In compunology, a honeypot is a trap set to detect, deflect, or in some manner counteract attempts at unauthorized use of information systems. Generally it consists of a computer, data, or a network site that appears to be part of a network, but is actually isolated, (un)protected, and monitored, and which seems to contain information or a resource of value to attackers.

A honeypot is valuable as a surveillance and early-warning tool. While it is often a computer, a honeypot can take other forms, such as files or data records, or even unused IP address space. A honeypot that masquerades as an open proxy to monitor and record those using the system is a sugarcane. Honeypots should have no production value, and hence should not see any legitimate traffic or activity. Whatever they capture is therefore malicious or unauthorized. One practical implication of this is honeypots that thwart spam by masquerading as the type of systems abused by spammers. They categorize trapped material 100% accurately: it is all illicit.

Honeypots can carry risks to a network, and must be handled with care. If they are not properly walled off, an attacker can use them to break into a system.

Victim hosts are an active network counter-intrusion tool. These computers run special software, designed to appear to an intruder as being important and worth looking into. In reality, these programs are dummies, and their patterns are constructed specifically to foster interest in attackers. The software installed on, and run by, victim hosts is dual purpose. First, these dummy programs keep a network intruder occupied looking for valuable information where none exists, effectively convincing him or her to isolate themselves in what is truly an unimportant part of the network. This decoy strategy is designed to keep an intruder from getting bored and heading into truly security-critical systems. The second part of the victim host strategy is intelligence gathering. Once an intruder has broken into the victim host, the machine or a network administrator can examine the intrusion methods used by the intruder. This intelligence can be used to build specific countermeasures to intrusion techniques, making truly important systems on the network less vulnerable to intrusion.
[edit] Types

Honeypots can be classified based on their deployment and based on their level of involvement. Based on the deployment, honeypots may be classified as

1. Production Honeypots
2. Research Honeypots

Production honeypots are easy to use, capture only limited information, and are used primarily by companies or corporations; Production honeypots are placed inside the production network with other production servers by organization to improve their overall state of security. Normally, production honeypots are low-interaction honeypots, which are easier to deploy. They give less information about the attacks or attackers than research honeypots do. The purpose of a production honeypot is to help mitigate risk in an organization. The honeypot adds value to the security measures of an organization.

Research honeypots are run by a volunteer, non-profit research organization or an educational institution to gather information about the motives and tactics of the Blackhat community targeting different networks. These honeypots do not add direct value to a specific organization. Instead they are used to research the threats organizations face, and to learn how to better protect against those threats. This information is then used to protect against those threats. Research honeypots are complex to deploy and maintain, capture extensive information, and are used primarily by research, military, or government organizations.

Spammers abuse vulnerable resources such as open mail relays and open proxies. Some system administrators have created honeypot programs that masquerade as these abusable resources to discover spammer activity. There are several capabilities such honeypots provide to these administrators and the existence of such fake abusable systems makes abuse more difficult or risky. Honeypots can be a powerful countermeasure to abuse from those who rely on very high volume abuse (e.g., spammers).

These honeypots can reveal the apparent IP address of the abuse and provide bulk spam capture (which enables operators to determine spammers' URLs and response mechanisms). For open relay honeypots, it is possible to determine the e-mail addresses ("dropboxes") spammers use as targets for their test messages, which are the tool they use to detect open relays. It is then simple to deceive the spammer: transmit any illicit relay e-mail received addressed to that dropbox e-mail address. That tells the spammer the honeypot is a genuine abusable open relay, and they often respond by sending large quantities of relay spam to that honeypot, which stops it. The apparent source may be another abused system?spammers and other abusers may use a chain of abused systems to make detection of the original starting point of the abuse traffic difficult.

This in itself is indicative of the power of honeypots as anti-spam tools. In the early days of anti-spam honeypots, spammers, with little concern for hiding their location, felt safe testing for vulnerabilities and sending spam directly from their own systems. Honeypots made the abuse less easy and safe.

Spam still flows through open relays, but the volume is much smaller than in 2001 to 2002. While most spam originates in the U.S.[1], spammers hop through open relays across political boundaries to mask their origin. Honeypot operators may use intercepted relay tests to recognize and thwart attempts to relay spam through their honeypots. "Thwart" may mean "accept the relay spam but decline to deliver it." Honeypot operators may discover other details concerning the spam and the spammer by examining the captured spam messages. (However, open relay spam has declined significantly.[citation needed])

Open relay honeypots include Jackpot,[2] written in Java, smtpot.py,[3] written in Python, and spamhole,[4] written in C. The Bubblegum Proxypot[5] is an open proxy honeypot (or proxypot).
[edit] E-mail trap
Main article: Spamtrap

An e-mail address that is not used for any other purpose than to receive spam can also be considered a spam honeypot. Compared with the term spamtrap, the term "honeypot" might better be reserved for systems and techniques used to detect or counter attacks and probes. Spam arrives at its destination "legitimately"?exactly as non-spam e-mail would arrive.

An amalgam of these techniques is Project Honey Pot. The distributed, open-source Project uses honeypot pages installed on websites around the world. These honeypot pages hand out uniquely tagged spamtrap e-mail addresses. E-mail address harvesting and Spammers can then be tracked as they gather and subsequently send to these spamtrap e-mail addresses.
[edit] Detection

Just as honeypots are a weapon against spammers, honeypot detection systems are a spammer-employed counter-weapon. As detection systems would likely use unique characteristics of specific honeypots to identify them, a plethora of honeypots in use makes the set of unique characteristics larger and more daunting to those seeking to detect and thereby identify them. This is an unusual circumstance in software: a situation in which "versionitis" (a large number of versions of the same software, all differing slightly from each other) can be beneficial. There's also an advantage in having some easy-to-detect honeypots deployed. Fred Cohen, the inventor of the Deception Toolkit, even argues that every system running his honeypot should have a deception port that adversaries can use to detect the honeypot.[6] Cohen believes that this might deter adversaries.
[edit] Honeynets

Two or more honeypots on a network form a honeynet. Typically, a honeynet is used for monitoring a larger and/or more diverse network in which one honeypot may not be sufficient. Honeynets and honeypots are usually implemented as parts of larger network intrusion-detection systems. A honeyfarm is a centralized collection of honeypots and analysis tools.[7][8]

The concept of the honeynet first began in 1999 when Lance Spitzner, founder of the Honeynet Project, published the paper "To Build a Honeypot":

"A honeynet is a network of high interaction honeypots that simulates a production network and configured such that all activity is monitored, recorded and in a degree, discretely regulated."[9]