In computer terminology, a
is a computer security mechanism set to detect, deflect, or, in some manner, annul attempts at unauthorized use of data systems. Generally, a honeypot consists of data (for example, in a network site) that appears to exist a legitimate part of the site which contains data or resource of value to attackers. It is actually isolated, monitored, and capable of blocking or analyzing the attackers. This is similar to police sting operations, colloquially known as “baiting” a suspect.
Honeypots can be classified based on their deployment (employ/action) and based on their level of involvement. Based on deployment, honeypots may exist classified as:
- product honeypots
- enquiry honeypots
are easy to utilise, capture only limited information, and are used primarily by corporations. Product honeypots are placed inside the production network with other production servers by an organization to ameliorate their overall country of security. Commonly, production honeypots are depression-interaction honeypots, which are easier to deploy. They give less information about the attacks or attackers than enquiry honeypots.[two]
are run to gather information about the motives and tactics of the black hat community targeting different networks. These honeypots do non add direct value to a specific organization; instead, they are used to research the threats that organizations face and to learn how to improve protect against those threats.
Enquiry honeypots are complex to deploy and maintain, capture extensive information, and are used primarily by research, armed services, or regime organizations.
Based on design criteria, honeypots can be classified as:
- pure honeypots
- loftier-interaction honeypots
- low-interaction honeypots
are full-fledged production systems. The activities of the attacker are monitored by using a issues tap that has been installed on the honeypot’due south link to the network. No other software needs to exist installed. Even though a pure honeypot is useful, stealthiness of the defense mechanisms tin be ensured past a more controlled mechanism.
imitate the activities of the product systems that host a diverseness of services and, therefore, an aggressor may be immune a lot of services to waste their time. By employing virtual machines, multiple honeypots can be hosted on a unmarried physical machine. Therefore, even if the honeypot is compromised, it can be restored more rapidly. In general, high-interaction honeypots provide more security by being difficult to detect, only they are expensive to maintain. If virtual machines are not bachelor, one physical computer must be maintained for each honeypot, which can be exorbitantly expensive. Example: Honeynet.
simulate only the services frequently requested past attackers.
Since they consume relatively few resources, multiple virtual machines can easily exist hosted on ane physical system, the virtual systems accept a curt response time, and less code is required, reducing the complexity of the virtual arrangement’s security. Example: Honeyd.
is a type of honeypot that masquerades every bit an open proxy.[six]
It can often have form equally a server designed to look like a misconfigured HTTP proxy.
Probably the most famous open up proxy was the default configuration of sendmail (before version 8.9.0 in 1998) which would forward electronic mail to and from any destination.
Deception engineering science
Recently, a new market segment called deception technology has emerged using bones honeypot technology with the addition of advanced automation for calibration. Deception engineering science addresses the automated deployment of honeypot resources over a large commercial enterprise or regime establishment.
Malware honeypots are used to detect malware by exploiting the known replication and assault vectors of malware. Replication vectors such as USB wink drives can easily be verified for testify of modifications, either through transmission means or utilizing special-purpose honeypots that emulate drives.
Spammers abuse vulnerable resources such as open up post relays and open proxies. These are servers which accept e-post from anyone on the Internet—including spammers—and send it to its destination. 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 corruption (e.g., spammers).
These honeypots can reveal the abuser’southward IP address and provide bulk spam capture (which enables operators to determine spammers’ URLs and response mechanisms). Every bit described past Thou. Edwards at ITPRo Today:
Typically, spammers examination a mail server for open relaying by only sending themselves an email message. If the spammer receives the email bulletin, the post server obviously allows open relaying. Honeypot operators, however, can use the relay exam to thwart spammers. The honeypot catches the relay exam email message, returns the exam e-mail message, and later blocks all other e-mail messages from that spammer. Spammers go along to use the antispam honeypot for spamming, but the spam is never delivered. Meanwhile, the honeypot operator can notify spammers’ ISPs and take their Net accounts canceled. If honeypot operators detect spammers who use open-proxy servers, they can also notify the proxy server operator to lock downward the server to preclude farther misuse.
The apparent source may be another abused system. Spammers and other abusers may utilise a chain of such abused systems to brand detection of the original starting betoken of the abuse traffic hard.
This in itself is indicative of the ability of honeypots as anti-spam tools. In the early days of anti-spam honeypots, spammers, with little concern for hiding their location, felt prophylactic testing for vulnerabilities and sending spam directly from their ain systems. Honeypots made the abuse riskier and more difficult.
Spam still flows through open relays, only the book is much smaller than in 2001-02. While most spam originates in the U.S.,[eleven]
spammers hop through open up relays across political boundaries to mask their origin. Honeypot operators may employ intercepted relay tests to recognize and thwart attempts to relay spam through their honeypots. “Thwart” may mean “accept the relay spam merely decline to deliver it.” Honeypot operators may find other details apropos the spam and the spammer past examining the captured spam messages.
Open relay honeypots include Jackpot, written in Java by Jack Cleaver;
smtpot.py, written in Python by Karl A. Krueger;
and spamhole, written in C.
is an open source honeypot (or “proxypot”).
An e-mail address that is not used for any other purpose than to receive spam tin can too be considered a spam honeypot. Compared with the term “spamtrap”, the term “honeypot” might be more than suitable for systems and techniques that are used to detect or counterattack probes. With a spamtrap, spam arrives at its destination “legitimately”—exactly as not-spam email would arrive.
An constructing of these techniques is Project Honey Pot, a distributed, open source projection that uses honeypot pages installed on websites around the world. These honeypot pages disseminate uniquely tagged spamtrap electronic mail addresses and spammers can so be tracked—the respective spam mail is afterwards sent to these spamtrap e-postal service addresses.[fifteen]
Databases oftentimes become attacked by intruders using SQL injection. As such activities are not recognized past bones firewalls, companies often apply database firewalls for protection. Some of the bachelor SQL database firewalls provide/support honeypot architectures so that the intruder runs against a trap database while the web application remains functional.
Just as honeypots are weapons against spammers, honeypot detection systems are spammer-employed counter-weapons. As detection systems would likely apply unique characteristics of specific honeypots to place them, such as the property-value pairs of default honeypot configuration,
many honeypots in-use utilise a set of unique characteristics larger and more daunting to those seeking to detect and thereby place 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 benign. There’due south also an advantage in having some piece of cake-to-detect honeypots deployed. Fred Cohen, the inventor of the Charade Toolkit, argues that every system running his honeypot should have a charade port which adversaries can use to observe the honeypot.
Cohen believes that this might deter adversaries.
The goal of honeypots is to attract and engage attackers for a sufficiently long period to obtain high-level Indicators of Compromise (IoC) such as set on tools and Tactics, Techniques, and Procedures (TTPs). Thus, a honeypot needs to emulate essential services in the production network and grant the aggressor the freedom to perform adversarial activities to increase its attractiveness to the attacker. Although the honeypot is a controlled environment and can exist monitored by using tools such equally honeywall,
attackers may still be able to apply some honeypots every bit pivot nodes to penetrate production systems.
The 2d risk of honeypots is that they may attract legitimate users due to a lack of communication in large-scale enterprise networks. For case, the security team who applies and monitors the honeypot may not disclose the honeypot location to all users in time due to the lack of communication or the prevention of insider threats.
“A ‘honey net’ is a network of high interaction honeypots that simulates a production network and configured such that all activeness is monitored, recorded and in a degree, discreetly regulated.”
2 or more honeypots on a network class a
dearest net. Typically, a honey net is used for monitoring a larger and/or more diverse network in which one honeypot may not exist sufficient. Dearest nets and honeypots are usually implemented as parts of larger network intrusion detection systems. A
is a centralized collection of honeypots and analysis tools.
The concept of the honey net first began in 1999 when Lance Spitzner, founder of the Honeynet Project, published the paper “To Build a Honeypot”.
The primeval honeypot techniques are described in Clifford Stoll’s 1989 volume
The Cuckoo’south Egg.
One of the primeval documented cases of the cybersecurity use of a honeypot began in Jan 1991. On January seven, 1991 while he worked at AT&T Bell Laboratories Cheswick observed a criminal hacker, known as a cracker, attempting to obtain a re-create of a password file. Cheswick wrote that he and colleagues constructed a “chroot “Jail” (or “roach motel”)” which allowed them to observe their attacker over a menstruation of several months.
In 2017, Dutch police used honeypot techniques to track downwardly users of the darknet market place Hansa.
The metaphor of a bear being attracted to and stealing honey is common in many traditions, including Germanic, Celtic, and Slavic. A common Slavic give-and-take for the comport is
“honey eater”. The tradition of bears stealing love has been passed down through stories and sociology, peculiarly the well known Winnie the Pooh.
- Canary trap
- Client honeypot
- Defense strategy (computing)
- Network telescope
- Performance Trust
References and notes
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Mokube, Iyatiti; Adams, Michele (March 2007). “Honeypots: concepts, approaches, and challenges”.
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Honeypots tracking hackers. Addison-Wesley. pp. 68–lxx. ISBN0-321-10895-seven.
Katakoglu, Onur (2017-04-03). “Attacks Landscape in the Nighttime Side of the Spider web”
Litchfield, Samuel; Formby, David; Rogers, Jonathan; Meliopoulos, Sakis; Beyah, Raheem (2016). “Rethinking the Honeypot for Cyber-Concrete Systems”.
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Talukder, Asoke K.; Chaitanya, Manish (17 December 2008).
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“Exposing the Underground: Adventues of an Open up Proxy Server”. 21 March 2011.
“Capturing web attacks with open proxy honeypots”. 3 July 2007.
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Edwards, M. “Antispam Honeypots Requite Spammers Headaches”. Windows Information technology Pro. Archived from the original on 1 July 2017. Retrieved
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“Secure Your Database Using Honeypot Architecture”. dbcoretech.com. August xiii, 2010. Archived from the original on March viii, 2012.
Cabral, Warren; Valli, Craig; Sikos, Leslie; Wakeling, Samuel (2019). “Review and Analysis of Cowrie Artefacts and Their Potential to be Used Deceptively”.
Proceedings of the 2019 International Conference on Computational Scientific discipline and Computational Intelligence. IEEE. pp. 166–171. doi:x.1109/CSCI49370.2019.00035. ISBN978-ane-7281-5584-5.
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Spitzner, Lance (2002).
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Qassrawi, Mahmoud T.; Hongli Zhang (May 2010). “Customer honeypots: Approaches and challenges”.
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“An Evening with BerferdIn Which a Cracker is Lured, Endured, and Studied”
“The word for “acquit”“.
Shepard, E. H., Milne, A. A. (1994). The Consummate Tales of Winnie-the-Pooh. United Kingdom: Dutton Children’s Books.
Lance Spitzner (2002).
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Sean Bodmer; Max Kilger; Gregory Carpenter; Jade Jones (2012).
Reverse Charade: Organized Cyber Threat Counter-Exploitation. McGraw-Hill Education. ISBN978-0-07-177249-5.
- The Ultimate Fake Access Point – AP less clear-text WPA2 passphrase hacking
- Distributed Open Proxy Honeypots Project: WASC
- SANS Institute: What is a Honey Pot?
- SANS Institute: Fundamental Honeypotting
- Projection Honeypot
- A curated list of honeypots, tools and components focused on open source projects