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CVE Vulnerability Database

CVE-2025-7459: Anisha Mobile Shop SQLi Vulnerability

CVE-2025-7459 is a critical SQL injection vulnerability in Anisha Mobile Shop 1.0 affecting the /EditMobile.php file. Attackers can exploit the ID parameter remotely. This article covers technical details, affected versions, impact, and mitigation.

Published:

CVE-2025-7459 Overview

A critical SQL injection vulnerability has been identified in code-projects Mobile Shop version 1.0. This vulnerability exists in the /EditMobile.php file where the manipulation of the ID parameter allows remote attackers to inject malicious SQL commands. The attack can be initiated remotely without authentication, and the exploit has been publicly disclosed.

Critical Impact

Remote attackers can exploit this SQL injection vulnerability to manipulate database queries, potentially extracting sensitive data, modifying records, or compromising the entire database backend of the Mobile Shop application.

Affected Products

  • Anisha Mobile Shop 1.0

Discovery Timeline

  • 2025-07-11 - CVE-2025-7459 published to NVD
  • 2025-07-16 - Last updated in NVD database

Technical Details for CVE-2025-7459

Vulnerability Analysis

This SQL injection vulnerability affects the /EditMobile.php endpoint in the Anisha Mobile Shop application. The vulnerability stems from improper handling of the ID parameter, which is passed directly into database queries without adequate input validation or sanitization. This allows attackers to inject arbitrary SQL statements that are executed by the database server.

The vulnerability is classified as network-accessible, meaning attackers can exploit it remotely over the internet without requiring local access to the target system. No authentication or user interaction is required to exploit this flaw, making it particularly dangerous for publicly accessible deployments of the Mobile Shop application.

Root Cause

The root cause of this vulnerability is the failure to properly validate and sanitize user-supplied input in the ID parameter before incorporating it into SQL queries. The application appears to use dynamic SQL construction without parameterized queries or prepared statements, allowing attacker-controlled data to be interpreted as SQL commands rather than data values.

This is classified under CWE-74 (Improper Neutralization of Special Elements in Output Used by a Downstream Component), which encompasses injection vulnerabilities where special characters or sequences can alter the intended behavior of downstream processing components.

Attack Vector

The attack is initiated remotely via network access to the vulnerable /EditMobile.php endpoint. An attacker crafts a malicious HTTP request containing SQL injection payloads in the ID parameter. Since the application fails to sanitize this input, the injected SQL code is executed directly against the backend database.

The vulnerability allows attackers to perform various malicious actions including extracting sensitive information from the database, modifying or deleting existing records, bypassing authentication mechanisms, and potentially executing operating system commands if the database server is misconfigured.

For technical details on the exploitation mechanism, see the GitHub Issue Discussion which contains the public disclosure information.

Detection Methods for CVE-2025-7459

Indicators of Compromise

  • Unusual or malformed requests to /EditMobile.php containing SQL syntax in the ID parameter
  • Database error messages in web server logs indicating SQL syntax errors or unexpected query behavior
  • Unexpected database queries or data extraction attempts in database audit logs
  • Increased traffic to the /EditMobile.php endpoint from unknown sources

Detection Strategies

  • Implement Web Application Firewall (WAF) rules to detect and block SQL injection patterns in HTTP requests
  • Monitor web server access logs for requests containing SQL keywords or special characters in URL parameters
  • Enable database query logging and alert on queries containing UNION, SELECT, INSERT, UPDATE, DELETE, or DROP statements from web application contexts
  • Deploy intrusion detection systems (IDS) with signatures for common SQL injection attack patterns

Monitoring Recommendations

  • Configure real-time alerting for suspicious patterns in the ID parameter of requests to /EditMobile.php
  • Implement database activity monitoring to detect unauthorized data access or modification attempts
  • Review web server error logs regularly for SQL-related error messages that may indicate exploitation attempts

How to Mitigate CVE-2025-7459

Immediate Actions Required

  • Remove or restrict access to the /EditMobile.php file until a patch is available
  • Implement Web Application Firewall (WAF) rules to filter SQL injection attempts targeting the ID parameter
  • If the application is not critical, consider taking it offline until proper remediation is completed
  • Conduct a database audit to identify any potential data compromise

Patch Information

No official vendor patch has been released at the time of this publication. Organizations using Anisha Mobile Shop 1.0 should monitor the Code Projects Resource for updates and security advisories. Additional technical information is available via VulDB #316108.

Workarounds

  • Implement input validation at the application level to ensure the ID parameter only accepts numeric values
  • Use prepared statements or parameterized queries if modifying the application source code
  • Deploy a Web Application Firewall (WAF) configured to block SQL injection attack patterns
  • Restrict network access to the application to trusted IP addresses only
  • Apply principle of least privilege to database accounts used by the application to minimize potential damage from exploitation
bash
# Example WAF rule for ModSecurity to block SQL injection in ID parameter
SecRule ARGS:ID "@detectSQLi" \
    "id:1001,\
    phase:2,\
    deny,\
    status:403,\
    msg:'SQL Injection Detected in ID Parameter',\
    log,\
    auditlog"

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

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