Tag, Category, and Taxonomy Manager – AI Autotagger with OpenAI vulnerabilities

The Tag, Category, and Taxonomy Manager – AI Autotagger with OpenAI plugin for WordPress is vulnerable to time-based blind SQL Injection via the 'existing_terms_orderby' parameter in the AI preview AJAX endpoint in all versions up to, and including, 3.40.1. This is due to insufficient escaping on user-supplied parameters and lack of SQL query parameterization. This makes it possible for authenticated attackers, with Contributor-level access and above who have AI metabox permissions, to append additional SQL queries into already existing queries that can be used to extract sensitive information from the database, cause performance degradation, or enable data inference through time-based techniques.

The Tag, Category, and Taxonomy Manager – AI Autotagger with OpenAI plugin for WordPress is vulnerable to time-based SQL Injection via the getTermsForAjax function in all versions up to, and including, 3.40.1. This is due to insufficient escaping on user-supplied parameters and lack of sufficient preparation on the existing SQL query. This makes it possible for authenticated attackers with contributor-level access and above to append additional SQL queries into existing queries to extract sensitive information from the database, granted they have metabox access for the taxonomy (enabled by default for contributors).

The Tag, Category, and Taxonomy Manager – AI Autotagger with OpenAI plugin for WordPress in versions up to and including 3.40.1 is vulnerable to authorization bypass. The "taxopress_merge_terms_batch" function does not properly verify that a user is authorized to perform an action, allowing authenticated attackers with subscriber-level access and above to merge or delete arbitrary taxonomy terms.

The Tag, Category, and Taxonomy Manager – AI Autotagger with OpenAI plugin for WordPress is vulnerable to SQL Injection via the 'post_types' parameter in all versions up to and including 3.40.0 due to insufficient escaping and lack of preparation on the SQL query. This allows authenticated attackers with Editor-level access and above to append additional SQL queries to extract sensitive information from the database.