Advanced Persistent Threat (APT) are elusive and target well-defined, specialized targets. Detecting APT attacks remains challenging due to the lack of attention given to human behavioral factors contributing to APTs, This Analytical study describes a spectrum of approaches and techniques for detecting, defending and Mitigating against APT attacks. The analysis is primarily based on detection methodology accuracy, defending techniques and mitigating strategies. Recent specialized research papers were studied and categorized based on their characteristics, nature of algorithm, and framework. Emphasis is given to Machine Learning (ML) and Deep Learning (DL) algorithms as they acquired efficient results and an effective approach. This paper concluded that ML technique is the most used and efficient detection mechanism to detect APT malware.