The development of cryptocurrency, blockchain, and digital finance has given rise to digital asset grants as a new form of wealth transfer that can potentially be exploited for money laundering (ML) originating from tax crimes. Their pseudonymous, cross-jurisdictional, and decentralized nature creates obstacles in identification, oversight, and legal proof. This study aims to identify the characteristics of suspicious digital asset grants, analyze the application of Red Flag Theory in risk detection, and examine the role of Digital Forensic Investigation in proving their connection to tax crimes as a predicate offense. The study employs a normative juridical method using statutory, conceptual, and literature review approaches. Analysis is conducted through the integration of Red Flag Theory, blockchain forensics, wallet attribution analysis, beneficial ownership investigation, digital-tax evidence correlation, and fund flow reconstruction. Results indicate that high-risk indicators include anonymous donors, unidentifiable beneficial owners, blockchain layering, cross-chain transactions, use of privacy technologies, and discrepancies between grant values and the recipient's economic profile. This study produces a Digital Asset Grant Red Flag Model, a Risk Matrix, an Early Warning System, and an integrated model of Red Flag Theory with Digital Forensic Investigation as a systematic framework for detecting, investigating, and verifying digital asset grants used as instruments of money laundering originating from tax crimes.
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