Ransomware is decided long before the locked screen. It happens the moment someone receives a file they weren’t expecting, downloads it, and opens it. That action, repeated daily in any organization, triggers most real infections, and it’s exactly what a ransomware simulation measures.
Ransomware remains one of the top threats in the current landscape. The latest ENISA Threat Landscape analyzed close to 4,900 incidents between mid-2024 and mid-2025, and again placed it near the top, with social engineering and email among the usual entry routes. Almost the entire security budget goes into stopping that email from arriving and its file from being opened. But no filter stops one hundred percent, and when one gets through, everything depends on what the person does with that file.
What is a ransomware simulation?
A ransomware simulation is a controlled exercise that hands the person a legitimate-looking file and measures what they do with it, with no real damage to systems. The concrete question it answers is simple. Do they download and open it? That is the action that, with real ransomware, starts the infection.
It isn’t an antivirus test or a backup recovery drill, which are technical exercises on the machine. Here the subject is the user and their decision about the file.
Why isn’t prevention enough on its own?
Prevention is necessary and it has a ceiling. The email carrying the file gets more convincing every year, and one person in a hurry is enough to neutralize a flawless filter. Once the file reaches the inbox, the last barrier is no longer technical. It’s the decision to download and open it.
That’s where the blind spot appears. An organization can have its prevention strategy well built and still not know how many of its people would open an unexpected attachment. Measuring that behavior follows the same reasoning we already apply to why it’s worth simulating ransomware. Don’t wait for the real attack to find out how people respond.
What is the behavior that really matters?
In a ransomware attack, the chain breaks or continues at one very specific point, when someone opens the file. Before that there is no encryption and no ransom. That’s why the behavior worth measuring is observable and almost binary. The person downloaded and opened the file, or they stopped.
It’s the ransomware equivalent of what click rate represents in phishing, but on an action with far greater consequences. A well-designed phishing simulation campaign measures the click; a ransomware one measures the next step, the one that hands over control of the machine.
How does a simulation measure that behavior?
The simulation puts a realistic file in front of the user, the kind an attacker would use, and records two signals, whether they download it and whether they open it. There is no harmful content behind it. At the exact moment they open it, instead of an infection an educational moment appears, showing them what they just did and why that gesture, with a real file, would have been enough.
That rehearsal can be repeated and varied. The file format changes, the pretext, the timing of the send. With each repetition, the decision to open an unexpected attachment becomes less automatic and the person learns to pause before doing it.
How do we know if behavior is improving?
What gets tracked over time is observable behavior. How many people downloaded the file and how many opened it. How that percentage changes campaign after campaign. Which areas open more and which learned to be wary. Those numbers, per user and per area, show whether the culture around unexpected files is improving or whether the program only eases the conscience.
Measuring that behavior also changes the conversation with leadership. It lets you move from “we trained everyone” to a concrete figure on how many people would still open the wrong file today, and how many did a quarter ago.
How does SMARTFENSE solve it?
SMARTFENSE is an AI-driven security awareness platform present in more than 30 countries across LATAM and Spain, and its simulation tools include ransomware scenarios alongside phishing ones. The ransomware simulation delivers a realistic file and measures the behavior that matters, the download and the opening, and fires an educational moment right when the user opens the file.
The metrics follow that approach. They don’t stop at a participation score, but at how many people downloaded and opened the file, and how that behavior evolves per user and per area over time. That way the program stops measuring only exposure and starts measuring the behavior that precedes an infection.
Against ransomware, prevention reduces how many dangerous files arrive, and the user’s behavior decides what happens to the ones that get through. When that behavior is measured instead of assumed, the program becomes something you can improve campaign by campaign. If you’d like to see how an exercise like this is designed end to end, a SMARTFENSE demo is a good place to start.
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