Dec 5, 2010

Honey Pots

n computer terminology, 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 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 application of this is a honeypot that thwartsspam by masquerading as a type of system abused by spammers. These honeypots 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.


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 an 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.

Database honeypot

Databases often get attacked by intruders using SQL Injection. Because such activities are not recognized by basic firewalls, companies often use database firewalls. Some of the available SQL database firewalls provide/support honeypot architectures to let the intruder run against a trap database while the web application still runs as usual.


Just as honeypots are weapons against spammers, honeypot detection systems are spammer-employed counter-weapons. As detection systems would likely use unique characteristics of specific honeypots to identify them, a great deal 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.[7] Cohen believes that this might deter adversaries.


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.

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."