Identifying Invariants in Smart Contracts

Identifying invariants is a crucial step in finding security vulnerabilities. This applies even more so to Stateful Fuzzing as they form the basis of the tests that will be used to validate the contract’s behavior under various conditions. Here are some strategies for identifying invariants in smart contracts, which are essential for creating effective stateful fuzz tests.

Understanding the Nature of Invariants

Invariants in smart contracts are assertions about the contract’s state that should remain true from the contract’s initialization to its termination. These can range from simple properties like non-negativity of balances to complex conditions ensuring the contract’s logic and business rules are upheld across all possible state transitions.

Strategies for Identifying Invariants

1. Review the Contract’s Specification and Documentation

The first step in identifying invariants is to thoroughly review the smart contract’s specification, requirements, and documentation. This includes understanding the intended functionality, the rules governing state changes, and any constraints or conditions that must always be met. The documentation often explicitly states certain invariants, such as the conservation of total token supply in a token contract.

2. Analyze the Contract’s State Variables

Examine the contract’s state variables to identify potential invariants. For example, in a smart contract managing an escrow service, an invariant might be that the sum of all escrowed amounts must equal the contract’s total balance. By understanding the role and intended behavior of each state variable, you can deduce conditions that should remain constant.

3. Understand the Contract’s Business Logic

Deeply understanding the business logic and rules the contract implements is crucial. For instance, in an Automated Market Maker (AMM) contract, the “constant product formula” is an invariant that must hold after every trade, liquidity addition, or removal. Identifying such critical business rules can guide you to define corresponding invariants. Often times this information is in the documentation but it can also be located in code comments where the business logic is implemented.

4. Consider the Contract’s Security Properties

Focus on security properties such as authorization, authentication, and access control. Invariants here might include conditions like “only the owner can withdraw funds” or “balances cannot decrease without a corresponding transfer or approval action.” These security-focused invariants are vital for preventing unauthorized access and ensuring the contract’s integrity.

5. Use Existing Tools and Frameworks

Leverage tools and frameworks designed for smart contract analysis, such as Slither or Mythril, which can help identify potential invariants by analyzing the contract’s code for common patterns, vulnerabilities, and logical conditions that must be preserved.

Examples of Common Invariants in Smart Contracts

• Conservation of Value: In some case the total value (e.g., cryptocurrency or tokens) controlled by a contract must remain constant, except when explicitly changed by defined transactions.
• Ownership and Access Control: Certain actions can only be performed by specific roles or addresses.
• State Consistency: The contract’s state must remain consistent and valid after every transaction. For example, a lending contract must not allow a loan’s outstanding amount to be negative.
• Liquidity Invariants: In some AMM contracts, the product of the reserves (e.g., reserveTokenA * reserveTokenB) must remain constant after swaps, excluding fees.

These are just a few examples of invariants that can be identified in smart contracts. The specific invariants for a given contract will depend on its functionality, business logic, and security requirements.

Conclusion

Identifying invariants is a critical yet nuanced part of developing secure smart contracts. By thoroughly understanding the contract’s specifications, state variables, business logic, and security properties, developers can pinpoint the conditions that must always hold true. Implementing stateful fuzz tests based on these invariants allows for the rigorous verification of the contract’s correctness and security, ensuring that it behaves as expected under all circumstances.