Authors: Tyler Thomas (University of New Haven (UNHcFREG)), Mathew Piscitelli (University of New Haven (UNHcFREG)), Ilya Shavrov (University of New Haven (UNHcFREG)), and Ibrahim Baggili (University of New Haven (UNHcFREG))
DFRWS USA 2020
We present Memory FORESHADOW: Memory FOREnSics of HArDware cryptOcurrency Wallets. To the best of our knowledge, this is the primary account of cryptocurrency hardware wallet client memory forensics. Our exploratory analysis revealed forensically relevant data in memory including transaction history, extended public keys, passphrases, and unique device identifiers. Data extracted with FORESHADOW can be used to associate a hardware wallet with a computer and allow an observer to deanonymize all past and future transactions due to hierarchical deterministic wallet address derivation. Additionally, our novel visualization framework enabled us to measure both the persistence and integrity of artifacts produced by the Ledger and Trezor hardware wallet clients. The framework can be generalized for use in future memory forensics work.