Privilege abuse within organizations is a major concern because it can lead to security breaches caused by malicious actions or behavior from employees. It is one of the key sources of insider threats in organizational systems. This paper presents an integrated approach to detecting and preventing privilege abuse by employees, focusing on identifying malicious activities. This is achieved by combining artificial intelligence and blockchain technology. RNN is used to analyze malicious behavior, while blockchain ensures a secure, decentralized ledger to prevent abuse. The goal is to combine the RNN model with blockchain technology to detect and prevent privilege abuse. The LSTM model was implemented as an API to identify any malicious activity by employees, and the classification results were stored on the blockchain to ensure security, trust, and data integrity. Experiments using the CERT r4.2 dataset demonstrate that the proposed approach outperforms current state-of-the-art techniques, achieving a classification accuracy of 98.75% with low false positives and false negatives in detecting insider threats.