
Fake-Shops Detection Certification 2025 – F-Secure Internet Security
| Release date | 2025-11-06 |
| Revision date | 2025-10-13 |
| Test Period | October 2025 |
| Number of Testcases | 500 |
| Online with cloud connectivity | ![]() |
| Update allowed | ![]() |
| False Alarm Test included | ![]() |
| Platform/OS | Microsoft Windows |
Introduction
Online consumers face significant risk when inadvertently accessing fake web shops, which are often designed with a high degree of sophistication to closely mimic legitimate e-commerce websites.
Besides the critical threat of data theft, an equally concerning risk is the potential to make purchases under the pretence of genuine transactions, only to find that ordered goods are never delivered.
Tested Products
Test Procedure
AV-Comparatives verified the effectiveness of cybersecurity products in detecting fake online shops. A false-alarm test with 100 popular legitimate shopping websites was also conducted. The test set consisted of 500 fake-shop test cases. The test was performed from October 1st to October 7th, 2025.
From the collected pool of fake-shop URLs, 500 that were still online at the time of testing were randomly selected. All tests were carried out on a fully patched Microsoft Windows 11 (64-bit) system using Google Chrome as the default browser.
To be certified by AV-Comparatives for Fake-Shop Detection, a product must detect at least 80% of the fake-shop URLs used in the test without causing any false alarms with legitimate shopping sites. Only a few products on the market currently aim to warn users against fraudulent e-commerce websites, and recognizing such scams remains technically challenging. Therefore, while the certification threshold may appear modest, achieving it is not easy, and only a small number of products are presently able to meet this standard.
Product Reviews
We have included a short feature review of the product in this report, so that users have an idea of what the product is like to use and what other features it has.
F-Secure Internet Security includes technologies intended to warn users when visiting fraudulent online stores. The feature analyses website characteristics and URLs to identify known or suspicious patterns commonly associated with fake online shops.
When a potential fake shop is detected, the website is blocked, and a warning message is displayed instead of the blocked website. There the user is warned about the threats of fake online store and recommending that the user not visit the site. Additionally, the user can report a false positive and create an exception for the site. In some cases a pop-up warning the user was displayed.
Example screenshots of detection messages are shown below.
This feature was directly relevant for the Fake Shop Detection Certification test, as it determines whether the product can effectively recognize fraudulent e-commerce websites.
Award levels reached in this Special Test
F-Secure received certification for its fake shop detection capabilities, highlighting its commitment to user safety and security. This certification is a testament to the product’s effectiveness in safeguarding users from financial loss by online scams.

| F-Secure | APPROVED |
Understanding Fake Online Shops and Other Scams
Scammers often impersonate legitimate brands by stealing logos, copying website designs, and creating domain names with minor misspellings. They manipulate reviews, use phishing emails, and run fake ads to lure victims. Search engine manipulation, fake trust badges, and deceptive customer service are common tactics to create a sense of legitimacy. Recent research by SRLabs revealed that these criminals frequently exploit previously expired domains with good Google reputations, enabling fraudulent websites to appear credible, trustworthy, and rank prominently in search engine results.
Examples of fake shops include websites based in China selling luxury goods at huge discounts, Eastern European sites offering cheap electronics, and Southeast Asian sites selling poor-quality clothing. Some shops even sell harmful health products from countries with lax regulations. However, not all suspicious signs guarantee a site is fake. Reasonable prices, customs delays, and foreign-based shops do not always indicate a scam. Even secure websites (HTTPS) can be fraudulent. Additionally, fake goods can sometimes be sold on major platforms like Amazon and eBay.
To minimise the risk of falling victim to these scams, we have compiled a list of some best practices for identifying fake shops:
- Be careful when shopping online on your mobile phone, as it is easier to accidentally click on fraudulent popups or ads.
- Verify website legitimacy by checking for misspelt domain names, valid SSL certificates (indicated by “https://” and padlock symbol), and domain registration information (https://who.is/, https://lookup.icann.org/).
- Look for contact information, such as a physical address, phone number, and email address.
- Review the website for grammatical errors and unclear policies on returns, refunds, and shipping.
- Search for reviews or scams associated with the retailer’s brand on various sites and social media.
- Report suspicious websites to relevant authorities.
- Avoid making payments outside the online shop and be cautious of foreign bank accounts (IBAN).
- Avoid advance payments.
- Ensure that you receive an order confirmation and invoice after purchase.
- Watch for hidden subscription traps in free offers.
- Monitor your financial accounts and report any suspicious activity to your bank or credit card company immediately.
- Use trusted and up-to-date security products with high detection rates.
- Avoid purchases from foreign shops, especially if legal action or refunds may be difficult.
- Keep up with the latest news on online scams and fraud tactics.
- Educate and share experience with your friends and family to help them stay safe online.
Copyright and Disclaimer
This publication is Copyright © 2025 by AV-Comparatives ®. Any use of the results, etc. in whole or in part, is ONLY permitted after the explicit written agreement of the management board of AV-Comparatives prior to any publication. AV-Comparatives and its testers cannot be held liable for any damage or loss, which might occur as result of, or in connection with, the use of the information provided in this paper. We take every possible care to ensure the correctness of the basic data, but a liability for the correctness of the test results cannot be taken by any representative of AV-Comparatives. We do not give any guarantee of the correctness, completeness, or suitability for a specific purpose of any of the information/content provided at any given time. No one else involved in creating, producing or delivering test results shall be liable for any indirect, special or consequential damage, or loss of profits, arising out of, or related to, the use or inability to use, the services provided by the website, test documents or any related data.
For more information about AV-Comparatives and the testing methodologies, please visit our website.
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(November 2025)









