How to Manage False Clicks in Phishing Simulations for Security Awareness Training

Struggling with false clicks in your phishing simulations? Learn how to manage these automated interactions for accurate results. Improve your cybersecurity training and ensure employees are properly assessed to strengthen your defense against real phishing threats.

2024-10-28

How to Manage False Clicks in Phishing Simulations for Security Awareness Training

Managing false clicks during phishing simulations is a crucial part of making sure your security awareness program is both effective and fair. Whether you’re using Gophish or a more advanced solution like KnowBe4, Cofense PhishMe, Proofpoint Wombat, or Keepnet Phishing Simulator, one thing remains the same: you want to raise cybersecurity awareness among your employees. For that to happen, the phishing tests need to be accurate, and false clicks—those unintentional interactions—can really mess with your results.

Identifying actual risky behaviors, such as employees clicking on malicious links, submitting credentials on fake websites, or even scanning quishing QR codes, is key to making your phishing simulations work. So, let’s dive into what false clicks are and how to manage them effectively.

What is a false click in phishing simulations?

In a phishing simulation, a false click is when a click or interaction is mistakenly logged as coming from an employee, but it was actually triggered by automated security tools. Tools like Mimecast, Barracuda, or Microsoft Defender often scan emails for threats, and this can set off false clicks in phishing simulations. These false positives mess up your reports, making it look like employees are falling for phishing attempts when they’re not.

If you don’t manage these false clicks, your cybersecurity training may become unreliable, and employees may lose trust in the process, thinking they’re being unfairly singled out.

Why false clicks happen in phishing simulations

False clicks are usually caused by security solutions that scan emails automatically. Tools like Mimecast, Proofpoint, or Barracuda will open emails and follow links to make sure they’re safe. The problem is, these tools act just like real users, triggering clicks that your phishing test software can misinterpret as employee actions. This can cause confusion and affect the accuracy of your cybersecurity awareness training.

The challenge false clicks create

Imagine your colleague, Bob, coming to you frustrated. He didn’t click on any of the phishing emails, but he still got flagged in the phishing simulation report and now has to redo his security awareness training. He’s not happy about it and neither are you.

This situation highlights a common problem: false clicks making it look like an employee failed a phishing test when they didn’t. It’s frustrating and unfair, and it can damage trust in your security awareness program.

Whitelisting isn’t enough

Whitelisting phishing simulation emails might seem like a good way to prevent false clicks, but it’s not a complete solution. Even if you whitelist the sender's address, secure email gateways (like Barracuda or Microsoft Defender) still scan and open these emails, leading to false interactions.

How to eliminate false clicks

To eliminate false clicks, your phishing simulation needs to use some smart technology. Here are a few effective ways to filter out these false clicks:

1. Unusual user-agent detection

Security tools use user-agents that are different from what a real user would use. For instance, a normal user might browse with Chrome or Firefox, while an automated security tool might use Python or Java. Phishing software that can detect these unusual user-agents can filter out false clicks from your reports.

2. Honeypot links

Adding invisible honeypot links to phishing emails is another great strategy. Regular users won’t see these links, but automated systems will. By tracking interactions with these hidden links, your phishing simulation tool can identify false clicks and exclude them from reports.

3. Anomaly detection

Sometimes the behavior of security tools is odd, like opening an email many times in a few seconds or clicking a link repeatedly. These behaviors are clear signs of an automated scan, not a human interaction. Using anomaly detection can help filter out these false clicks. You can even flag interactions from unusual locations. For example, if an employee in London appears to be clicking on emails from a U.S. IP address, it’s probably a false click.

How Keepnet handles false clicks

At Keepnet Human Risk Management Platform, we’ve designed a Sandbox Detection System that helps eliminate false clicks caused by secure email gateways and other automated tools. We combine honeypot links, unusual user-agent detection, and anomaly monitoring to ensure that only real interactions are counted. This makes sure your phishing test reports are accurate and reliable.

Unlike KnowBe4 and other vendors, we’ve built this feature specifically to tackle false clicks, reducing frustration and ensuring fair training results. You can stop worrying about incorrect data and focus on improving your team’s security awareness.

Real examples of false click detection

To give you an idea of how our false click detection works, here are two real-life examples from our phishing simulations:

One campaign detected interactions from non-standard user agents like HeadlessChrome, flagging them as false clicks. This ensured that the simulation results were accurate and that only actual user behavior was logged.
In another case, our honeypot feature caught multiple interactions from a security tool’s IP address. These were marked as false clicks, ensuring that the phishing test results reflected actual user actions, not automated scans.

False Click Detection Sample 1 — Picture 1: False Click Detection Sample 1

False Click Detection Sample 2 — Picture 2: False Click Detection Sample 2

These examples show the power of smart phishing test software in eliminating false clicks and improving the accuracy of your simulations.

Best practices for managing false clicks

Managing false clicks is all about using advanced phishing test software with features like anomaly detection, honeypot links, and user-agent filtering. Here are some tips to keep in mind:

Choose phishing software that can detect and exclude false clicks from automated systems.
Regularly review and adjust your security systems to stay ahead of evolving techniques used by automated scanning tools.
Make sure your reports are based on real user actions so that your security awareness training is accurate and fair.

Why false click detection is critical

False click detection is important because it ensures the integrity of your phishing simulations. Without it, you risk making decisions based on faulty data, which can weaken your overall cybersecurity posture. Accurate simulations give you a true picture of your organization’s risk and help you build a more effective cyber security awareness training program.

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Frequently Asked Questions

How do false clicks affect the overall accuracy of phishing simulation reports?

False clicks can significantly distort the results of your phishing simulations. These clicks, often triggered by automated security tools or email scanning gateways, can make it appear as though employees are interacting with phishing emails when they haven’t. This creates an inaccurate representation of your organization’s risk level, making it harder to assess employee behavior and adjust your cybersecurity awareness program accordingly. It can also waste time on unnecessary follow-ups with employees who didn’t actually fall for the simulation.

Can false clicks impact my organization’s phishing training strategy?

Yes, false clicks can directly impact your phishing training strategy. If these are not properly managed, you might end up targeting the wrong employees for additional training. This could lead to decreased engagement and frustration from employees who feel they’ve been unfairly penalized. The effectiveness of your security awareness efforts depends on accurate reporting, so filtering out false clicks ensures the training reaches those who actually need it.

How do automated email security systems create false clicks?

Automated email security systems, like Mimecast, Proofpoint, or Microsoft Defender, scan emails and follow links to check for malicious content. These systems open attachments, click links, and sometimes even interact with phishing pages as part of their process to determine if an email is safe. During this scanning process, the phishing simulation software may log these actions as if they were performed by an actual user, which results in false clicks. This type of behavior is common with sandbox environments or Integrated Cloud Email Security (ICES) tools.

How can phishing simulations be designed to avoid overwhelming employees with training based on false positives?

By ensuring your phishing simulation platform uses advanced false click detection methods like honeypot links, anomaly detection, and unusual user-agent monitoring, you can significantly reduce false positives. This ensures that only real user actions are reported. Phishing simulation tools should be configured to exclude interactions from security scanning tools, ensuring that employees are only assigned additional training when they genuinely fail a phishing test.

What happens if false clicks are ignored or not properly managed?

If false clicks aren’t managed, your phishing simulation data will be unreliable. Employees who are falsely flagged may lose trust in the training program, leading to a disengaged workforce. Additionally, cybersecurity decisions based on inaccurate data could leave real vulnerabilities unaddressed, putting your organization at risk. Ignoring false clicks also means that security awareness efforts will be misaligned, potentially leaving genuine weaknesses in employee behavior uncorrected.

Are false clicks more common with certain types of phishing attacks, like quishing or smishing?

Yes, false clicks may be more common in certain types of phishing simulations, such as quishing (QR code phishing) or smishing (SMS phishing), because these simulations involve unique interactions with external links or codes. For example, security systems that scan QR codes or SMS links could mistakenly trigger interactions, leading to false clicks. However, advanced phishing simulation tools should be able to detect and filter these false interactions using techniques like honeypot detection and unusual behavior monitoring.

How can I optimize the delivery of phishing simulations to reduce the risk of false clicks?

To minimize the risk of false clicks, it's essential to properly configure your phishing campaigns. This might include whitelisting domains to reduce security scans but also employing advanced detection methods like honeypot links or anomaly tracking to identify and exclude automated interactions. You should also consider testing your phishing simulations on a small scale first to spot any issues with false positive clicks before rolling them out to the entire organization.

Do mobile devices trigger false clicks during phishing simulations?

Yes, mobile devices can contribute to false clicks during phishing simulations, especially when mobile email apps or security software automatically open emails and links. Mobile operating systems sometimes handle email previews and link interactions differently from desktop systems. However, a robust phishing simulation tool will be able to detect these patterns by looking at user-agent data to distinguish between real human actions and automated actions triggered by mobile devices or apps.

What are the key indicators to detect a false click?

There are several key indicators that suggest a false click in a phishing simulation:

These indicators can be monitored and flagged to filter out false clicks effectively.

Multiple quick clicks or email openings within a short time frame.
Unusual user-agent information, such as Python or Java, that isn’t typically used by employees.
Interactions from security tool IP addresses instead of employee locations.
Links or phishing pages accessed from unexpected regions, such as IPs from different countries than where the user is based.
Repeated interactions with invisible honeypot links that human users wouldn’t see.

How can phishing simulation tools evolve to better handle false clicks in the future?

Phishing simulation tools can evolve by continuously improving the use of machine learning and behavioral analytics to better understand and differentiate between human and automated interactions. Enhanced use of contextual data like user location, device type, and real-time behavior could also help refine the detection of false clicks. Additionally, tighter integration with email security solutions will allow for more seamless communication between systems, reducing the chances of automated scans creating false positives. Regular updates to handle new types of phishing threats, like callback phishing and quishing, will also keep false click detection relevant as attack methods evolve.