The emerging Blockchain technology is designed to provide decentralized computing, and information can be stored and exchanged in an immutable and transparent manner over the blockchain network. The information is stored in the form of smart contracts over the nodes, these smart contracts are self-enforcing software pieces that execute transactions over the hosted blockchain. Using blockchain-based smart contracts is a niche concept but writing a safe and trustworthy smart contract before deploying it on the node i.s very challenging. Blockchain smart contracts could contain code security vulnerabilities that can become the loophole for financial damages by cyber attacks
Before adopting smart contracts, developers and security auditors must examine them to guarantee that they are entirely secure because even one security flaw could result in the loss of millions. Several analysis tools have been developed to design safe and secure smart contracts and investigate the security flaws in smart contracts. However, despite the abundance of bug-finding tools, there is no organized method to assess the suggested tools and determine their efficacy. In this blog post, learn about the various methods available for automated analysis and the comparative performance of some of the most popular tools.
Several code analysis techniques and tools have been developed to find security bugs in smart contracts. The study of codes has two methods - Static analysis and Dynamic Analysis. Analyzing codes while a program is operating is known as dynamic code analysis, and on the other hand, analyzing the code when a program is not executing is static analysis.
Static analysis is done without running the code in its intended environment. Before execution, a smart contract's source code is examined using static analysis. This entails that the smart contract code can be tested without executing it. Static analyzers can help comply with best practices and find common vulnerabilities in Ethereum smart contracts.
Dynamic analysis techniques must run the smart contract in a runtime environment to find bugs in your code. Dynamic code analyzers track how contracts behave as they are being executed and produce a thorough report of any vulnerabilities or property violations.
Contract testing methods that use dynamic analysis include fuzzing. Fuzz testing involves feeding your smart contract with data, then watching how the contract responds. Some input values might result in resource leaks, crashes, or worse, unintended code execution when sent to a smart contract. Such issues are foreseen by fuzzing efforts, allowing you to close the vulnerability.
Since the creation of smart contracts, numerous open-source analytical tools have been developed. Static analysis tools make up the majority of created open-source technologies. These tools are available for free use, but they have various limitations, and there is not a single tool that can give comprehensive security coverage to smart contract
For reviewing smart contract code properly, developers require both static and dynamic analyzers. One of the most popular open-source tools, Slither, uses tracking techniques and data flow analysis to find code weaknesses. The open-source version of this program can identify about 20 issues, including re-entrancy, suicidal contracts, locked ether, and arbitrary ether sending. Another popular open source tool is Mythril, which analyses smart contracts built on the Ethereum blockchain and other blockchains, including Hedera, Quorum Vechain, Roostock, Tron, and any other blockchain that is EVM compatible. It scans the byte code of the Ethereum virtual machine. There are more tools available, but the depth of identifying vulnerabilities varies in each tool, some can only do static analysis, and some are only useful for dynamic code analysis. Some of these tools can not detect bytecode or smart contract addresses as they can not work in a dynamic environment. Some of these tools are required to write code lines into the tool for detecting vulnerabilities, which makes it a tedious task to detect and remediate the vulnerabilities. The execution time for identification and remediation is very high in many cases.
Even while developers have access to various open source tools, there is no assurance that these tools will find all vulnerabilities. Oyente focuses on detecting only re-entrancy problems that are based on the use of call.value, while Mythrill, Securify, and Manticore could not detect many cases of injected reentrancy, timestamp dependency, unhandled exceptions, or integer overflow/underflow. Some modern tools, like Slither, consider identifying send-and-transfer-based re-entrancy problems with limited gas. But sending and transferring do not shield users against re-entry vulnerabilities if gas prices change. Some tools are also prolonged regarding the time it takes to analyze contracts. Moreover, most Ethereum smart contract analysis tools use the static analysis methodology. However, both static and dynamic analyses are required to identify or check all the vulnerabilities in a smart contract.
Blockchain technology is evolving quickly, and so are security challenges for decentralized blockchain applications. Consequently, many new features and functionalities are getting introduced to the Ethereum blockchain, and there are chances that new vulnerabilities will evolve. Therefore, it might result in the creation of novel and sophisticated analysis tools for identifying these weaknesses.
The Vulnerability Management tool from BlockChainSentry - BCS smart contract security finds more than 120 types of vulnerabilities in your smart contracts at every level, including development, deployment, and version control. Some of the highlights of our security tool include
The vulnerability scan process is fully automated. Users just have to upload the smart contracts into the tool to get scan results with detailed remedial steps for each detected vulnerability. You can mail to request a live demo of the application at - email@example.com