Why Better Phishing Simulations Are Key to Preventing Data Breaches

Phishing continues to dominate industry reports on the most successful and common cyberattack types, with the most recent Comcast Business Cybersecurity Report listing 2.6 billion phishing attempts per year. What’s more, the trending use of AI tools has even further emboldened malicious actors.

To combat this threat, many security-conscious organizations have implemented phishing simulations and other forms of phishing training, effectively raising employee awareness around the issue. Yet, phishing-related data breaches still persist, posing the question of whether adopting a program based on simulations is even worth it.

Often, the key lies in how these simulations are designed and delivered. Let’s examine what it takes to build a strong phishing simulation program that actually changes behavior for the better and reduces the risk of data breaches.

The Impact of a Strong Phishing Simulation Program

Before we get into what makes a phishing simulation program effective, let’s explore the reasons for its existence. There are two parts of the equation: the stakes involved with addressing the phishing problem and the proven effects of training simulations as a practical and cost-effective method for human learning.

Phishing simulations target the most heavily exploited attack vector: human error. No matter how advanced your technical defenses are, a single click on a malicious link can bypass them all. Traditionally, businesses have tried addressing this problem by conducting annual security awareness training or distributing generic informational materials.

However, as humans, we learn best through experience. A strong phishing simulation program builds tangible skills, and reinforces actual behavior patterns, for the workforce to spot, report, and respond to phishing attempts in real time. 

The positive effects extend beyond individual improvements. Over time, phishing simulations shape a security-aware culture where employees become the first line of defense, rather than the weakest link in the security chain.

Poorly Executed Phishing Simulations Are Risky

With that said, organizations must be careful in how they design and deliver phishing simulations, as poor execution can have the opposite of the desired effect.

The main culprits of ineffective simulation is the use of generic, irrelevant templates. The templates may be old and not reflective of the current sophistication of phishing attacks, or they might not be personalized to reflect the recipient’s role. This type of simulation will likely create a false sense of security, which will backfire when employees face a real, more advanced threat.

Even if the training material is relevant, it must be delivered correctly and with the right intentions. When phishing simulations are framed as traps designed to catch people or embarrass them, they quickly lose their educational value. Employees may begin to feel that the security team is out to shame them, rather than support their learning.

If this persists, employees will be less likely to engage and retain the information from the training, and may even be hesitant to report real phishing attempts due to their mistrust of the IT team.

A perfect example of a poorly-executed simulation comes from the University of California, Santa Cruz. In 2024, the university sent recipients a phishing test claiming they had been exposed to Ebola and needed to take immediate action. The test sparked unnecessary panic on campus and eventually outrage among faculty and staff, who justifiably felt it was an inappropriate technique. Instead of building security awareness, it only created fear and resentment toward the IT team.

What Makes a Phishing Simulation Effective?

To drive real behavioral change and reduce the risk of phishing-related data breaches, phishing simulations must go beyond basic click tests. Here are some key elements that set successful programs apart.

First, effective programs focus on mimicking real-world phishing techniques that are relevant not just for the organization, but also to the individuals based on their roles and the types of threats they are most likely to encounter.

For example, the finance team will likely benefit most from receiving training on fake vendor payment requests or invoices. Even tech giants like Meta and Google would have benefited from this type of training before being tricked into wiring over $100 million to a fraudster posing as a legitimate supplier a few years ago.

These types of scams can happen any time, so simulations shouldn’t follow a pre-determined and predictable pattern. Instead, they must be sent randomly, mixed together with real emails the employee might receive during the day. 

Once the employee interacts with the simulation email, a micro-learning session should be initiated in real time to help employees understand what they missed (and how to spot similar attacks in the future), or to praise them for their successful identification of a phishing message. This reinforces the learning element, turning mistakes into immediate teaching moments without penalizing or shaming.

Lastly, all solid phishing simulation programs are data-driven. Metrics like click-through rates, report rates, and repeat offenses will help the IT team understand whether progress is being made, and how they can steer their efforts to produce better outcomes. It will also pinpoint vulnerable groups they can target for more personalized training.

Conclusion

With phishing emails sent by the thousands each day, targeting organizations of all industries and sizes, phishing simulations have emerged as an effective and cost-efficient solution.

When done well, phishing simulations don’t just test awareness, they cultivate it. They help employees learn how to think critically in a fast-paced environment, where simple negligence can lead to devastating breaches.

Learning how to properly incorporate phishing simulations into its cybersecurity program will set an organization apart from one that reactively responds to incidents, to one that expects and prevents them.