This paper investigates the use of Machine Learning (ML) techniques to efficiently extract threat intelligence from hacker forums. By comparing Convolutional Neural Networks (CNNs) with traditional ML methods like Support Vector Machines (SVMs) on text data from a real hacker forum, the study found that traditional methods can achieve performance levels comparable to CNNs, offering a viable and resource-efficient alternative for threat analysis.