Attackers increasingly seek to compromise organizations' systems and data with advanced methods, often utilising legitimate tools. In the main, organisations employ reactive approaches to cyber security, focused on rectifying immediate incidents and preventing repeat attacks, through protections such as Security Information and Event Management (SIEM), firewalls, anti-spam/anti-malware solutions and system patches have been demonstrated to have significant weaknesses in addressing modern attacks. Proactive approaches, have been seen as part of the solution to this problem. However, techniques such as vulnerability and penetration testing (VAPT) are recognised as having limited scope and only working with threats that have already been discovered. Promising methods such as threat hunting are gaining momentum, enabling organisations to identify and rapidly respond to any potential attacks, though they have been criticised for their significant cost. In this paper, we present a novel model for uncovering tactics, techniques, and procedures (TTPs) through offensive security, specifically threat hunting via adversary emulation. The proposed technique is based on a novel approach of inducing adversary emulation (mapping each respective phase) model inside the threat hunting approach. The experimental results show that the proposed approach exploits the threat hunting via adversary emulation and has countervailing effects on hunting advance level threats. Moreover, the threat detection ability of the proposed approach utilizes minimum resources. The proposed approach can be exploited to develop the offensive security-aware environment for organizations to uncover advanced attack mechanisms and test their ability for attack detection.