Users who rely on ShopSicuro to check an online store before making a purchase may, in some cases, encounter a negative rating or a warning that does not reflect the site’s actual reliability. These cases are known as false positives: situations in which the automated analysis flags a risk that doesn’t actually exist, or assigns a low score to a store that operates properly. Understanding why they occur is important for using the tool correctly and avoiding hasty decisions based on a single result.

What ShopSicuro Analyzes and Where It Can Go Wrong

ShopSicuro’s analysis is based on a series of automated checks: the presence of valid SSL certificates, domain registration, the availability and readability of the terms and conditions of sale, information about the seller, contact details, and other elements that, taken together, provide an indication of an online store’s reliability. The system cross-checks this data in real time by consulting external sources and analyzing page content.

This is precisely the critical point: these are automated checks, not manual reviews conducted by a human expert on a case-by-case basis. An algorithm, no matter how well calibrated, operates based on patterns and thresholds. When a site deviates from the expected pattern—even for entirely legitimate reasons—it may receive a rating that does not accurately reflect its status.

The Most Common Causes of False Positives

One of the most common reasons involves newly launched sites. A domain registered just a few months ago—even if it belongs to a legitimate company duly registered with the Chamber of Commerce—exhibits characteristics statistically similar to those of fraudulent online stores: little history, a lack of established reviews, and no record in reporting databases. The system cannot tell whether it is an honest, new store or a recently created scam: when in doubt, the rating tends toward caution.

A second factor concerns the technical structure of the site. Some legitimate e-commerce sites use unconventional configurations: domains with unusual extensions, SSL certificates issued by less common but still valid authorities, and terms and conditions pages written concisely or structured differently from what the scraper expects. In these cases, the automated analysis may fail to recognize the elements it’s looking for and interpret their absence as a negative signal.

Then there is the issue of unscheduled maintenance and temporary service disruptions. If, at the time ShopSicuro performs its check, the site is partially offline, the server is responding slowly, or certain pages are under maintenance, the checks may return incomplete or incorrect data. The system captures a snapshot of the site’s status at a specific moment: if that moment is unfortunate, the result may be distorted.

Another, less obvious cause involves marketplaces and aggregator sites. Some shops operate as storefronts on third-party platforms or link to terms and conditions hosted on a domain other than the one being analyzed. In these cases, the information that ShopSicuro expects to find directly on the site is missing or scattered, and the analysis is unable to reconstruct the complete picture.

Finally, it’s worth mentioning the issue of contractual clauses. ShopSicuro analyzes the text of the terms of sale using the “Clausola Sicura” tool, which assesses the presence and accuracy of the minimum information required by European consumer protection regulations. Here, too, atypical wording—perhaps overly technical, very concise, or structured in a non-standard way—may slip through the checks or be interpreted as incomplete, even though it essentially contains everything required by law.

How to interpret the results while accounting for false positives

The correct way to use ShopSicuro is to treat it as an initial filter, not as a definitive verdict. A store that receives a warning signal deserves a more in-depth analysis before being ruled out: it’s worth checking whether it has a verifiable presence on social media, whether there are reviews on independent platforms, and whether the seller’s information can be found in the business registry. A negative result from ShopSicuro is a starting point for further investigation, not a conclusion.

The same applies in reverse: a positive score does not equate to an absolute guarantee. The tool significantly reduces the risk of encountering fraudulent sites, but no automated system is infallible. The combination of automated analysis and consumer common sense remains the most effective strategy.

What to Do If You Believe the Assessment Is a False Positive

If you run an online store and believe that the ShopSicuro assessment does not accurately reflect your situation, you can report it through the support channels available on the website. Reports are reviewed and, where necessary, contribute to the continuous improvement of the analysis criteria. The goal is not to penalize honest merchants, but to progressively refine the tool’s ability to distinguish between real and apparent risk.

If, on the other hand, you’re a consumer who has received a warning about a store you know to be reliable, our advice is not to rely solely on the automated result. Use ShopSicuro as a starting point for your assessment, cross-check the information with other sources, and remember that the absence of a particular element in the analysis does not necessarily mean the seller has something to hide.