Case Study:

Drug Trade Detection Using Open-Source Intelligence (OSINT)

The opioid epidemic is devastating the lives of millions of people. Agencies across the globe are trying to stop the flow of illicit opioids at the source and intercept counterfeit narcotics before they reach local communities. Especially fentanyl, a synthetic opioid 50 to 100 times more potent than morphine, is in high demand, making it lucrative for crime syndicates to produce and distribute. Especially illicit fentanyl, a synthetic opioid found in most fake pills, is the primary driver of overdose deaths.

A law enforcement agency involved in the war on drugs was investigating the steep rise in overdose deaths in a metropolitan area. It suspected a specific dealer of being behind it, based on information that was collected during previous investigations. Since most criminal activities are conducted online, the agency needed a powerful digital tool to assist in its online investigations. It opted for an AI-powered tool to quickly and efficiently scout all layers of the web to find clues.


After entering specific keywords and search terms, the tool detected several statements online about the purchase of fentanyl and other contraband opioids. This gave investigators their first clue. By collecting and analyzing vast amounts of OSINT data, the tool was able to identify the author behind the statements. Since all internet users, including the identified individual, leave digital footprints, the tool was able to map his connections, which turned out to be a global network of producers, distributors, dealers, and sellers. Using the AI tool for entities analysis, the system filtered out irrelevant data and left the investigators with a clear view of the whole drug trafficking chain. The dealer who was originally identified bought his merchandise from an importer who also sold to other dealers in neighboring states.

The AI-powered WEBINT platform of Cobwebs Technologies is ideally suited to investigate any sort of crime syndicated or other network-based criminal activity. The tool’s qualitative network analysis cross-analyzed the identified members of this drugs network and presented the results in a graph showing all the shared connections between them. Using the smart filtering option, the investigators were also able to find hidden members, which provided them with quality leads.

To get insights into the location of the drug trade, the tool collected data from location-based data sources that were publicly available on the surface, deep, and dark web. These collected and analyzed geospatial data were used to identify patterns and trends. It allowed investigators to not only map all the players involved in the drugs operation, but also the flow of drugs and payments across the globe. This was especially important in this case, where knowing the exact location of a dealer or a drug shipment in real-time can be a matter of life or death.

In this case, law enforcement was able to take down a significant drug operation that was probably involved in the overdose deaths of too many people.

In general, law enforcement agencies use the platform to detect patterns and quantify events, risks, and potential consequences, while investigators and decision-makers can follow these leads to stop criminal activities such as the drugs trade.

They can perform location-based investigations from any device and a wide range of sources, gaining insight into the locations associated with relevant threat actors such as dealers. This enables the detection of illegal activities, analysis of relevant threat actors, uncovering hidden connections, and gaining situational awareness to make informed decisions.

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