Abstract: A method and apparatus that receive blockchain transaction data from a blockchain ledger to a transaction database, receive intelligence labels from a blockchain ecosystem intelligence database, select a blockchain transaction flow comprising blockchain transactions associated with a digital account source address, digital account intermediate addresses, a digital account destination address, and intermediate transactions, receive input trace parameters, where the input trace parameters include at least one of an objective directional setting, a tracing constraint, and a transaction filter, the transaction filter based on the transaction timestamps and the digital assets transferred, apply the intelligence labels to the digital account source address, the digital account intermediate addresses, and the digital account destination address, apply an artificial intelligence graph search algorithm to the blockchain transaction flow based on the input trace parameters, and generate a report including tracing desti

Abstract: A computing apparatus, a non-transitory computer-readable storage medium, and a method of offering blockchain transactions of non-fungible tokens (NFTs) including providing a digital storefront platform for the NFTs with a mint module, configured to create and mint NFTs on blockchains, and a trade module configured to transact with the minted NFTs. A key cycler is configured to allow parallel transactions with blockchains, payment processors, the mint module, and the trade module. The key cycler includes a plurality of private keys on a web-based key management service (KMS). The key cycler is configured to facilitate transaction payments using fiat currency or cryptocurrency. Anti-money laundering (AML) and counter-terrorism financing (CTF) screening capabilities may be incorporated into the disclosed solution.

Abstract: A continuous vulnerability management system for identifying, analyzing, protecting, and reporting on digital assets is disclosed. The continuous vulnerability management system comprises a sandbox engine configured to scan digital assets for vulnerabilities, including a static analysis unit for static code scanning, a dynamic analysis unit for analyzing compiled code, and a statistical analysis unit for processing a risk score and generating an audit report. A knowledge base is also disclosed, including a knowledge base engine configured to acquire information related to new vulnerabilities to digital assets. A risk scoring engine is configured to analyze sandbox engine outcomes and assign a risk score to each vulnerable asset. A security control system is configured to act on an identified vulnerable asset based on the risk score assigned to the identified vulnerable asset.

Abstract: A method involves receiving digital on blockchain information and digital off blockchain information. The digital data from the digital on blockchain information and the digital off blockchain information is extracted. The entity knowledge base engine contextualizes the relationships based on the digital data and the digital off blockchain information and the digital on blockchain information. The risk classification engine analyzes the digital data and transforms the digital data to an identified behavior category. The risk scoring regression engine analyzes the classified risk data and assigns a risk score to each classified risk data. The risk policy engine analyzes the classified risk data and determines if any deviations from rules or standards have or will occur. The security control system takes an action on the digital on blockchain information and digital off blockchain information based on the assigned risk score and any deviations from rules or standards.

Abstract: A method and apparatus that receive blockchain transaction data from a blockchain ledger to a transaction database, receive intelligence labels from a blockchain ecosystem intelligence database, select a blockchain transaction flow comprising blockchain transactions associated with a digital account source address, digital account intermediate addresses, a digital account destination address, and intermediate transactions, receive input trace parameters, where the input trace parameters include at least one of an objective directional setting, a tracing constraint, and a transaction filter, the transaction filter based on the transaction timestamps and the digital assets transferred, apply the intelligence labels to the digital account source address, the digital account intermediate addresses, and the digital account destination address, apply an artificial intelligence graph search algorithm to the blockchain transaction flow based on the input trace parameters, and generate a report including tracing desti

Abstract: A method involves receiving digital on blockchain information and digital off blockchain information. The digital data from the digital on blockchain information and the digital off blockchain information is extracted. The entity knowledge base engine contextualizes the relationships based on the digital data and the digital off blockchain information and the digital on blockchain information. The risk classification engine analyzes the digital data and transforms the digital data to an identified behavior category. The risk scoring regression engine analyzes the classified risk data and assigns a risk score to each classified risk data. The risk policy engine analyzes the classified risk data and determines if any deviations from rules or standards have or will occur. The security control system takes an action on the digital on blockchain information and digital off blockchain information based on the assigned risk score and any deviations from rules or standards.

Abstract: A continuous vulnerability management system for identifying, analyzing, protecting, and reporting on digital assets is disclosed. The continuous vulnerability management system comprises a sandbox engine configured to scan digital assets for vulnerabilities, including a static analysis unit for static code scanning, a dynamic analysis unit for analyzing compiled code, and a statistical analysis unit for processing a risk score and generating an audit report. A knowledge base is also disclosed, including a knowledge base engine configured to acquire information related to new vulnerabilities to digital assets. A risk scoring engine is configured to analyze sandbox engine outcomes and assign a risk score to each vulnerable asset. A security control system is configured to act on an identified vulnerable asset based on the risk score assigned to the identified vulnerable asset.