A honeypot is an information system resource whose value lies in unauthorized or illicit use of that resource. They are closely monitored network decoys serving several purposes: they can distract adversaries from more valuable machines on a network, they can provide early warning about new attack and exploitation trends and they allow in-depth examination of adversaries during and after exploitation of a honeypot.• Has no production value; anything going to/from a honeypot is likely a probe, attack or compromise
• Used for monitoring, detecting and analyzing attacks
• Does not solve a specific problem. Instead, they are a highly flexible tool with different applications to security
• A trap set to detect and deflect attempts at unauthorized use of information systems.
• It consist of a computer, data or a network site that appears to be part of a network but which is actually isolated & protected.
• Whatever they capture is supposed to be malicious & unauthorized.
An example of a honeypot is a system used to simulate one or more network services that you designate on your computer's ports. An attacker assumes you're running vulnerable services that can be used to break into the machine. This kind of honeypot can be used to log access attempts to those ports including the attacker's keystrokes. This could give you advanced warning of a more concerted attack
Etymology
The term "honeypot" is often understood to refer to the English children's character Winnie-the-Pooh, a stuffed bear who was lured into various predicaments by his desire for pots of honey.
During the Cold War it was an espionage technique, which inspired spy fiction. The term "honeypot" was used to describe the use of female to gain secret information. In a common scenario, a pretty female Communist agent would trick a male Western official into handing over secret information.
An alternative explanation for the term is a reflection of the sarcastic term for outhouses and other methods of collecting feces and other human waste in places that lack indoor plumbing. Honey is a euphemism for such waste, which is kept in a honeypot until it is picked up by a honey wagon and taken to a disposal area. In this usage, attackers are the equivalent of flies, drawn by the stench of sewage
History of Honeypot
The concept of the honeypot is not new. In fact as early as 1991, a number of publications expounded on concepts that were to be foundations of today’s honeypot development. Two publications in particular stood out:
v 1990/1991 The Cuckoo’s Egg and Evening with Berferd
Clifford Stoll was an astrophysicist turned systems manager at Lawrence Berkeley Lab. Due to a 75 percent accounting error was able to track down a hacker that was using their computers as a launching pad to hack hundreds of military, industrial, and academic computers in search of secrets. His book “The Cuckoo's Egg”, published in 1988, detailed his experiences through this 3 year incident where he observed the hacker and subsequently gathered information that led to the hackers arrest.
The other publication that was of particular note during this period was “An Evening with Berferd” by the well respected Internet Security expert, Bill Cheswick. In the paper, Mr. Cheswick describes how he and his colleagues set up their jail machine, also known as roach motel2 in which they chronicled a hackers movements and the bait and traps they used to lure and detect him.
v 1997 - Deception Toolkit
The Deception Toolkit is one of the original and landmark Honeypots. It is generally a collection of PERL scripts designed for UNIX systems that emulate a variety of known vulnerabilities. The concept put forward by the DTK is “deceptive defense” which now central in Honeypot concepts and implementations
v 1998 - CyberCop Sting
CyberCop Sting is a component of the CyberCop intrusion protection software family which runs on NT. Cybercop Sting has also been referred to as a “decoy server” for it can simulate a network containing several different types of network devices, including Windows NT servers, Unix servers and routers. Each of these decoys had the ability to track, record, and report intrusive activity to network and security administrators. As with the DTK, each of these decoys can run simulated services. However, as with the problem with most simulated or low-interaction Honeypots, you can only only simulate limited functionality with Cybercop sting such as telnet logins or SMTP banners thus limiting its ability to deceive and to study hackers in the long term.
v 1998 - NetFacade (and Snort)
As with Cybercop Sting, it creates a simulated network of hosts, with simulated IP addresses, running seemingly vulnerable services but in a much larger scale. NetFacade can simulate an entire class C network up to 254 systems. It can also simulate 7 different operating systems with a variety of different services.
v 1998 - BackOfficer Friendly
Back Officer Friendly runs in Windows and was free thus giving more people access to Honeypot technology. Though It didn’t give much functionality it was still a very useful piece of software which demonstrated the concepts of the Honeypot to a lot of people that who were not familiar to Honeypot concepts at that time.
v 1999 - Formation of the Honeynet Project 9
A group of people led by Lance Spitzner decided to form the Honeynet Project 9. The honeynet project is a non-profit group dedicated to researching the blackhat community and to share their work to others. Their primary tool for research is the honeynet, an advanced form of Honeypot.
v 2003- Some Honeypot Tools
In 2003, several important Honeypot tools were introduced through these organizations such as Snort-Inline12, Sebek13, and advanced virtual honeynets14.
Ø Snort- Inline augmented Snort to block and disable attacks instead of just detecting them.
Ø Sebek provided a means to capture hacker activities in Honeypots by logging their keystrokes.
Ø Virtual honeynets provided a means to deploy multiple honeynets with just one computer.
Classification of Honetpot
• By level of interaction
Ø High
Ø Low
• By Implementation
Ø Virtual
Ø Physical
• By purpose
Ø Production
Ø Research
1). Level of Interaction
Interaction defines the level of activity a honeypot allows an attacker. There are two categories of interaction “Low Level “ & “High Level Interaction” which helps us understand what type of honeypot you are dealing with, its strengths, and weaknesses.
Low Interaction: Low-interaction honeypots have limited interaction, they normally work by emulating services and operating systems. Attacker activity is limited to the level of emulation by the honeypot.
Ø Simulates some aspects of the system
Ø Easy to deploy, minimal risk
Ø Limited Information
Advantages
Ø Its simplicity.
Ø These honeypots tend to be easier to deploy and maintain, with minimal risk.
Ø Usually they involve installing software, selecting the operating systems and services you want to emulate and monitor, and letting the honeypot go from there. This plug and play approach makes deploying them very easy for most organizations.
Ø The emulated services mitigate risk by containing the attacker's activity, the attacker never has access to an operating system to attack or harm others.
Disadvantages
Ø They log only limited information and are designed to capture known activity.
Ø It’s easier for an attacker to detect a low-interaction honeypot, no matter how good the emulation is, skilled attacker can eventually detect their presence.
Examples of low-interaction honeypots include Specter, Honeyd, and KFSensor.
High Interaction: High-interaction honeypots are different; they are usually complex solutions as they involve real operating systems and applications. Nothing is emulated; we give attackers the real thing. If you want a Linux honeypot running an FTP server, you build a real Linux system running a real FTP server.
Ø Simulates all aspects of the OS: real systems
Ø Can be compromised completely, higher risk
Ø More Information
Ø Honey-net
Advantages
Ø Extensive amounts of information can be captured. By giving attackers real systems to interact with, you can learn the full extent of their behavior, everything from new rootkits to international IRC sessions.
Ø They make no assumptions on how an attacker will behave. Instead, they provide an open environment that captures all activity. This allows high-interaction solutions to learn behavior we would not expect.
Disadvantages
Ø It increases the risk of the honeypot as attackers can use these real operating system to attack non-honeypot systems.
As result, additional technologies have to be implement that prevent the attacker from harming other non-honeypot systems
Difference between high level interaction and low level interaction
| Low-interaction Solution emulates operating systems and services. Ø Easy to install and deploy. Usually requires simply installing and configuring software on a computer. Ø Minimal risk, as the emulated services control what attackers can and cannot do. Ø Captures limited amounts of information, mainly trans-actional data and some limited interaction. | High-interaction No emulation, real operating systems and services are provided. Ø Can capture far more information, including new tools, communications, or attacker keystrokes. Ø Can be complex to install or deploy (commercial versions tend to be much simpler). Ø Increased risk, as attackers are provided real operating systems to interact with |
2). Physical vs Virtual Honeypots
• Real machines
• Own IP Addresses
• Often high-interactive
Ø A “Virtual Honeypot” is simulated by another machine that responds to network traffic sent to the virtual honeypot
• Simulated by other machines that:
– Respond to the traffic sent to the honeypots
– May simulate a lot of (different) virtual honeypots at the same time.
A software program that is designed to appear to be a real functioning network but is actually a decoy built specifically to be probed and attacked by malicious users. In contrast to a honeypot, which is typically a hardware device that lures users into its trap, a virtual honeypot uses software to emulate a network.
Physical honeypots are often high-interaction, so allowing the system to be compromised completely, they are expensive to install and maintain. For large address spaces, it is impractical or impossible to deploy a physical honeypot for each IP address. In that case, we need to deploy virtual honeypots.
3). Production vs Research honeypot
Production honeypots are systems that help mitigate risk in your organization or environment. They provide specific value to securing your systems and networks. Their job is to take care of the bad guys. How do they accomplish this? To answer that question, we are going to break down security into three categories and then review how honeypots can or cannot add value to each one of them. The three categories are as:
Prevention:
In terms of security, prevention means keeping the bad guys out. If you were to secure your house, prevention would be similar to placing deadbolt locks on your doors, locking your windows, and perhaps installing a chainlink fence around your yard. You are doing everything possible to keep out the threat. The security community uses a variety of tools to prevent unauthorized activity. Examples include firewalls that control what traffic can enter or leave a network or authentication, such as strong passwords, digital certificates, or two-factor authentication that requires individuals or resources to properly identify themselves. Based on this authentication, one can determine who is authorized to access resources. Mechanisms such as encryption prevent attackers from reading or accessing critical information, such as passwords or confidential documents.
What role do honeypots play here? How do honeypots keep out the bad guys?
Honeypots adds little value to prevention, since they do not deter the enemy. In fact, if incorrectly implemented, a honeypot may introduce risk, providing an attacker a window into an organization. The deception concept is used to have attackers’ waste time and resources in attacking honeypots, as opposed to attacking production systems. The deterrence concept is that if attackers know there are honeypots in an organization, they may be scared off as they do not want to be detected or they do not want to waste their time or resources attacking the honeypots.
Both concepts are psychological weapons used to confuse a human attacker but most attacks are usually performed by automated tools, such as auto-rooters or worms so deception or deterrence will not be able to prevent these attacks because there is no conscious individual to deter or deceive.
Both concepts fail to prevent the most common of attacks: targets of opportunity. The attacker use automated tools that hack into systems for them. These attackers do not spend time analyzing the systems they target. They merely take a shotgun approach, hitting as many computers as possible and seeing what they get into.
However, the time and resources involved in deploying honeypots for preventing attacks, especially prevention based on deception or deterrence is time better spent on security best practices. As long as you have vulnerable systems, you will be hacked. No honeypot can prevent that.
Detection:
The second tier of security is detection, the act of detecting and alerting unauthorized activity. If you were to secure your house, detection would be the installation of burglar alarms and motion detectors. These alarms go off when someone breaks in. In case the window was left open or the lock on the front door was picked, we want to detect the burglar if they get into our house. Within the world of information security, we have the same challenge. Sooner or later, prevention will fail, and the attacker will get in. There are a variety of reasons why this failure can happen: A firewall rule base may be misconfigured, an employee uses an easy-to-guess password, and a new vulnerability is discovered in an application. There are numerous methods for penetrating an organization. Prevention can only mitigate risk; it will never eliminate it.
Within the security community, Network Intrusion Detection Systems, are designed to monitor networks and detect any malicious activity. However, they do not keep out the bad guys, but they alert us if someone is trying to get in and if they are successful.
How do honeypots help detect unauthorized or suspicious activity? While honeypots add limited value to prevention, they add extensive value to detection. For many organizations, detection is extremely difficult. Three common challenges of detection are :
v False positives are when systems falsely alert suspicious or malicious activity. What a system thought was an attack or exploit attempt was actually valid production traffic.
v False negatives are the exact opposite: They are when an organization fails to detect an attack.
v The third challenge is Data aggregation, centrally collecting all the data used for detection and then corroborating that data into valuable information.
A single false positive is not a problem. The problem occurs when these false alerts happen hundreds or even thousands of times a day. System administrators may receive so many alerts in one day that they cannot respond to all of them and hence start ignoring these false positive alerts as they come in day after day. Network Intrusion Detection Systems are very familar with false positives. The only solution to false positives is to modify the system to not alert about valid, production traffic. This is an extremely time-consuming process, requiring highly skilled individuals who understand network traffic, system logs, and application activity.
A false negative is when a system fails to detect a valid attack. The risk is that a successful attack may occur, but the systems fail to detect and alert to the activity. NIDS not only face the challenge of false positives but also have problems with false negatives.
The third challenge to detection is data aggregation. Modern technology is extremely effective at capturing extensive amounts of data. NIDS, system logs, application logs—all of these resources are very good at capturing and generating gigabytes of data. The challenge becomes how to aggregate all this data so it has value in detecting and confirming an attack.
Due to their simplicity, honeypots effectively address the three challenges of detection: false positives, false negatives, and data aggregation. Most honeypots have no production traffic, so there is little activity to generate false positives.
Honeypots address false negatives because they are not easily defeated by new exploits. In fact, one of their primary benefits is they can detect a new attack by virtue of system activity, not signatures. It works on the concept that anything sent its way is suspect.
The simplicity of honeypots also addresses the third issue: data aggregation. Honeypots address this issue by creating very little data. There is no valid production traffic to be logged, collected, or aggregated. Honeypots generate only several megabytes of data a day, most of which is of high value. This makes it extremely easy to diagnose useful information from honeypots.
Response
Once we detect a successful attack, we need the ability to respond. When securing our house, we want to be sure someone can protect us in case of a break-in. Often house burglar alarms are wired to monitoring stations or the local police department. When an alarm goes off, the proper authorities are alerted and can quickly react, protecting your house. The same logic applies to securing your organization. Honeypots add value to the response aspect of security.
When an attacker breaks into a system, their actions leave evidence, evidence that can be used to determine how the attacker got in, what they did once they gained control of the system, and who were they. It is this evidence that is critical to capture. Without it, organizations cannot effectively respond to the incident.
Honeypots can help address these challenges to reaction capability. Remember, a honeypot has no production activity, so this helps the problem of data pollution. When a honeypot is compromised, the only real activity on the system is the activity of the attacker, helping to maintain its integrity. If we look at our train station analogy, imagine a crime at a train station where there are no people or trains coming or going. Evidence such as fingerprints or hair samples are far more likely to remain intact. The same case is true for honeypots. Honeypots can also easily be taken offline for further analysis. Since honeypots provide no production services, organizations can easily take them down for analysis without impacting business activity.
Research Honeypots are complex to deploy and maintain, capture extensive information and are used primarily by research, military or government organization. They can be used for the following:
Ø To capture automated threats, such as worms or auto-rooters. By quickly capturing these weapons and analyzing their malicious payload, organizations can better react to and neutralize the threat.
Ø As an early warning mechanism, predicting when future attacks will happen. This works by deploying multiple honeypots in different locations and organizations. The data collected from these research honeypots can then be used for statistical modeling, predicting future attacks. Attacks can then be identified and stopped before they happen.
Ø To capture unknown tools or techniques
Ø To better understand attackers' motives and organization. By capturing their activity after they break into a system, such as communications among each other, we can better understand who our threat is and why they operate.
Ø To gain information on advanced blackhats
Advantages of Honeypot
Honeypots are a tremendously simply concept, which gives them some very powerful strengths.
Ø Small data sets of high value: Honeypots collect small amounts of information. Instead of logging a one GB of data a day, they can log only one MB of data a day. Instead of generating 10,000 alerts a day, they can generate only 10 alerts a day. Remember, honeypots only capture bad activity; any interaction with a honeypot is most likely unauthorized or malicious activity. As such, honeypots reduce 'noise' by collectin only small data sets, but information of high value, as it is only the bad guys. This means its much easier (and cheaper) to analyze the data a honeypot collects and derive value from it.
Ø New tools and tactics: Honeypots are designed to capture anything thrown at them, including tools or tactics never seen before.
Ø Minimal resources: Honeypots require minimal resources, they only capture bad activity. This means an old Pentium computer with 128MB of RAM can easily handle an entire class B network sitting off an OC-12 network.
Ø Encryption or IPv6: Unlike most security technologies (such as IDS systems) honeypots work fine in encrypted or IPv6 environments. It does not matter what the bad guys throw at a honeypot, the honeypot will detect and capture it.
Ø Information: Honeypots can collect in-depth information that few, if any other technologies can match.
Ø Simplicty: Finally, honeypots are conceptually very simple. There are no fancy algorithms to develop, state tables to maintain, or signatures to update. The simpler a technology, the less likely there will be mistakes or misconfigurations.
Disadvantages of Honeypot
Like any technology, honeypots also have their weaknesses. It is because of this they do not replace any current technology, but work with existing technologies.
Ø Limited view: Honeypots can only track and capture activity that directly interacts with them. Honeypots will not capture attacks against other systems, unless the attacker or threat interacts with the honeypots also.
Ø Risk: All security technologies have risk. Firewalls have risk of being penetrated, encryption has the risk of being broken, IDS sensors have the risk of failing to detect attacks. Honeypots are no different, they have risk also. Specifically, honeypots have the risk of being taken over by the bad guy and being used to harm other systems. These risk various for different honeypots. Depending on the type of honeypot, it can have no more risk then an IDS sensor, while some honeypots have a great deal of risk.
by Niels Provos, A virtual honey pot application, which allows us to create thousands of IP addresses with virtual machines and corresponding network services. It is open source software released under GNU General Public License.
• It is able to simulate big network on a single host.
• It provides simple functionality.
• It gives an attacker to façade to attack
Honeyd
Honeyd is a low-interaction honeypot. Developed
How Honeyd Works
Honeyd works on the concept of monitoring unused IP space. Anytime it sees a connection attempt to an unused IP, it intercepts the connection and then interacts with the attacker, pretending to be the victim. By default, Honeyd detects and logs any connection to any UDP or TCP port. In addition, you can configure emulated services to monitor specific ports, such as an emulated FTP server monitoring TCP port 21. When an attacker connects to the emulated service, not only does the honeypot detect and log the activity, but it captures all of the attacker's interaction with the emulated service. In the case of the emulated FTP server, we can potentially capture the attacker's login and password, the commands they issue, and perhaps even learn what they are looking for or their identity. It all depends on the level of emulation by the honeypot. Most emulated
services work the same way.
Know Your Enemy:
Honeynets
Honeynets
Honeynet
Tradationally information security has been primarily defensive. Firewalls, Intrusion detection system, encryption; all of these mechanism are used defensively to protect one’s resource. The strategy is to defend one’s organization as best as possible, detect any failures in the defense, and then react to those failures. The problem with this approach is it purely defensive, the enemy has the initiative. Honeypots attempts to change that. The primary purpose of honeypot is to gather information on threats. This information has defferent value for different organization.
Eg.
· Academic research institution may use honeypot to gather data for research, such as worm activity.
· Security organization may use honeypot to capture and analyze malware for anti-virus.
· Government organization use them to learn more about who is targetting them and why???
Honeynets are a prime example of high-interaction honeypot. Honeynets are not a product; they are not a software solution that you install on a computer. Instead, Honeyents are an architecture, an entire network of computers designed to attacked. The idea is to have an architecture that creates a highly controlled network, one where all activity is controlled and captured. Within this network we place our intended victims, real computers running real applications. The bad guys find, attack, and break into these systems on their own initiative. When they do, they do not realize they are within a Honeynet. All of their activity, from encrypted sessions to emails and files uploads, are captured without them knowing it. This is done by inserting kernel modules on the victim systems that capture all of the attacker's actions. At the same time, the Honeynet controls the attacker's activity. Honeynets do this using a Honeywall gateway. This gateway allows inbound traffic to the victim systems, but controls the outbound traffic using intrusion prevention technologies. This gives the attacker the flexibility to interact with the victim systems, but prevents the attacker from harming other non-Honeynet computers.
Honeynet Architecture
Honeynets are nothing more than an architecture. To succesfully deploy a honeynet; the honeynet architecture should be correctly deployed. The key to the honeynet architecture is what we call a “honeywall”. This is a gateway device that seperates your honeypots from the rest of the world. Any traffic going to or from the honeypots must go through the honeywall. This gateway is traditionally a layer 2 bridging device, meaning the device should be invisible to anyone interacting with the honeypots. Below we see a diagram of this architecture. The Honeywall has 3 interfaces. The first 2
There are several key requirements that a honeywall must implement; Data Control, Data Capture, Data Analysis, Data Collection. Data Control defines how activity is contained with the honeynet without an attacker knowing it. Its purpose is to minimize risk. Data Capture is capturing all of the attacker's activity without the attacker knowing it. Data Analysis is the ability to analyze this data. Data Collection is the ability to collect data from multiple honeynets to a single source. Of all these requirements, Data Control is the more important. Data Control always takes priority as its role is to mitigate risk. We describe each in more detail below.
v Data Control is the containment of activity, it is what mitigates risk. By risk, we mean there is always the potential of an attacker or malicious code using a honeynet to attack or harm non-honeynet systems, or abusing the honeynet in some un-expected way. We want to make every effort possible to ensure that once an attacker is within our honeynet or a system is compromised, they cannot accidentally or purposefully harm other non-honeynet systems. The challenge is implementing data control while minimizing the attacker's or malcious's code chance of detecting it. This is more challenging then it seems. First, we have to allow the attackers some degree of freedom to act. The more activity we allow the attackers to perform, the more we can potentially learn about them. However, the more freedom you allow an attacker, the more risk there is they will circumvent Data Control and harm other non-honeynet systems. The balance of how much freedom to give the attacker vs. how much you restrict their activity is a decision every organization has to make themselves.
v Data Capture is the monitoring and logging of all of the threat's activities within the honeynet. It is this captured data that is then analyzed to learn the tools, tactics, and motives of attackers. The challenge is to capture as much data as possible without the threat detecting the process. As with Data Control, one of the primary lessons learned for Data Capture has been the use of layers. It is critical to use multiple mechanisms for capturing activity. Not only does the combination of layers help piece together all of the attacker's actions, but it prevents having a single point of failure. The more layers of information that are captured, at both the network and host level, the more that can be learned. To minimize the ability of attackers to detect our capture mechanisms, there are two ways: First, make as few modifications to the honeypots as possible. The more modifications you make, the greater the chance of detection. Second it is best that captured data not be stored locally on the honeypots themselves. Not only could this data be detected by attackers, but it could also be modified or deleted. As such, captured data must be logged and stored on a seperate, secured system.
v Data Analysis is the third requirement. Remember, the entire purpose of a honeynet is information. A honeynet is worthless if you have no ability to convert the data it collect to information, you must have some ability to analyze the data. Different organizations have different needs, and as such will have different data analysis requirements.
v Data Collection applies only to organizations that have multiple honeynets in distributed environments. Most organizations will have only one single honeynet, what we call a standalone deployment. As such they do not need to worry about Data Collection. However, organizations that have multiple honeynets logically or physically distributed around the world have to collect all of the captured data and store it in a central location. This way the captured data can be combined, exponentially increasing its value. The Data Collection requirement provides the secure means of centrally collecting all of the captured information from distributed honeynets.
Implementing all of these requirements is extremely difficult, complex, and time consuming. In the past it took a great deal of time and effort to deploy such an architecture. However, today the Honeynet Project has developed a rapid and simple way for an organization to deploy such functionality, its call the Honeywall CDROM. The purpose of this bootable CDROM is to make it simple to rapidly build and deploy a honeywall, the critical component to honeynet architecture. You simply install the Honeywall CDROM into a computer with multiple NICs, and it automates the build process of a honeywall, implementing all of the requirements we just discussed above.
Advantages of Honeynet
• High Data Value
Ø Small Data
• Low Resource Cost
Ø Weak or Retired system
• Simple Concept, Flexible Implementation
• Return on Investment
Ø Proof of Effectiveness
• Catch new attacks
Disadvantages of honeynet
• In reference to risk, there are four general areas we will cover;
v Harm: when a honey net is used to attack or or harm other, non-honey net systems.
Eg. An attacker may break into a honeynet, and then launch an outbound attack never seen before, successfully harming or compromising its intended victim.
v Detection: Once the true identity of a honey net has been identified, its value is dramatically reduced. Attacker can ignore or bypass the honeynet, eliminating its capability for capturing information.
v Disabling: Attackers may want to not only detect a honey net's identity, but disable its Data Control or Data Capture capabilities, potentially without the honeynet administrator knowing that functionality has been disabled (feed the honeypot with bogus activity, making administrator think that data capture is still functioning and recording activity when it is not.)
v Violation: Attackers may attempt criminal activity from your compromised honey net without actually attacking anyone outside your honey net
Eg. Attackers using a honeypot to upload then distribute illegal material. Remember, this individual broke into your system on their own initiative. If detected, this illegal activity would be attributed to you by way of it being on your system. You may then have to prove that it was in fact not you who was responsible for this activity.
Difference between Honeypot & Honeynet
• Honeypots use known vulnerabilities to lure attack.
– Configure a single system with special software or system emulations
– Want to find out actively who is attacking the system
• Honeynets are networks open to attack
– Often use default installations of system software
– Behind a firewall
– Rather they mess up the Honeynet than your production system.
References:
v http://en.wikipedia.org/wiki/honeypot
v http://www.honeynet.org
v www.honeypots.net/
v www.honeynet.org/papers/index.html
v www.awprofessional.com/articles/article.asp
v www.spitzner.net/honeypots.html
v www.honeynet.org.papers/cdrom/roo/
v www.honeynet.ie.about.html
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