Counterfeit activity has quickly evolved far beyond individuals publishing fake listings or selling imitation products. Today, organised networks use legitimate-looking online storefronts, social media marketplaces, and global supply chains to exploit brand equity and mislead consumers.
Counterfeit networks inflict significant financial losses while also eroding customer trust and market confidence. The challenge for businesses is no longer identifying isolated infringements, but understanding the networks that enable them.
Open Source Intelligence (OSINT) is the targeted collection and analysis of publicly available or licensable data. It can help companies expose these networks and crucially, unmask the real-world identities behind counterfeit goods. The latter is especially vital. If organisations can pass good, evidenced intelligence to law enforcement about the people behind counterfeit goods, it is far more likely they will act on it.
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Why counterfeiters now move faster than manual investigations
The internet facilitates the sale of vast volumes of counterfeit goods. This makes safeguarding brand reputation an incredibly resource-intensive task without the right tools. The majority of bad actors behind counterfeit sales conceal their identities and the sheer scale of the problem gives investigators l*********** to spend on each case. Indeed, the size of the task can often overwhelm the capabilities of corporate intelligence functions.
Concurrently, counterfeit networks now operate with the efficiency of legitimate digital businesses. The use of e-commerce platforms and social media marketplaces have already provided digital threat actors with a highly effective way to sell fake goods. Now, AI-driven automation is empowering them to scale quickly and with greater sophistication. Generative AI models, for example, enable the rapid creation of convincing storefronts, product imagery and customer interactions, thereby accelerating the pace of brand abuse.
Yet the internet and AI are highly advantageous for investigators too. OSINT is a powerful tool for any brand protection investigation; it can help investigators to glean invaluable insights into the individuals and entities behind counterfeit production. But the large swathes of data found across many platforms are nearly impossible to manage manually and make connections hard to spot.
That’s why the use of OSINT technology and AI has become indispensable for matching the speed, skill and scale of bad actors. Responding to human inputs, OSINT tools can search and collate large volumes of disparate data into a digestible format for investigators. Investigators can then apply their judgement and critical thinking skills on this intelligence to uncover the real-world networks involved in counterfeit sales.
But how exactly does this work?
OSINT in practice: exposing counterfeit networks
Let’s say we’re investigating counterfeits of a Rolex watch. How could we get from an online image of the watch all the way to exposing the real-life digital sellers and entities behind it?
The first step would be to carry out a reverse image search. Using a specialist OSINT browser, we can scan the internet for similar or identical images to the ‘original’. It’s imperative we use a secure browser to protect our networks/devices and, crucially, ensure we don’t leave our own digital footprint – especially given so many goods are sold on the dark web, an environment riddled with security risks. The search results will then show us the website(s) an image is housed on.
In our case, one of the search results could be a suspicious e-commerce site, with the site name and product listing strongly suggesting the watch is a replica. Off the back of this information, we can use automation tools to access and visualise the website’s metadata: affiliated email addresses, phone numbers, publicly available social media profiles, and so on.
Analysing this data might reveal an email address associated with the vendor – valuable information. There are then a variety of automation tools we can use to analyse this address and see if any publicly viewable social media profiles are linked to it. Once we discover a relevant username, we can use it to search for any other online profiles affiliated with it.
Here, the process gives us the name of an individual warranting further investigation – and a name is a critical piece of information. We can use it to produce actionable intelligence from a wide range of data sources. Searching corporate records with this name, we find greater detail on the entities and people involved in selling counterfeit goods through the vendor. We also discover the person is in fact also the director of a connected parent company, implicating this company in the illicit sales of fake Rolex watches.
OSINT tools can then display information like corporate networks in a visual chart and show how data connects. Examining the corporate network associated with this company, we can then unmask other entities and people who might be involved. Suddenly, we’ve gone from an online image to a whole network of criminals connected to the sale of fake Rolex watches.
Revealing the hidden lifecycle of brand abuse
The hypothetical Rolex example is of course a specific incident. But viewing brand abuse as a lifecycle rather than a series of isolated incidents is fundamental to building a more effective intelligence gathering and sharing process. And ultimately, better intelligence leads to more successful enforcement.
Counterfeit activity leaves traces across website domains, social media and supply chain data that, when viewed in isolation, might appear insignificant. And with data spread across so many platforms, the lifecycle of brand abuse can remain hidden. Therefore, adopting the proactive use of OSINT can reveal the hidden extent of brand abuse taking place on an ongoing basis.
For example, continuous use of OSINT can help uncover how counterfeit goods move from online promotion to physical delivery. Patterns such as repeated domain registrations, shared social media account behaviour, and consistent supply routes can expose how operations scale or re-emerge after enforcement. Rather than isolated events, this paints a picture of how counterfeit networks operate on a wider scale.
Building defenses that match the threat
There have never been so many ways for a brand to sell their products. But digital marketplaces and AI are giving organised criminal networks themselves increasing capabilities to sell counterfeit products – products which represent a direct threat to a brand’s equity. To combat the threat effectively, organisations can’t simply investigate one-off counterfeit cases. They need to understand the networks behind them.
OSINT empowers investigators to connect digital footprints. With the smart use of OSINT technology and AI, investigative teams can map relationships between counterfeit vendors and shell entities that might otherwise fly under the radar. Most importantly, they can unmask the real-life identities behind illicit operations.
Catch more CIO Insights: Identity is the New Perimeter: The Rise of ITDR
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