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StarknetAVS

StarknetAVS

AML Transaction Compliance AVS

Created on 8th December 2024

StarknetAVS

StarknetAVS

AML Transaction Compliance AVS

The problem StarknetAVS solves

DeFi platforms are increasingly targeted for money laundering and illicit activities due to their pseudonymous and decentralized nature. Traditional AML compliance relies on centralized intermediaries, which can be points of corruption and failure. Our AML Transaction Compliance AVS addresses these challenges by providing a decentralized, trust-minimized solution for monitoring and flagging suspicious transactions. By eliminating intermediaries, the AVS prevents corruption and ensures that compliance checks are transparent, auditable, and resilient against manipulation. This enhances the security and integrity of DeFi protocols, fosters regulatory compliance, and builds trust among users and stakeholders.

Challenges we ran into

Integration with EigenLayer:
EigenLayer’s evolving interfaces and limited documentation made it difficult to seamlessly integrate our AVS contracts. We often encountered unexpected behaviors and had to dive deep into EigenLayer’s source code to understand underlying mechanisms.

Operator Coordination Logic:
Designing a reliable consensus mechanism among multiple operators was complex. Ensuring that at least two out of three operators agree on flagging required meticulous contract design to prevent edge cases and ensure security.

Additional Features

Multi-Operator Consensus Mechanism:
Implemented a consensus protocol requiring at least two out of three operators to agree on flagging a transaction, enhancing the reliability and security of compliance checks.

Mock Data Generation Script:
Developed a TypeScript-based script to simulate transaction data, enabling comprehensive testing and demonstration of the AVS’s capabilities without relying on live data feeds.

Enhanced Frontend Integration:
Integrated the AVS with a React-based dashboard, providing real-time visualization of flagged transactions and compliance metrics, thereby improving usability and stakeholder transparency.

Tracks Applied (2)

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