An Analysis of Opioid Trafficking on the Surface Web

Abstract

Turns out, your everyday search engine might be hiding more than comedic videos and cooking blogs. While opioid trafficking is often associated with the dark web, recent studies suggest that illegal drug markets are creeping into the more visible corners of the internet. This research set out to investigate whether opioid trafficking can be identified on the surface web by combining a custom-built web crawler with a Large Language Model (LLM) to analyze web page text. On an initial test crawl of 75 webpages, the system flagged 17 as high-confidence cases of trafficking, most involving semi-synthetic opioids like Hydrocodone and Oxycodone. Strikingly, every flagged instance was attributed to sellers, not buyers, highlighting the commercial nature of these listings. These findings suggest that the surface web is not only being used for illicit activity, but that automated tools can meaningfully detect and categorize this behavior.