CVE-2024-1981 in WPvivid Backup and Migration Plugin
Summary
by MITRE • 02/29/2024
The Migration, Backup, Staging – WPvivid plugin for WordPress is vulnerable to SQL Injection via the 'table_prefix' parameter in version 0.9.68 due to insufficient escaping on the user supplied parameter and lack of sufficient preparation on the existing SQL query. This makes it possible for unauthenticated attackers to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database.
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Analysis
by VulDB Data Team • 01/17/2025
The vulnerability identified as CVE-2024-1981 affects the WPvivid plugin for WordPress, specifically version 0.9.68, where a SQL injection flaw exists within the migration, backup, and staging functionality. This represents a critical security weakness that stems from inadequate input validation and sanitization practices within the plugin's codebase. The vulnerability manifests through the 'table_prefix' parameter which is processed without proper escaping mechanisms, allowing malicious actors to manipulate database queries through crafted input. The flaw falls under the category of CWE-89 SQL Injection, which is classified as a high-risk vulnerability in the Common Weakness Enumeration catalog and is frequently targeted in automated attack campaigns due to its potential for data exfiltration and system compromise.
The technical exploitation of this vulnerability occurs when an attacker submits a malicious value through the 'table_prefix' parameter, which is then incorporated into SQL queries without proper parameterization or input sanitization. This lack of proper SQL query preparation creates an environment where attackers can append additional SQL commands to the existing queries, effectively bypassing normal access controls and authentication mechanisms. The vulnerability is particularly dangerous because it does not require authentication, making it accessible to any attacker who can interact with the plugin's functionality. The absence of sufficient input validation and escaping allows for the injection of malicious SQL constructs that can manipulate the database structure and extract sensitive information including user credentials, personal data, and system configuration details.
The operational impact of this vulnerability extends beyond simple data theft, as it can enable attackers to escalate privileges within the WordPress environment and potentially gain full control over the affected website. Attackers can leverage this vulnerability to extract user accounts, modify database content, and potentially establish persistent access through backdoor creation. The implications are particularly severe for WordPress installations that rely heavily on the WPvivid plugin for backup and migration operations, as these functions often require elevated privileges and access to sensitive database structures. According to ATT&CK framework, this vulnerability maps to T1078 Valid Accounts and T1046 Network Service Scanning, as attackers can use the SQL injection to discover valid database accounts and potentially map network services to further exploit the environment.
Mitigation strategies for CVE-2024-1981 should prioritize immediate plugin updates to versions that address the SQL injection vulnerability, as developers typically release patches to resolve such issues. System administrators should implement network-level protections such as web application firewalls to monitor and block suspicious SQL injection attempts targeting the affected plugin. Input validation should be strengthened at multiple layers including application-level sanitization, parameterized queries, and proper escaping of user-supplied data. Database access controls should be reviewed and restricted to minimize the potential damage from successful exploitation attempts. Additionally, monitoring systems should be implemented to detect unusual database access patterns and query executions that may indicate exploitation attempts, as the vulnerability creates specific query patterns that can be identified through proper log analysis and anomaly detection mechanisms.