How to Avoid Network Honeypots?

Honeypots are an intriguing defensive tool experiencing explosive growth. The market is set to more than triple from $2.4 billion in 2024 to $7.5 billion by 2033, at a 14% annual growth rate. This surge reflects their evolving role. While originally designed to defend servers from hacker attacks, network honeypots acquired another vital purpose as bots and data collection became ubiquitous: protecting websites from web scraping.

Honeypots are decoys that seem like a compromised system to malefactors, making them appear to be an easy target. The use of honeypots makes it easy to divert hackers’ attention away from the real target. Moreover, cybersecurity experts use this application to investigate cybercriminal behavior and identify and resolve vulnerabilities.

However, as we all know, every problem has a solution. And, just as honeypots solved many issues, data gatherers discovered a solution to honeypots. In this post, you will learn all you need to know about this tool and how to avoid honeypots.

Also read: Web Scraping With Proxies

How Do Network Honeypots Work?

For a honeypot to function, the system must look genuine. In addition to performing the same operations that a production system would perform, it should also include fake files that seem essential. Any machine equipped with sniffing and logging capabilities may serve as a honeypot. Additionally, it is a good idea to place a honeypot inside a corporate firewall. Not only does it provide vital logging and alerting features, but it can also block outbound traffic, preventing a hacked honeypot from pivoting toward other internal assets.

For a honeypot to be effective, it must mimic a real system closely enough that attackers will believe it to be genuine, complete with fake files that appear essential to its operation.

Source: Spitzner, L. (2003). Honeypots: Catching the insider threat. In Information Security Management Handbook (pp. 213-223). CRC Press

There are various types of honeypots based on their use and size. Rather than overwhelm you with extraneous information, we will only cover the most important and relevant categories. Also, there are different honeypot technologies that we will cover below. You can’t avoid something that you don’t know how to do.

Also read: Five Tips for Outsmarting Anti-Scraping Techniques

Honeypot Varieties

• Pure honeypot. It is a full-scale, production-like system that runs on several servers. It is packed with sensors and includes fake confidential data and user information. Although they might be complicated to manage, the information they produce is priceless.
• High-interaction honeypot. As a pure honeypot, it runs several services, but it is not as complicated or holds as much data. The purpose of high-interaction honeypots is not to be produced at full scale. However, they seem to handle all the services of a production system, including an operating system. With this type of honeypot, the business can monitor aggressors’ practices and techniques. High-interaction honeypots require a bunch of resources and are hard to handle, but the by-products may be worth it.
• Mid-interaction honeypot. These mimic parts of the application layer but lack their own operating system. The goal is to slow or confound attackers to give businesses more time to determine how to respond.
• Low-interaction honeypot. Most honeypots used in production settings are of this type. Low-interaction honeypots operate a few services and function primarily as an early warning and detection tool. Security teams install honeypots throughout their networks because they are easy to build and manage.

Also read: Data Parsing with Proxies

Honeypot Technologies

• Client honeypots. The bulk of honeypots are servers that are skimming for links. Client honeypots actively search for malicious servers that attack clients, keeping an eye out for any strange or unusual changes to the honeypot. Systems like these usually use virtualization technology and include containment mechanisms to protect the research team.
• Database honeypots. Firewalls frequently ignore SQL injections, for instance. Therefore, some businesses deploy database firewalls that include honeypots to generate fake databases.
• Honeynets. A honeynet is another type that demands its own description. It is a network of honeypots used to monitor large-scale systems that require the use of more than one honeypot. Firewalls protect honeynets, which monitor all incoming traffic and route it to honeypots. In addition to gathering information on criminal activity, this counterfeit network safeguards the genuine network. For analyzing DDoS attacks and ransomware attacks, researchers use honeynets. Cybersecurity professionals also use them to defend business networks since a honeynet includes all incoming and outgoing traffic.
• Malware honeypots. To identify malware, they use well-known replication and attack pathways. Honeypots mimic USB storage devices. If a system becomes infected with malware that spreads via USB, the honeypot will fool the infection into infecting the emulated device.
• Spam honeypots. They are utilized to forge open mail relays and open proxies. Spammers will first dispatch themselves an email to sample the open mail relay. If they are successful, they will send out a tremendous amount of spam. In this way, the honeypot can detect and identify the spam that follows, as well as effectively block it.

Also read: Business Growth Using Proxies

How to Avoid Network Honeypots?

Anti-crawler honeypots are similar to anti-spam honeypots. They exist to keep websites safe from data theft. However, there is a drawback: they cannot distinguish between harmful and authorized crawlers. Even if you just obtain publicly accessible information for legal purposes, honeypots will still affect you.

Bot Fight Mode (BFM) and Super Bot Fight Mode (SBFM) are designed to stop active attacks quickly. Due to their aggressive nature, false positives can occur where legitimate human or automated traffic is incorrectly challenged or blocked.

Source: Cloudflare Official Documentation

The remedy is simple. Change your IP address with each request, and you will be far less likely to get a ban. You can accomplish that effectively and simply by using residential proxies. Because these are IP addresses of real-world devices, honeypots will not mistake your crawler for a bot. Your crawler’s request will be sent to one of the devices and subsequently to the destination server. Thus, the target server will see the IP address of the proxy, making it believe that the user is unique.

You should also be aware that some honeypot URLs will have the CSS style display:none. That might be a method for detecting a honeypot. Other honeypots may blend in links with the background color, so ensure that your crawler only follows visible connections.

Also read: Free Libraries to Build Your Own Web Scraper

Signs You’ve Triggered a Honeypot

Recognizing when you’ve fallen into a honeypot trap is crucial for web scraping operations. The sooner you identify honeypot detection, the faster you can adjust your approach and avoid permanent IP bans or legal complications. Here are the telltale signs that your scraper has triggered a honeypot:

Sudden IP Blocks or CAPTCHA Challenges

One of the most obvious indicators is when your previously successful scraper suddenly encounters CAPTCHA challenges or complete IP blocks. If your crawler was accessing a website without issues and then abruptly gets challenged or blocked, you likely interacted with a honeypot element. This is especially suspicious if the block happens immediately after following a specific link or accessing a particular page.

Fake or Corrupted Data Responses

Honeypots often serve deliberately incorrect or nonsensical data to identify and waste the resources of scrapers. If you notice that the data you’re collecting suddenly becomes:

• Inconsistent with what you see in a regular browser
• Contains obvious placeholder text or random characters
• Shows pricing that seems unrealistic or impossible
• Includes product descriptions that don’t match the titles

These are strong signals that you’ve been flagged and the server is feeding your bot false information instead of real content.

Unusually Slow Response Times

A dramatic slowdown in server responses can indicate that your requests are being routed through a honeypot or tarpit designed to waste your computational resources. If pages that previously loaded in milliseconds now take several seconds or even timeout, the website may be deliberately throttling your bot to make scraping economically unviable.

Redirect Loops or 403 Errors

Getting caught in endless redirect chains or receiving persistent 403 (Forbidden) errors when your browser can access the same pages normally is a classic honeypot symptom.

Websites use these techniques to trap bots while allowing legitimate users to browse freely. If your scraper keeps getting redirected between the same two or three URLs without ever reaching the actual content, you’ve likely triggered a trap.

Differential Content Serving

One of the more sophisticated honeypot techniques involves serving different content to bots versus browsers. Warning signs include:

• Your scraper retrieving empty pages while browsers see full content
• Missing images, JavaScript, or CSS resources in bot requests
• Receiving older or cached versions of pages instead of current content
• Getting served a completely different website layout or structure

You can test this by comparing the HTML your scraper receives against what you see when inspecting the page source in a regular browser. Significant differences indicate the server is fingerprinting and segregating your bot traffic.

Unexpected JavaScript Challenges

If your headless browser or scraper suddenly encounters JavaScript challenges that weren’t there before, such as complex fingerprinting scripts, invisible reCAPTCHA v3 checks, or browser behavior verification, the website has likely identified your automated activity and deployed countermeasures.

Honeypot-Specific Patterns

Watch for these technical indicators in your logs:

• HTTP headers that differ from what a browser would send
• Cookies that track honeypot interactions, often with names like “hp_trap” or “bot_check”
• URLs in your access logs that contain “/honeypot/”, “/trap/”, or similar obvious naming
• Server responses that include meta tags blocking robot indexing specifically for your requests

By monitoring these warning signs, you can quickly identify when your scraper has triggered a honeypot and take corrective action before facing more severe consequences like permanent IP blacklisting or legal action.

Conclusion

You should also follow the guidelines for effective web scraping, such as using diverse headers and avoiding sending too many queries. All of these approaches will make your crawler seem to be a genuine user rather than a bot, enabling you to collect all of the necessary data.

Avoid network honeypots, outsmart anti-scraping techniques, and make sure your web scraping project delivers on time.

FAQs About Network Honeypots

Q1. What is decoy honeypot?

A decoy honeypot is a fake system designed to lure in attackers, making them think they’ve found something valuable to exploit. It’s like setting a trap. These honeypots can be anything from fake servers to decoy databases, giving attackers something to target while keeping your real systems safe.

When an attacker launches a malware attack or tries to hack into a system, they might end up in a production honeypot instead of a real, sensitive system. The honeypot logs all their actions, helping you understand how they operate and what they’re after, without putting your actual data at risk.

So, the next time a hacker thinks they’re onto something, they’re really just messing around in a decoy honeypot, letting you monitor their behavior while keeping your systems safe!

Q2. What’s the difference between low and high-interaction honeypots?

Low-interaction honeypots run few services and primarily provide early warnings. They’re easy to deploy and manage. High-interaction honeypots simulate full production systems with multiple services and operating systems, allowing detailed monitoring of attacker techniques but requiring significantly more resources to maintain.

Q3. How do honeypots detect web scrapers?

Honeypots detect scrapers by monitoring request patterns, tracking IP addresses making repeated requests, and using hidden links with CSS display:none or links matching background colors. When bots interact with these invisible elements that normal users wouldn’t see, the honeypot identifies them as automated scrapers.

Q4. How can I avoid honeypot detection while scraping?

Use residential proxies to rotate IP addresses with each request, making traffic appear from real devices. Only follow visible links, avoiding hidden elements with display:none CSS or background-matching colors. Vary request headers and limit query frequency to mimic genuine user behavior.

Q5. What is a honeynet?

A honeynet is a network of multiple interconnected honeypots protected by firewalls. It monitors all incoming and outgoing traffic, routing threats to decoy systems. Honeynets are used for analyzing large-scale attacks like DDoS and ransomware while protecting the actual production network.