AI Digital Assets Legal Specialist
An AI Digital Assets Legal Specialist navigates the complex intersection of artificial intelligence, intellectual property, and di…
Skill Guide
The discipline of writing, testing, deploying, and systematically auditing self-executing code on blockchain platforms to ensure security, correctness, and economic soundness.
Scenario
Create and deploy a token with custom supply, ownership, and pausable functionality to a testnet (Goerli, Sepolia).
Scenario
You are given a naive staking contract that allows users to deposit an ERC-20 token and earn interest. Identify all security and logic flaws.
Scenario
Analyze a live, simplified lending protocol (e.g., a fork of Aave v2). Model a scenario where a price oracle is manipulated via a flash loan to extract value.
Foundry is the industry standard for high-performance testing (fuzzing, symbolic execution) and development in Solidity. Hardhat offers rich plugin ecosystem and debugging. OpenZeppelin provides battle-tested, secure base contracts to build upon.
Slither provides immediate vulnerability detection and code metrics. Mythril and Echidna perform deeper, automated vulnerability discovery. Tenderly is essential for debugging and simulating complex mainnet transaction flows.
Certora and Halmos allow you to mathematically prove contract invariants. Platforms like Code4rena provide real-world audit experience and a way to benchmark skills against peers.
Answer Strategy
The strategy is to demonstrate a systematic, layered approach. Start with high-level architecture review and documentation check. Then proceed to static analysis, manual line-by-line review focusing on critical areas (access control, external calls, state management), and finally dynamic testing (unit tests, fuzzing, invariant testing). Emphasize the importance of understanding the economic model and threat modeling before diving into code.
Answer Strategy
This tests practical experience and depth of understanding. The candidate should explain the vulnerability's root cause (e.g., a subtle logic error in a rounding function during a multi-step operation), why it wasn't caught by standard tools, and the process of writing a proof-of-concept (PoC) to confirm it on a fork.
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