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Many modern smart contract research methods do not need source code and can search the entire public blockchain for potentially insecure contracts.
FREMONT, CA: Traditional methods for safe app creation have not yet been applied to blockchain-centric software. Highly distributed and trustless systems pose entirely new challenges and involve new ways of thinking about program vulnerabilities.
The following software security practices are likely to be part of a smart contract growth cycle:
Secure Code Frameworks
Developers need audited and proven frameworks to build a stable code from standard patterns. These can include but are not limited to secure math procedures, verification and authorization, or monetary transaction management.
Dynamic Code Analysis Tools
The Maian tool—a tool for automatic detection of buggy Ethereum smart contracts of three different types: suicidal, prodigal, and greedy—used by university researchers to classify insecure intelligent contracts is an example of hybrid static analysis with concrete execution, which finds dynamic vulnerabilities that would be ignored by conventional static analysis methods lacking symbolic execution. Many modern smart contract research methods do not need source code and can search the entire public blockchain for potentially insecure contracts.
Secure Governance and Policy Creation
Historically, blockchain contracts have remained static, and consumers have put their confidence in the contract code's integrity. Today, no deal is exempt from hacking and glitches, so contract providers need to establish customer and asset security policies. Smart contract creators will need to consider guidelines for patching live contracts and strategies for managing incident response.
Static Code Analysis and Code Linting
Tools today can recognize typical code smells and remove low-hanging fruit bugs in the solidity code. In the future, these methods must be framework-aware and contain a more safety-related collection of guidelines.
For non-trivial systems deployed on blockchain technology, enterprises need a threat modeling framework to routinely classify all system components, possible threat actors, and controls offered by the platform. Security departments will then draw decisions about the infrastructure's overall security and add new security steps to prepare for perceived risks.
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