CVE-2025-7157: Anisha Online Note Sharing SQLi Vulnerability

CVE-2025-7157 Overview

A critical SQL injection vulnerability has been identified in code-projects Online Note Sharing version 1.0. The vulnerability exists in the /login.php file where improper handling of the username and password parameters allows attackers to inject malicious SQL commands. This flaw enables remote attackers to bypass authentication mechanisms, extract sensitive data, and potentially compromise the underlying database server.

Critical Impact

Remote attackers can exploit this SQL injection vulnerability to bypass authentication, access unauthorized data, and potentially gain complete control over the application's database.

Affected Products

• Anisha Online Note Sharing 1.0

Discovery Timeline

• 2025-07-08 - CVE CVE-2025-7157 published to NVD
• 2025-07-09 - Last updated in NVD database

Technical Details for CVE-2025-7157

Vulnerability Analysis

The vulnerability resides in the login functionality of the Online Note Sharing application. The /login.php endpoint fails to properly sanitize user-supplied input in the username and password parameters before incorporating them into SQL queries. This classic SQL injection vulnerability allows attackers to manipulate the query logic, enabling authentication bypass and unauthorized data access.

The attack can be executed remotely without any prior authentication or user interaction required. Given that this vulnerability affects the primary authentication mechanism, successful exploitation grants attackers access to the application with potentially elevated privileges. The exploit has been publicly disclosed, increasing the risk of widespread exploitation.

Root Cause

The root cause of this vulnerability is classified under CWE-74 (Improper Neutralization of Special Elements in Output Used by a Downstream Component). The application directly concatenates user input into SQL queries without proper parameterization or input validation. This allows specially crafted input containing SQL metacharacters to alter the intended query structure and execute arbitrary SQL commands against the database.

Attack Vector

The attack is network-based and requires no authentication or user interaction. An attacker can submit malicious payloads through the login form, targeting either the username or password field. Common exploitation techniques include:

• Authentication bypass using payloads like ' OR '1'='1 to always evaluate true
• Union-based injection to extract data from other database tables
• Error-based injection to enumerate database structure and contents
• Time-based blind injection for data exfiltration when direct output is not visible

The vulnerability is remotely exploitable and the exploit has been disclosed publicly, making it accessible to attackers with basic SQL injection knowledge. For technical details on the exploit, refer to the GitHub CVE Issue Discussion and VulDB CVE 315096 Analysis.

Detection Methods for CVE-2025-7157

Indicators of Compromise

• Unusual login attempts containing SQL syntax characters such as single quotes, double dashes, or semicolons
• Database errors or exceptions appearing in application logs following authentication attempts
• Unexpected successful logins from unknown IP addresses or at unusual times
• Evidence of data exfiltration or unauthorized database queries in database audit logs

Detection Strategies

• Deploy Web Application Firewall (WAF) rules to detect and block SQL injection patterns in HTTP POST parameters
• Implement database activity monitoring to identify anomalous queries originating from the web application
• Review web server access logs for requests to /login.php containing encoded SQL injection payloads
• Configure intrusion detection systems with signatures for common SQL injection attack patterns

Monitoring Recommendations

• Enable detailed logging for all authentication attempts including the source IP and timestamp
• Monitor database query logs for unusual SELECT statements or UNION-based queries
• Set up alerts for multiple failed login attempts followed by a successful authentication
• Implement real-time monitoring for database error messages that may indicate injection attempts

How to Mitigate CVE-2025-7157

Immediate Actions Required

• Restrict access to the /login.php endpoint to trusted IP ranges if possible
• Implement a Web Application Firewall (WAF) with SQL injection protection rules
• Review application logs for evidence of prior exploitation attempts
• Consider temporarily disabling the application until a patch is applied

Patch Information

As of the last update on 2025-07-09, no official vendor patch has been released for this vulnerability. Organizations using Online Note Sharing 1.0 should monitor the Code Projects Security Resources for security updates. Given the critical nature of this SQL injection vulnerability and the public availability of exploit information, organizations should prioritize implementing workarounds or consider alternative solutions.

Workarounds

• Implement prepared statements with parameterized queries in the /login.php file
• Add server-side input validation to reject input containing SQL metacharacters
• Deploy a reverse proxy or WAF configured to filter SQL injection attempts
• Implement rate limiting on the login endpoint to slow down automated exploitation attempts
• Consider placing the application behind a VPN to restrict access to authorized users only

# Example WAF rule for ModSecurity to block SQL injection
# Add to modsecurity.conf or rules configuration
SecRule ARGS "@detectSQLi" \
    "id:1001,\
    phase:2,\
    block,\
    msg:'SQL Injection Attack Detected on login.php',\
    logdata:'Matched Data: %{MATCHED_VAR} found within %{MATCHED_VAR_NAME}',\
    severity:'CRITICAL'"