Program Analysis - Building Secure Contracts (original) (raw)

Building Secure Contracts

Program Analysis

We will use three distinctive testing and program analysis techniques:

• Static analysis with Slither. All the paths of the program are approximated and analyzed simultaneously through different program presentations (e.g., control-flow-graph).
• Fuzzing with Echidna. The code is executed with a pseudo-random generation of transactions. The fuzzer attempts to find a sequence of transactions that violates a given property.
• Symbolic execution with Manticore. This formal verification technique translates each execution path into a mathematical formula on which constraints can be checked.

Each technique has its advantages and pitfalls, making them useful in specific cases:

* if all paths are explored without timeout

Slither analyzes contracts within seconds. However, static analysis might lead to false alarms and is less suitable for complex checks (e.g., arithmetic checks). Run Slither via the CLI for push-button access to built-in detectors or via the API for user-defined checks.

Echidna needs to run for several minutes and will only produce true positives. Echidna checks user-provided security properties written in Solidity. It might miss bugs since it is based on random exploration.

Manticore performs the "heaviest weight" analysis. Like Echidna, Manticore verifies user-provided properties. It will need more time to run, but it can prove the validity of a property and will not report false alarms.

Suggested Workflow

Start with Slither's built-in detectors to ensure that no simple bugs are present now or will be introduced later. Use Slither to check properties related to inheritance, variable dependencies, and structural issues. As the codebase grows, use Echidna to test more complex properties of the state machine. Revisit Slither to develop custom checks for protections unavailable from Solidity, like protecting against a function being overridden. Finally, use Manticore to perform targeted verification of critical security properties, e.g., arithmetic operations.

• Use Slither's CLI to catch common issues
• Use Echidna to test high-level security properties of your contract
• Use Slither to write custom static checks
• Use Manticore for in-depth assurance of critical security properties

A note on unit tests: Unit tests are necessary for building high-quality software. However, these techniques are not best suited for finding security flaws. They typically test positive behaviors of code (i.e., the code works as expected in normal contexts), while security flaws tend to reside in edge cases that developers did not consider. In our study of dozens of smart contract security reviews, unit test coverage had no effect on the number or severity of security flaws we found in our client's code.

Determining Security Properties

To effectively test and verify your code, you must identify the areas that need attention. As your resources spent on security are limited, scoping the weak or high-value parts of your codebase is important to optimize your effort. Threat modeling can help. Consider reviewing:

• Rapid Risk Assessments (our preferred approach when time is short)
• Guide to Data-Centric System Threat Modeling (aka NIST 800-154)
• Shostack thread modeling
• STRIDE / DREAD
• PASTA
• Use of Assertions

Components

Knowing what you want to check also helps you select the right tool.

The broad areas frequently relevant for smart contracts include:

• State machine. Most contracts can be represented as a state machine. Consider checking that (1) no invalid state can be reached, (2) if a state is valid, then it can be reached, and (3) no state traps the contract.
  • Echidna and Manticore are the tools to favor for testing state-machine specifications.
• Access controls. If your system has privileged users (e.g., an owner, controllers, ...), you must ensure that (1) each user can only perform the authorized actions and (2) no user can block actions from a more privileged user.
  • Slither, Echidna, and Manticore can check for correct access controls. For example, Slither can check that only whitelisted functions lack the onlyOwner modifier. Echidna and Manticore are useful for more complex access control, such as permission being given only if the contract reaches a specific state.
• Arithmetic operations. Checking the soundness of arithmetic operations is critical. Using SafeMath everywhere is a good step to prevent overflow/underflow, but you must still consider other arithmetic flaws, including rounding issues and flaws that trap the contract.
  • Manticore is the best choice here. Echidna can be used if the arithmetic is out-of-scope of the SMT solver.
• Inheritance correctness. Solidity contracts rely heavily on multiple inheritance. Mistakes like a shadowing function missing a super call and misinterpreted c3 linearization order can easily be introduced.
  • Slither is the tool for detecting these issues.
• External interactions. Contracts interact with each other, and some external contracts should not be trusted. For example, if your contract relies on external oracles, will it remain secure if half the available oracles are compromised?
  • Manticore and Echidna are the best choices for testing external interactions with your contracts. Manticore has a built-in mechanism to stub external contracts.
• Standard conformance. Ethereum standards (e.g., ERC20) have a history of design flaws. Be aware of the limitations of the standard you are building on.
  • Slither, Echidna, and Manticore will help you detect deviations from a given standard.

Tool Selection Cheatsheet

Other areas will need to be checked depending on your goals, but these coarse-grained areas of focus are a good start for any smart contract system.

Our public audits contain examples of verified or tested properties. Consider reading the Automated Testing and Verification sections of the following reports to review real-world security properties:

• 0x
• Balancer