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CVE Vulnerability Database
Vulnerability Database/CVE-2025-7753

CVE-2025-7753: Anisha Appointment Booking SQL Injection

CVE-2025-7753 is a critical SQL injection vulnerability in Anisha Online Appointment Booking System 1.0 affecting the /admin/adddoctor.php file. This article covers the technical details, affected versions, and mitigation.

Published: March 24, 2026

CVE-2025-7753 Overview

A SQL injection vulnerability has been identified in code-projects Online Appointment Booking System version 1.0. The vulnerability exists in the /admin/adddoctor.php file, where the Username parameter is not properly sanitized before being used in SQL queries. This allows remote attackers to inject malicious SQL statements and potentially compromise the underlying database.

Critical Impact

Remote attackers can exploit this SQL injection vulnerability to bypass authentication, extract sensitive data, modify database contents, or potentially achieve further system compromise through database-level attacks.

Affected Products

  • Anisha Online Appointment Booking System version 1.0

Discovery Timeline

  • July 17, 2025 - CVE-2025-7753 published to NVD
  • July 18, 2025 - Last updated in NVD database

Technical Details for CVE-2025-7753

Vulnerability Analysis

This SQL injection vulnerability (CWE-89) affects the administrator functionality within the Online Appointment Booking System. The vulnerable endpoint /admin/adddoctor.php processes user-supplied input through the Username parameter without adequate sanitization or parameterized queries. When an attacker supplies a crafted username value containing SQL metacharacters and commands, these are interpreted by the database engine as part of the query structure rather than as data.

The vulnerability is classified under both CWE-89 (SQL Injection) and CWE-74 (Improper Neutralization of Special Elements in Output Used by a Downstream Component), indicating a fundamental failure in input validation and output encoding practices.

Root Cause

The root cause of this vulnerability is improper input validation and the use of unsanitized user input directly in SQL queries. The application fails to implement parameterized queries or prepared statements, allowing user-controlled data to be concatenated directly into SQL statements. This classic SQL injection pattern occurs when developers construct queries through string concatenation rather than using secure database APIs that separate code from data.

Attack Vector

The attack can be initiated remotely over the network without requiring authentication or user interaction. An attacker can craft malicious HTTP requests targeting the /admin/adddoctor.php endpoint with SQL injection payloads in the Username parameter. Successful exploitation could allow:

  • Bypassing authentication mechanisms
  • Extracting sensitive information from the database including user credentials and appointment records
  • Modifying or deleting database records
  • Potentially escalating to command execution if database permissions allow

The exploit has been publicly disclosed, increasing the risk of widespread exploitation. Technical details are available through the GitHub CVE Issue #22 and VulDB #316743.

Detection Methods for CVE-2025-7753

Indicators of Compromise

  • Unusual or malformed requests to /admin/adddoctor.php containing SQL syntax in the Username parameter
  • Database error messages in application logs indicating SQL syntax errors
  • Unexpected database queries or query execution patterns
  • Evidence of data exfiltration or unauthorized database modifications
  • Multiple failed authentication attempts with SQL injection patterns

Detection Strategies

  • Deploy Web Application Firewall (WAF) rules to detect and block SQL injection patterns in HTTP requests
  • Implement application-layer logging to capture all requests to administrative endpoints
  • Configure database audit logging to monitor for suspicious query patterns or unauthorized data access
  • Use intrusion detection systems (IDS) with signatures for common SQL injection attack patterns
  • Monitor for anomalous database activity including bulk data extraction or schema enumeration

Monitoring Recommendations

  • Enable verbose logging on the web application server for requests to /admin/ paths
  • Configure alerting for database errors related to SQL syntax or malformed queries
  • Implement real-time monitoring for high-volume requests to the vulnerable endpoint
  • Review web server access logs for patterns indicative of automated SQL injection tools

How to Mitigate CVE-2025-7753

Immediate Actions Required

  • Restrict access to /admin/adddoctor.php through network-level controls or authentication requirements
  • Implement Web Application Firewall rules to filter SQL injection attempts targeting the Username parameter
  • Consider taking the affected functionality offline until a patch is available
  • Audit the database for evidence of compromise and unauthorized access
  • Review and strengthen authentication mechanisms for administrative interfaces

Patch Information

No official vendor patch has been identified at this time. Organizations using the Online Appointment Booking System should monitor the code-projects resource page for security updates. Given the public disclosure of this vulnerability and the lack of vendor remediation, organizations should implement compensating controls immediately.

Workarounds

  • Implement input validation to sanitize the Username parameter, rejecting characters such as single quotes, double quotes, semicolons, and SQL keywords
  • Deploy a Web Application Firewall (WAF) configured to detect and block SQL injection patterns
  • Restrict network access to the administrative interface to trusted IP addresses only
  • Consider migrating to a more actively maintained appointment booking solution
  • If source code access is available, implement parameterized queries or prepared statements
bash
# Example: Apache mod_rewrite rule to block access to vulnerable endpoint
# Add to .htaccess or Apache configuration
<Location "/admin/adddoctor.php">
    Order deny,allow
    Deny from all
    Allow from 192.168.1.0/24
</Location>

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

  • Vulnerability Details
  • TypeSQLI

  • Vendor/TechAnisha Online Appointment Booking System

  • SeverityMEDIUM

  • CVSS Score6.9

  • EPSS Probability0.04%

  • Known ExploitedNo
  • CVSS Vector
  • CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:L/VI:L/VA:L/SC:N/SI:N/SA:N/E:P/CR:X/IR:X/AR:X/MAV:X/MAC:X/MAT:X/MPR:X/MUI:X/MVC:X/MVI:X/MVA:X/MSC:X/MSI:X/MSA:X/S:X/AU:X/R:X/V:X/RE:X/U:X
  • Impact Assessment
  • ConfidentialityLow
  • IntegrityNone
  • AvailabilityLow
  • CWE References
  • CWE-74

  • CWE-89
  • Technical References
  • Code Projects Resource

  • GitHub CVE Issue #22

  • VulDB CTI ID #316743

  • VulDB #316743

  • VulDB Submission #615494
  • Related CVEs
  • CVE-2025-7752: Anisha Appointment Booking SQL Injection

  • CVE-2025-7751: Anisha Appointment Booking SQL Injection

  • CVE-2025-7750: Anisha Appointment Booking SQL Injection

  • CVE-2025-7749: Anisha Appointment Booking SQL Injection Flaw
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