Honeypot fingerprinting poses a significant threat in cybersecurity, as attackers who are able to identify honeypot systems can successfully evade them, thereby greatly reducing their overall effectiveness as defensive and intelligence-gathering tools. Over the years, numerous studies have proposed a variety of analytical techniques and countermeasures to minimize honeypot fingerprinting and improve honeypot stealth. This paper presents a comprehensive examination of the methods and strategies that attackers employ to detect and fingerprint honeypot systems, including behavioural, network-based, and system-level indicators. In addition, this paper analyzes common vulnerabilities inherent in both low-interaction and high-interaction honeypots that facilitate successful fingerprinting. Existing anti-detection and obfuscation techniques are evaluated for their effectiveness and limitations. Specifically, this paper offers a structured analysis of honeypot fingerprinting techniques, examines attackers’ probing strategies, evaluates the most vulnerable protocol artifacts, and outlines mitigation strategies to reduce the likelihood of honeypot detection. Finally, this paper discusses how emerging technologies and increasingly complex computing environments, such as cloud infrastructure and virtualization, impact honeypot deployment, and it highlights open challenges and promising future research directions in the field of honeypot anti-fingerprinting.