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CVE Vulnerability Database

CVE-2024-9925: Taismartfactory Qplant SF SQLi Vulnerability

CVE-2024-9925 is a SQL injection vulnerability in TAI Smart Factory's QPLANT SF that allows attackers to extract database information via the RequestPasswordChange endpoint. This article covers technical details, impact, and fixes.

Published:

CVE-2024-9925 Overview

CVE-2024-9925 is a SQL injection vulnerability discovered in TAI Smart Factory's QPLANT SF version 1.0, an industrial manufacturing software platform. This vulnerability allows remote attackers to retrieve all database information by sending specially crafted SQL queries to the email parameter on the RequestPasswordChange endpoint. The flaw represents a significant security risk for organizations using this smart factory management solution, as it could lead to complete database compromise without requiring any authentication.

Critical Impact

Remote attackers can exploit this SQL injection vulnerability to extract complete database contents, including sensitive manufacturing data, user credentials, and proprietary business information without authentication.

Affected Products

  • TAI Smart Factory QPLANT SF version 1.0

Discovery Timeline

  • 2024-10-15 - CVE-2024-9925 published to NVD
  • 2024-10-17 - Last updated in NVD database

Technical Details for CVE-2024-9925

Vulnerability Analysis

This SQL injection vulnerability (CWE-89) exists in the password reset functionality of QPLANT SF. The RequestPasswordChange endpoint fails to properly sanitize user input in the email parameter before incorporating it into SQL queries. This allows attackers to inject malicious SQL statements that are executed by the database server with the privileges of the application's database user.

The vulnerability is particularly dangerous because it exists in an unauthenticated endpoint—the password reset functionality is intentionally accessible to users who cannot log in. This means attackers do not need any credentials or prior access to exploit this vulnerability.

Root Cause

The root cause of this vulnerability is improper input validation and the use of dynamic SQL queries that directly concatenate user-supplied input. The email parameter value is inserted into SQL statements without parameterized queries or prepared statements, allowing attackers to escape the intended query structure and inject arbitrary SQL commands.

Attack Vector

The attack vector is network-based, requiring no privileges or user interaction. An attacker can send crafted HTTP requests to the RequestPasswordChange endpoint with malicious SQL syntax in the email parameter. Common exploitation techniques include UNION-based injection to extract data from other tables, error-based injection to enumerate database structure, and blind SQL injection using time delays or conditional responses to infer data.

The vulnerability can be exploited remotely over the network by sending malicious payloads through the password change request mechanism. Once exploited, an attacker can potentially retrieve all database information, including user credentials, manufacturing data, and any other sensitive information stored in the backend database system.

Detection Methods for CVE-2024-9925

Indicators of Compromise

  • Unusual HTTP requests to the RequestPasswordChange endpoint containing SQL syntax characters such as single quotes, UNION statements, or comment sequences
  • Database error messages appearing in HTTP responses that reveal internal query structure
  • Abnormal database query patterns or execution times indicating time-based blind SQL injection attempts
  • Unexpected data access patterns or bulk data extraction from the QPLANT SF database

Detection Strategies

  • Implement Web Application Firewall (WAF) rules to detect SQL injection patterns in requests to the RequestPasswordChange endpoint
  • Monitor application logs for requests containing suspicious characters or SQL keywords in the email parameter
  • Deploy database activity monitoring to detect unusual query patterns or unauthorized data access
  • Configure intrusion detection systems with signatures for common SQL injection attack patterns

Monitoring Recommendations

  • Enable detailed logging for the RequestPasswordChange endpoint and review logs for anomalous request patterns
  • Set up alerts for database queries containing UNION, SELECT, or other SQL keywords in unexpected contexts
  • Monitor for increased error rates or unusual response times from the QPLANT SF application
  • Track and baseline normal database access patterns to identify anomalous extraction activities

How to Mitigate CVE-2024-9925

Immediate Actions Required

  • Restrict network access to the QPLANT SF application to trusted IP addresses only until a patch is available
  • Implement a Web Application Firewall (WAF) with SQL injection protection rules in front of the application
  • Consider disabling the RequestPasswordChange functionality temporarily if not critical to operations
  • Review database access logs for signs of prior exploitation and assess potential data exposure

Patch Information

No vendor patch information is currently available in the CVE data. Organizations should monitor the INCIBE Security Notice on SQL Injection for updates from TAI Smart Factory regarding security patches or fixes for this vulnerability.

Workarounds

  • Deploy a reverse proxy or WAF to filter malicious SQL injection patterns before requests reach the application
  • Implement network segmentation to isolate the QPLANT SF server from untrusted networks
  • Use database account restrictions to limit the application's database user permissions to minimum required privileges
  • Enable database query logging and alerting to detect exploitation attempts in real-time
bash
# Example WAF rule to block common SQL injection patterns
# ModSecurity rule for Apache/Nginx
SecRule ARGS:email "@rx (?i)(\b(select|union|insert|update|delete|drop|alter|create|truncate)\b|--|;|')" \
    "id:100001,phase:2,deny,status:403,msg:'SQL Injection Attempt Detected in email parameter'"

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

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