History of Honeypots
The concept of honeypots in cybersecurity was first documented by Clifford Stoll in his 1989 book “The Cuckoo’s Egg.” In it, Stoll recounts his use of a honeypot to track down a German hacker who was breaching US military computers. This foundational work introduced the term “honeypot” to cybersecurity and laid the groundwork for their use in understanding and capturing hacker behavior.
Progressing from theory to practice, the field saw the introduction of the Deception Toolkit in 1997, representing the first instance of a honeypot specifically designed to deceive and retaliate against cyber-attackers.
The following year, in 1998, the cybersecurity industry reached a significant milestone with the release of CyberCop Sting, the first commercial honeypot. This event marked the transition of honeypots from experimental tools used by security experts to mainstream cybersecurity products.
What are Honeypots?
A honeypot in cybersecurity is a mechanism set to detect, deflect, or in some manner, counteract attempts at unauthorized use of information systems. Generally, it consists of a computer 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.
This is distinct from a firewall, which is a network security system that monitors and controls incoming and outgoing network traffic based on predetermined security rules. While a firewall is designed to keep out threats, a honeypot is meant to attract them to learn from their activities or prevent them from causing harm elsewhere in the system.
Here’s Some Honeypot Types
Low-interaction honeypots simulate only basic services that attackers often target. They are less complex and reduce the risk of system compromise. For instance, low-interaction honeypots may emulate simple protocols like file transfer protocol (FTP) without full functionality. Glutton is an example of a low-interaction honeypot.
Medium interaction honeypots offer more advanced interaction than low interaction ones, simulating more services and applications. Kippo is an example of a medium interaction honeypot. They can engage attackers more deeply without exposing the full complexity of a high-interaction system. For example, a medium interaction honeypot may simulate a vulnerable web application but not an entire operating system.
High-interaction honeypots provide real operating systems and full services for attackers to interact with comprehensively. HoneyPLC is an example of a high- interaction honeypot. They are designed to engage attackers in-depth. Honeynets, which typically consist of networks of high-interaction honeypots, are used to study attacker behavior comprehensively.
Honeypot Detection Methods
Identifying honeypots requires spotting abnormal system behaviors and anomalies. Experienced hackers and red team professionals can often recognize honeypots based on their knowledge of how authentic systems typically function under normal conditions.
For example, if an attacker or red teamer successfully breaches a network and conducts a port scan, gaining easy access to a system with weak credentials running a common service like SSH, this would raise suspicions that something unusual may be occurring. However, it typically takes a pattern of anomalies, not just a single abnormality, to conclusively determine a system is a honeypot.
Telltale signs can include increased latency in system responses, certain commands not functioning as expected, or behaviors that seem artificially limited. However, these signs can be brief, as honeypots now come with different technical configurations to mimic real systems more closely.
Services like Shodan's Honey Score analyze systems for telltale honeypot characteristics using standard detection techniques. Offensive Security has also developed modules tailored to identify specific honeypot software, giving professionals multiple options for identification. The overall goal here is to detect inconsistencies that diverge from normal operating procedures on authentic systems.
The Benefits of Using Honeypots
When implemented effectively, honeypots can drastically strengthen an organization's cybersecurity posture.
The Dangers of Using Honeypots
While honeypots provide security advantages, they also come with inherent risks if not properly managed and configured.
Potential dangers include misconfiguration risks, as an incorrectly configured honeypot may fail to capture intended information and could even become a liability by revealing internal network details or allowing attackers to use it as a stepping stone for further attacks.
There are also risks of discovery and subversion, where, although unlikely, an identified honeypot could be subverted by an attacker to feed misinformation to security teams or launch attacks on other targets, potentially turning the defense mechanism against the defenders.
Additionally, honeypots require resources to deploy, maintain, and monitor, so without proper oversight, they run the risk of becoming an inefficient use of funds - especially if they do not deliver the intended security benefits of identifying and studying real threats due to misconfiguration or discovery.
Careful configuration and management are necessary to realize the security advantages while mitigating these risks. Regular monitoring and updating are important to prevent honeypots from becoming outdated or providing inaccurate threat intelligence over time. That said, with the right precautions, honeypots can be a valuable security tool when properly executed.
Introduction to Honeytokens
Honeypots and honeytokens are both deception-based cybersecurity tools, but they differ in important ways. Honeypots are entire simulated environments like systems, networks, or services that are designed to attract and detect attackers. They provide an expansive view of malicious activity by emulating full systems.
In contrast, honeytokens are individual pieces of fake data, credentials, or resources implanted to trigger alerts when accessed. They offer a more focused and lightweight form of deception. Whereas honeypots aim to study threat behavior through comprehensive simulation, honeytokens primarily function as tripwires or canaries.
Dwayne McDaniel
On a side note here, if you’re interested in reading about how honeytokens can play a part in an active cyber defense strategy, I recommend reading this article "Intrusion Detection Through Cyber Deception: Disrupting Attacks With An Active Defense," published in February 2023.
Honeypots vs. Honeytokens
When considering deception-based cybersecurity tools like honeypots and honeytokens, it's important to weigh their respective advantages. Honeytokens offer a less time-consuming option for deployment and management compared to honeypots. They can be quickly deployed without complex configurations, reducing implementation time and effort.
Honeytokens are also much easier to set up and maintain. Organizations do not need to manage entire systems, services, or networks as required with honeypots. Being data-based, honeytokens integrate more seamlessly into pre-existing infrastructure.
Monitoring honeytokens is straightforward as well. Security teams can easily track interaction with honeytokens, focusing on specific data points or assets. This simplicity enhances the efficiency of security operations. Unlike honeypots, honeytokens are typically designed to avoid reacting to scans or automated probes. As a result, they help prevent false positives, ensuring alerts are more likely to indicate genuine threats.
In general, the simplified setup, maintenance, and monitoring of honeytokens make them a more efficient deception-based option for security teams compared to honeypots. Their ability to streamline operations while reducing false alerts further contributes to their advantage(s).
Next Steps With GitGuardian
GitGuardian is actively working towards an automated honeytoken deployment system. This upcoming feature will empower organizations to seamlessly integrate honeytokens into their security strategy, strengthening their defenses without added complexity or manual effort.
If you’re interested in hearing more about this honeytoken technology, click here to schedule a demo.
