The vulnerability stems from improper access control mechanisms within the application's dataset management functions. Specifically, the application fails to adequately verify the user's permissions before allowing operations on dataset prompts and their variations. This oversight means that any authenticated user could potentially manipulate or remove data they should not have access to, leading to data integrity and confidentiality issues.

An attacker, after gaining authenticated access to the application, could exploit this vulnerability by crafting malicious DELETE requests targeting specific dataset_prompt or dataset_prompt_variation IDs. By manipulating the request parameters, the attacker could delete or alter dataset entries without proper authorization, potentially leading to loss of critical data or unauthorized data modification.

Any user or data within the lunary-ai/lunary application that relies on the integrity and confidentiality of dataset prompts and their variations is at risk due to this vulnerability. This includes project managers, data scientists, and other stakeholders who depend on accurate and secure dataset management.