What Is a Honeypot in Cybersecurity?

What Is a Honeypot in Cybersecurity?

Learn how honeypots attract and record cyber attacker behavior, turning unsolicited activity into high-value intelligence that traditional defenses rarely capture.

Honeypots in cybersecurity are decoy systems strategically placed alongside an organization’s production systems. They can be designed to mimic many types of assets, such as servers, services, user endpoints, web apps, or OT devices, depending on your goals.

The events and artifacts they collect, for example, security tools, commands, IPs, and paths an attacker uses, can be used to enrich threat intelligence, tune detection rules, validate security controls, and support investigations.

How Honeypots Work

A honeypot looks and acts exactly like a real computer system. It includes applications and data to fool cybercriminals into thinking it’s a legitimate target, such as a company’s customer billing system – a frequent target for criminals hunting for credit card numbers. Once hackers are in the honeypot, their behaviors can be tracked and assessed for clues on how to make the real network more secure.

Any interaction with honeypots is treated as hostile, giving you a clear signal about who is probing you, what tools they use, and how they try to move laterally. This cuts through the noise and allows you to focus on the intruder.

Here is how the honeypot process works:

1. Setup (Contain)

First, you create a safe environment. The honeypot is placed in a “quarantine zone” or a highly isolated section of the network. They cannot move laterally to attack your actual servers or databases.

2. Bait (Lure)

To entice hackers, you have to make the system appear exploitable by deliberately introducing security flaws.

• Weak security: Set up a user account with a weak password (like “Password123”) or leave specific network ports open, making it feel like the hacker found an easy way in.

• Breadcrumbs: Leave fake digital clues. These might be files named “Passwords.txt” or fake API keys to keep them interested and dig deeper into the trap.

3. Surveillance (Observe)

Once the intruder takes the bait, the honeypot acts like a one-way mirror. You’ll be able to record absolutely everything they do without them knowing.

• Recording: Capture every keystroke, every password, and every malicious file they download.

• Analysis: Map attackers’ behavior. Are they looking for financial data? Are they trying to install ransomware? This tells you what kind of threat actor you are dealing with.

4. Response (Act)

Finally, when you gather intelligence, it is used to protect your real network.

• Immediate blocking: Data is sent to your security systems to block that attacker. This includes critical details like the hacker’s IP address or the specific software tool they used.

• Future-proofing: Patch network security vulnerabilities by studying how hackers breached the honeypot, effectively using the criminals’ own tactics against them.

Types of Honeypots

Honeypots are grouped into two main categories: level of interaction (how deep the trap goes) and cybersecurity strategy (how the trap functions). Security professionals can choose different types of honeypots based on what they want to catch and the level of risk they are willing to take.

By level of interaction

These categories define the level of freedom you grant the hacker once they are inside the trap.

1. Low-interaction honeypots

Low-interaction honeypots act as a digital facade. They simulate basic services, like a login screen that doesn’t actually lead anywhere.

 The attacker cannot log in or execute commands, which completely contains the threat and eliminates the risk that the decoy will become a launchpad for further attacks. Teams use these tools primarily for mass threat detection because they offer a high-value signal with minimal maintenance.

For example, during the Log4Shell (Log4j) crisis, threat intelligence firms like GreyNoise used low-interaction honeypots to track the massive wave of initial exploitation attempts. These simple sensors recorded millions of malicious “JNDI” lookup strings without ever executing the harmful code.

2. High-interaction honeypots

High-interaction honeypots function like a fully furnished house with the doors left unlocked. Unlike low-interaction versions, these operate on real operating systems with genuine applications. This allows adversaries to log in, escalate privileges, and deploy malware.

Defenders gain deep forensic insight into the attacker’s tools and lateral movement techniques. However, because the system is real, the risk of containment failure is higher.

While low-interaction traps caught the initial scans for the Log4Shell vulnerability, high-interaction honeypots were required to capture the Khonsari ransomware payload. Microsoft researchers observed the attackers fully executing the ransomware on the decoy system.

3. Pure honeypots

Pure honeypots represent the most authentic environment for deception. They run on physical hardware within the production network and mimic actual business assets perfectly, rather than using virtualization.

This physical realism deceives sophisticated adversaries who can identify and avoid virtual environments. These systems offer the highest fidelity intelligence but are resource-intensive and difficult to scale.

In particular, the analysis of the Stuxnet worm required physical hardware (a pure network of honeypots) because the malware specifically targeted Siemens Step7 software on physical Programmable Logic Controllers (PLCs). Virtualized environments failed to trigger the malware’s payload.

By deployment strategy

These honeypot types describe the specific mechanism or technology used to set the trap.

1. Virtual honeypots

They run inside a virtual machine (VM) rather than on a physical computer. Virtual honeypots are lightweight and cheap to run. If a hacker infects one with a virus, you can simply delete the virtual machine and spin up a fresh one in seconds.

Cloud security researchers frequently use virtual honeypot software (specifically vulnerable Docker containers) to catch groups like TeamTNT. These attackers automatically scan for exposed cloud resources to install cryptocurrency miners. Because the honeypots are virtual, researchers can let the infection happen, record the attacker’s script and wallet address, and then instantly wipe and reset the container to catch the next wave.

2. Decoy honeypots

These are fake assets injected directly into the real network to confuse the attacker. Decoy honeypots (like decoy databases or cloud accounts) make it nearly impossible for a hacker to find the real valuable data without triggering an alarm.

Security teams frequently place Honeytokens (decoy AWS access keys) inside code repositories to catch credential thieves. Research by Palo Alto Networks Unit 42 shows that attackers often use automated bots to scrape these keys within minutes of exposure.

When the attacker attempts to use the decoy key to log in, it fails to grant access but instantly alerts the security team to the breach and the attacker’s IP address.

3. Sticky honeypots (Tarpits)

This honeypot is designed to waste an attacker’s time. It acts like digital quicksand. When a hacker scans this system, the sticky honeypot responds very slowly or keeps the connection open indefinitely. This frustrates the attacker and buys your security team more time to respond.

During the Code Red worm outbreak, network defenders deployed the LaBrea tarpit to combat the infection. The worm spread rapidly by opening connections to infect new servers. LaBrea answered these requests but refused to close the connection, effectively holding the worm’s threads hostage.

4. Watering hole honeypots

The watering hole approach places a trap in a location that attracts a lot of network traffic or attention, like predators waiting by a river. Instead of waiting for a hacker to scan the network, you place a honeypot near a popular file server or directory. Watering hole honeypots detect hackers who are already moving through the network, looking for high-traffic areas.

For instance, ransomware groups like LockBit are known to aggressively scan and encrypt shared network drives to maximize operational disruption. Defenders counter this by placing “canary files” (documents that act as watering-hole honeypots) within these public folders.

When the ransomware script attempts to modify or encrypt this specific file, it triggers a high-priority alert, allowing the security team to isolate the infected machine before the encryption spreads to critical data.

Key Components of a Honeypot System

Honeypots work when the parts are simple, isolated, and measurable. To establish a minimal yet enterprise-ready stack that generates high-signal telemetry without introducing new risks, the following components are essential:

• Decoys and lures: The core trap. This includes believable decoy systems (hosts, containers, services) and the breadcrumbs (canary tokens, fake credentials, API keys) seeded in realistic locations to attract an adversary.

• Aggressive isolation: The containment. Decoys must be placed in a separate VLAN, VPC, or cloud account with default-deny egress rules. This is a hard requirement to prevent a breach from becoming a pivot point.

• Instrumentation and telemetry: The “black box” recorder. This is the out-of-band mechanism that captures all attacker activity (packets, commands, file changes, memory) and sends it to a secure, separate logging system.

• Orchestration and automation: The management engine. This is the control plane that automatically deploys, rotates, and tears down decoys. It randomizes artifacts to avoid fingerprinting and enables quick resets after an engagement.

• Integration and data pipeline: This acts as the bridge between detection and response. It feeds the alert from the honeypot to your main security system so you can immediately block the intruder or isolate the cyber threat.

Benefits of Using Honeypots

Honeypots in cybersecurity add value by improving signal quality and shortening the path from detection to action. Blue teams are typically required to sift through significant noise for actionable intelligence. A honeypot functions as a zero-noise sensor. Any alert it generates is a high-fidelity, actionable signal, not more fatigue.

Here are the top five benefits of a honeypot in enterprise environments:

1. Yields high-fidelity alerts

Since legitimate users have no reason to touch a honeypot, any activity is inherently suspicious. This certainty eliminates false alarms and acts as a critical early warning system for threats that standard analytics often miss.

2. Captures raw TTP and threat intelligence

Decoys record an attacker’s live commands, tools, and infrastructure. This rich telemetry is converted into new, behavior-based detection rules for SIEM and XDR, improving defenses across the entire production environment.

3. Validates security controls and discovers gaps

When an attacker interacts with a decoy, you get a real-world test of your security stack. Missed EDR alerts or failed segmentation rules reveal tuning gaps and hardening priorities. Observed exploit attempts also show what attackers are targeting first.

4. Detects internal and application-specific threats

Honeypots are uniquely suited for “inside-the-perimeter” threats. Honeytokens and fake shares detect insider misuse and lateral movement. API and web decoys can surface specialized threats like e-commerce fraud, bot activity, and account takeover attempts.

5. Offers a scalable and cost-effective profile

Low-interaction decoys are fast, safe, and cheap to deploy, providing broad coverage. A few high-interaction decoys can be added surgically to provide deep forensic insight where it’s most needed, giving you a flexible cost-to-value ratio.

Risks and Limitations of Honeypots

Deploying honeypots introduces controlled risk. Getting value requires tight containment, clear governance, and realistic expectations about what a sensor can and cannot see.

• Compromise and pivot: If a high-interaction honeypot is breached and not properly isolated, attackers can use it as a foothold. Containment must be strict.

• Evasion by skilled malicious actors: Adversaries can fingerprint decoys, refuse to engage, or feed false data, which reduces the intelligence value.

• High operational overhead: Realistic honeypots require skilled setup, active monitoring, and regular refresh. Set-and-forget makes them easy to spot.

• Limited visibility: A honeypot only sees what interacts with it. It cannot confirm what attackers are doing elsewhere in the environment.

• Legal and policy exposure: Data collection must comply with privacy laws, the deployment purpose must be documented, and isolation must be verifiable to reduce liability if the decoy is abused.

Honeypots vs. Honeynets

A honeypot is a single decoy. A honeynet is a coordinated network of decoys that mimics a small, realistic segment of a network. Use a honeypot for fast, low‑overhead signals. When you need to observe attacker behavior across multiple critical systems at the campaign level, a honeynet is a better choice in the United States.

Let’s examine the key differences between honeypots and honeynets in the table below.

Real-World Use Cases of Honeypots

Honeypots deliver practical wins across common enterprise scenarios. The following examples highlight how early warning, comprehensive telemetry, and enhanced detection and response capabilities can be achieved:

1. IoT/OT reconnaissance and malware analysis

The Mirai botnet, which famously took down large portions of the internet (like Dyn, Twitter, and Netflix), was discovered and analyzed almost entirely thanks to honeypots.

Security researchers set up low-interaction Telnet honeypots. They noticed that automated scanners were attempting to log in with a hard-coded list of about 60 default factory passwords (such as admin/admin or root/password).

Once “infected,” the honeypots revealed the botnet’s TTPs. It would scan the internet for other vulnerable IoT devices, report back to its C2 server, and await orders for a DDoS attack. This is the textbook case for using honeypots to map botnet infrastructure and capture malware payloads.

2. Cloud and API abuse

Security researchers used a cloud honeypot to analyze how attackers abuse stolen AWS and other cloud credentials.

They intentionally “leaked” fake but valid-looking AWS access keys in public locations, such as GitHub repositories. The honeypot was rigged to send an immediate alert the moment the key was used.

Within minutes, automated scanners like the AndroxGh0st malware found the keys and immediately began programmatic reconnaissance, attempting to query services such as Amazon SES (Simple Email Service) to find and exfiltrate additional sensitive information. This provided a perfect, real-time feed of malicious IPs and attacker TTPs for cloud environments.

3. Email traps and phishing research

The Spamhaus Project, one of the world’s largest and most respected anti-spam organizations, is essentially a massive, distributed honeypot operation.

Spamhaus maintains a huge list of “spam trap” email addresses. These are addresses that have never been used for legitimate mail. Some are “pristine” (created solely as traps), and others are “recycled” (old, dead addresses).

Any email sent to these addresses is, by definition, unsolicited spam. Spamhaus analyzes the stream of malicious mail, identifies new spammer IPs, phishing domains, and malware-hosting sites, and publishes them in real-time blocklists that mail servers worldwide use.

Best Practices for Deploying Honeypots

Effective honeypots are safe, realistic, and measurable. The practices below focus on isolation, credibility, and outcomes rather than specific tools:

• Define objectives and scale deliberately. Clarify goals, TTP collection, or control validation. Start with low-interaction decoys for breadth, adding high-interaction decoys for depth only when containment and metrics are stable.

• Isolate aggressively and design for realism. Enforce containment as a hard requirement. Use separate accounts, strict IAM, and default-deny egress. Mirror production banners, seed synthetic user artifacts, and never use live datasets.

• Capture and harden all telemetry. Log packets, commands, and memory snapshots using out-of-band collection. Forward events to centralized, immutable storage and document the chain of custody.

• Integrate with security operations. Forward normalized events to SIEM, XDR, and TIP. Map behaviors to MITRE ATT&CK and build automated response playbooks, such as host isolation or token rotation.

• Refresh and validate continuously. To keep the trap effective, IT teams must regularly “rotate the bait” by changing credentials and updating file timestamps to maintain the illusion of life.

Role of Honeypots in Threat Intelligence

Honeypots act as controlled collection points that capture real attacker behavior with minimal background noise. Data security analysts use this telemetry to create and refine threat intelligence that drives protection and hunting.

Honeypot data also exposes emerging threats by surfacing unique indicators and behaviors that do not yet appear in other feeds. The time from the initial decoy interaction to publication is tracked so new rules can be promoted to production and findings can be confirmed in real systems.

This role improves early warning, focuses hunting on the right assets and time windows, and prioritizes catching real attacks in your environment with minimal noise. It complements dark web monitoring and digital forensics.

Here’s what this looks like through the Group-IB Threat Intelligence Platform:

• Collection

Decoys enable us to capture malicious IPs, domains, URLs, command transcripts, payload hashes, tools, persistence artifacts, and malware samples from live sessions, and to hunt for TTPs with prefetch files.

• Enrichment

Our analysts map events to MITRE ATT&CK, cluster by infrastructure, and form hypotheses to test across the environment. This turns behavioral context into targeted hunting queries.

• Dissemination

Enriched data is distributed to SIEM, XDR, and EDR integrations. High-confidence indicators are also pushed to perimeter and inline controls, such as firewalls, DNS filters, web and email gateways, web application firewalls (WAFs), and endpoint platforms, to block the reuse of the same infrastructure.

This updates detection rules across the stack and provides evidence packages to support takedown requests against scam kits or other abusive infrastructure.

Turn Honeypot Alerts Into Proactive Defense

Honeypots work best when they feed real operations. Our experts use them to reveal attacker tools, paths, and intent across identity systems, application tiers, and cloud control planes.

Here is how we convert those signals into decisions that your SOC can trust:

• • Threat Intelligence enriches honeypot hits with adversary profiles and mapped TTPs. Your team can triage by risk, attribute activity with confidence, and track infrastructure overlap across campaigns.
  • Managed XDR correlates honeypot activity with endpoint, network, and cloud telemetry to raise high-fidelity detections and guide incident response.
  • Digital Risk Protection extends visibility to external infrastructure, leaked data, and staging activity that references your decoys. It also supports takedowns to disrupt attacker preparation.

Get in touch with Group-IB experts today for an assessment on how your SOC can deploy honeypots to catch intrusions earlier and reduce risk with defensible evidence.