flaw

CVE-2025-10833 Overview

A SQL Injection vulnerability has been identified in 1000projects Bookstore Management System version 1.0. The vulnerability exists in the /login.php file, where improper handling of the unm (username) parameter allows attackers to inject malicious SQL queries. This vulnerability can be exploited remotely without authentication, potentially compromising the integrity and confidentiality of the application's database.

Critical Impact
Remote unauthenticated attackers can exploit this SQL injection vulnerability to bypass authentication, extract sensitive data, modify database contents, or potentially execute arbitrary commands on the underlying database server.

Affected Products

1000projects Bookstore Management System version 1.0

Discovery Timeline

September 23, 2025 - CVE-2025-10833 published to NVD
September 25, 2025 - Last updated in NVD database

Technical Details for CVE-2025-10833

Vulnerability Analysis

This vulnerability is a classic SQL Injection flaw (CWE-74: Improper Neutralization of Special Elements in Output Used by a Downstream Component) occurring in the login functionality of the Bookstore Management System. The application fails to properly sanitize user-supplied input in the unm parameter before incorporating it into SQL queries executed against the backend database.

When a user submits login credentials through /login.php, the username value is directly concatenated into a SQL query without proper input validation or parameterized query implementation. This allows attackers to craft malicious input that alters the intended SQL logic.

The vulnerability is exploitable remotely over the network with no authentication required, making it accessible to any attacker who can reach the application. Successful exploitation can result in unauthorized data access, data manipulation, and potential authentication bypass.

Root Cause

The root cause of this vulnerability is the direct use of unsanitized user input in SQL query construction. The application lacks proper input validation and does not utilize prepared statements or parameterized queries when processing the unm argument in the login functionality. This is a fundamental secure coding violation that allows user-controlled data to be interpreted as SQL code rather than data.

Attack Vector

The attack is conducted remotely over the network. An attacker can manipulate the unm parameter in login requests sent to /login.php to inject SQL syntax. Common exploitation techniques include:

Using single quotes and SQL keywords to manipulate query logic
Employing UNION-based injection to extract data from other tables
Utilizing time-based or boolean-based blind injection techniques to infer database contents
Bypassing authentication by injecting conditions that always evaluate to true

The vulnerability is publicly documented, and technical details are available through the GitHub CVE Issue and VulDB #325190.

Detection Methods for CVE-2025-10833

Indicators of Compromise

Unusual login attempts with SQL metacharacters (single quotes, double dashes, semicolons) in username fields
Database error messages appearing in web server logs or responses
Unexpected SQL queries or commands in database query logs
Authentication bypass events where users gain access without valid credentials

Detection Strategies

Implement Web Application Firewall (WAF) rules to detect SQL injection patterns in login requests
Monitor application logs for requests containing SQL keywords (UNION, SELECT, OR, AND) in the unm parameter
Configure database auditing to detect unusual query patterns or privilege escalation attempts
Deploy intrusion detection systems with signatures for common SQL injection attack patterns

Monitoring Recommendations

Enable detailed logging for /login.php and monitor for anomalous request patterns
Set up alerts for multiple failed login attempts followed by successful authentication
Monitor database connections for queries originating from the web application that deviate from expected patterns
Review web server access logs for requests with unusually long unm parameter values

How to Mitigate CVE-2025-10833

Immediate Actions Required

Restrict network access to the Bookstore Management System to trusted IP addresses only
Implement a Web Application Firewall with SQL injection protection rules
Consider taking the application offline until a proper fix is implemented
Audit database logs for signs of prior exploitation

Patch Information

No official vendor patch has been released for this vulnerability at the time of publication. Organizations using 1000projects Bookstore Management System version 1.0 should contact the vendor for remediation guidance or implement the workarounds described below.

For additional technical details, refer to the VulDB CTI #325190 and VulDB Submission #656419.

Workarounds

Deploy a Web Application Firewall (WAF) configured to block SQL injection attempts targeting the login endpoint
Implement input validation at the network perimeter to filter requests containing SQL metacharacters
Restrict database user permissions to limit the impact of potential exploitation
If source code access is available, modify /login.php to use prepared statements with parameterized queries

bash

# Example WAF rule configuration (ModSecurity)
SecRule ARGS:unm "@detectSQLi" \
    "id:100001,\
    phase:2,\
    deny,\
    status:403,\
    msg:'SQL Injection attempt detected in login parameter',\
    log,\
    auditlog"