  Current methods to prevent crypto asset fraud are based on the analysis of
transaction graphs within blockchain networks. While effective for identifying
transaction patterns indicative of fraud, it does not capture the semantics of
transactions and is constrained to blockchain data. Consequently, preventive
methods based on transaction graphs are inherently limited. In response to
these limitations, we propose the Kosmosis approach, which aims to
incrementally construct a knowledge graph as new blockchain and social media
data become available. During construction, it aims to extract the semantics of
transactions and connect blockchain addresses to their real-world entities by
fusing blockchain and social media data in a knowledge graph. This enables
novel preventive methods against rug pulls as a form of crypto asset fraud. To
demonstrate the effectiveness and practical applicability of the Kosmosis
approach, we examine a series of real-world rug pulls from 2021. Through this
case, we illustrate how Kosmosis can aid in identifying and preventing such
fraudulent activities by leveraging the insights from the constructed knowledge
graph.
