ABSTRACT: The swift progression of technology has resulted in a proportional expansion of the at- tack surface, presenting notable obstacles in the field of threat management and mitigation. Zero-day attacks are widely known as one of the most powerful forms of attacks to ad- dress. Zero-day attacks refer to cyber attacks that take advantage of software or hardware vulnerabilities that are not yet recognized by the security vendor. Conventional security measures, including firewalls and antivirus software, may prove inadequate in preventing attacks in instances where the vendor has not yet issued any patches or fixes for the identi- fied vulnerabilities. Consequently, there is a pressing need for more sophisticated detection techniques. The utilization of deception techniques entails the creation of fake systems or data with the aim of attract attackers to expose their presence. Conversely, threat hunt- ing intelligence involves the proactive exploration of potential threats. The present study proposes a methodology that integrates the aforementioned techniques to help the identify zero-day attacks. The efficacy of this methodology is assessed via experiments employing real attack scenarios. The findings indicate that the suggested methodology has the poten- tial to considerably enhance the detection efficacy of zero-day attacks, thereby presenting a viable solution to augment cybersecurity in the wake of swiftly changing security threats.