Glossary Term

Honeypot

A decoy system or service set up to lure attackers and study their tactics without endangering real assets.

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What it is

A honeypot is a deliberately exposed system, network service, or environment that mimics a legitimate target to lure attackers. Its purpose is to detect, analyze, and understand attack patterns in a controlled setting. Security teams deploy honeypots as bait, appearing vulnerable with open ports, outdated software, or fake credentials, to entice cybercriminals into revealing their tools, methods, and motivations.

There are different types of honeypots. Low-interaction honeypots emulate limited functionality, such as SSH or HTTP responses, capturing superficial attack attempts like credential brute-forcing. High-interaction honeypots, on the other hand, simulate full-fledged systems with realistic services, allowing researchers to observe complex intrusion techniques and malware behavior. Some organizations expand this concept into honeynets, entire fake networks designed for long-term threat intelligence collection.

Why it matters

Honeypots serve dual roles: detection and deception. They provide early warning indicators of emerging threats, reveal vulnerabilities in real infrastructure, and allow analysts to study attack lifecycles without compromising operational systems. Insights from honeypots enhance intrusion detection rules, strengthen incident response playbooks, and contribute to community threat intelligence feeds.

Moreover, honeypots waste attacker resources and increase the cost of intrusion attempts. When used strategically within deception technologies, they create uncertainty for adversaries, forcing them to question whether a target is genuine or a trap.

How to reduce risk

  • Deploy honeypots in isolated network segments with no production data or privileges.
  • Use them alongside intrusion detection systems and SIEM tools for correlated monitoring.
  • Regularly update honeypot signatures to reflect realistic system behaviors.
  • Automate alerting and data collection to capture indicators of compromise efficiently.
  • Integrate findings into threat intelligence workflows to improve real-time defenses.