The best smart contract analysis tools of 2025

An overview of current smart contract testing tools

Introduction

With the rapid development of blockchain and smart contract technologies, the problem of their security becomes critical. Statistics show that hundreds of millions of dollars are lost annually due to vulnerabilities in smart contracts.

Testing smart contracts has become an integral part of their development and auditing, especially for blockchain projects with high security requirements. There are many tools available to analyze smart contracts. Each of these tools has unique features that help ensure quality and security.

Previously, we conducted a comparative analysis of Mythril, Securify, and Slither, demonstrating their capabilities in finding vulnerabilities such as reentrancy attacks and arithmetic errors. We also described key attack scenarios and provided recommendations for avoiding vulnerabilities and restricting access to critical functions.

A few years have passed and the situation has changed. Now we see the following main challenges related to the security of smart contracts:

1. Difficulty in selecting testing tools due to their large number and different specifics.
2. Lack of systematized information about the capabilities and limitations of each tool.
3. The need for practical guidance on how to configure and use the tools.
4. The need to understand what types of vulnerabilities each tool detects.

Therefore, today we see the following tasks for ourselves:

1. To systematize information about the most relevant modern tools for testing smart contracts.
2. Provide top-priority practical recommendations on their use.
3. Help developers choose the best set of tools and methods for their projects.
4. Demonstrate the effectiveness of different tools using real-life examples.

In this article, we describe the best tools for analyzing smart contracts and share the experience of our auditing team that helps projects achieve a high level of security. This will allow developers and information security professionals to choose the best tools to improve the security of their projects and ensure effective smart contract auditing.

How we selected smart contract analysis tools

From a large number of smart contract auditing tools, we selected a limited list of state-of-the-art tools based on their popularity, flexibility, efficiency, and integration capabilities.

Popularity in the community

The selected tools have broad support in the blockchain developer community and are actively updated. The popularity of the tools among developers and smart contract security specialists, as well as active support from the community and developers of these tools, ensure regular updates and quick bug fixes. This makes the tools more reliable than before. In addition, support for examples, documentation, and plugins makes these tools more user-friendly.

1. Hardhat and Truffle are leading frameworks for developing on Ethereum that provide convenient tools for compiling, testing, and deploying contracts. The popularity of these frameworks ensures a rich ecosystem of plugins and support.
2. Slither and Mythril are known for their powerful capabilities for, respectively, static and dynamic analysis of smart contracts. Such capabilities make these tools indispensable for security auditing.

Flexibility

The tools on this list are suitable for a wide range of blockchain platforms, giving developers the flexibility they need.

1. Aderyn allows for custom analyzers, making it particularly useful for projects with high-security requirements.
2. Foundry supports multi-blockchain projects, enabling fast integration with different networks.
3. Ganache creates a private blockchain network for testing smart contracts, enabling transaction simulation without gas costs.
4. Tenderly enables realistic transaction simulation and debugging in real time. This makes it ideal for DeFi projects.

Efficiency in finding vulnerabilities

These tools provide a variety of approaches for security testing and are suitable for extremely complex tasks. Each tool is unique, contributing to the quality, accuracy, and reliability of testing. They help developers and auditors find logic errors, optimize code, and identify potential vulnerabilities.

1. Diligence Fuzzing by ConsenSys allows you to find hidden vulnerabilities using automated input generation and fuzzing. The tool integrates with Scribble, a smart contract testing tool, through runtime verification. This allows developers to define smart contract specifications for more accurate testing and identifying potential issues in the contract logic.
2. Echidna is a fuzzing-testing framework for smart contracts on Solidity that generates various inputs to detect anomalies in contract behavior, providing a high level of testing coverage and identifying hidden vulnerabilities.
3. Manticore is a binary analysis tool that allows you to run symbolic execution and explore different variants of algorithms, identifying potential vulnerabilities and bugs in smart contracts.
4. Medusa is a powerful fuzzing testing tool capable of running parallel tests, which greatly speeds up the bug detection process. Due to its ability to handle large code bases, Medusa is particularly effective in large teams or for large-scale projects.
5. Mythril is a tool for analyzing the security of EVM byte code. Mythril uses symbolic execution, SMT solving, and taint analysis to identify various vulnerabilities in smart contracts designed for Ethereum and other EVM-compatible blockchains.
6. Slither is a static code analyzer for smart contracts that not only automatically finds vulnerabilities, but also identifies opportunities for code optimization and visualizes the execution algorithm. This helps auditors better understand the structure of a smart contract.

Integration

Modern blockchain projects are actively using automation to ensure code security and quality.

1. Solhint is a Solidity code linter that provides automated validation against style and security standards. It is ideal for CI/CD processes.
2. Tenderly provides continuous contract monitoring, integrating with popular development tools such as Hardhat and Foundry.

Description of smart contract analysis tools

Here is a slightly more detailed description of the most relevant smart contract testing tools in alphabetical order.

Aderyn

Aderyn is a static Solidity smart contract analyzer based on Rust. The main goal of this tool is to help developers and security researchers identify vulnerabilities in the codebase. With its high speed and ability to create custom detectors, Aderyn can be easily integrated into development processes.

Key functions:

1. Vulnerability analysis of Solidity smart contracts.
2. Support for creating custom detectors for specific tasks.
3. Fast command line interface (CLI) for easy interaction.
4. Output results in Markdown and JSON formats.

Diligence Fuzzing

This tool from ConsenSys uses fuzzing to identify vulnerabilities in smart contracts. Diligence Fuzzing generates random inputs to test the resilience of contracts to unpredictable scenarios.

Key features:

1. Foundry and Scribble-based testing support.
2. Use of Harvey fuzzers to analyze EVM byte code.
3. Reporting identifying potential problems quickly.

Echidna

Echidna provides fuzzing-based testing of smart contracts. The tool verifies invariant preservation even under extreme input data.

Key functions:

1. Code-specific input data generation.
2. Reports on gas usage and test coverage.
3. Interactive interface for customizing fuzzing campaigns.

Foundry

Foundry is a feature-rich framework for developing and testing smart contracts. Its advantages include support for multi-blockchain projects and high-performance unit testing.

Key Features:

1. Solidity test support with automatic test feature discovery.
2. Property-based testing to verify common behavior.
3. Support for integration with other tools.

Ganache

Ganache is building a local private blockchain network to test smart contracts.

Key features:

1. Transaction simulation with block-level accuracy.
2. Forking the Ethereum core network for realistic tests.
3. Rapidly creating state snapshots and restoring them.

Case Study: In the Geisted project, the H-X Technologies team used Ganache to simulate real-world transactions. A vulnerability related to Unchecked CALL Return Values was discovered due to the use of an assembler for contract validation. This increased the likelihood of errors that could go undetected. Recommendations included avoiding assembly language and implementing more secure Solidity constructs. Detailed test results are in the Report on Security Assessment of ERC20, GMarketplace, and NFTCollection + GNFT.

Hardhat

Hardhat is a user-friendly framework for developers that supports debugging and test automation features.

Key features:

1. Testing using Mocha and Chai.
2. Additional features for debugging contracts.
3. Integration with modern deployment tools.

Manticore

Manticore provides symbolic execution to analyze all possible execution paths of a smart contract.

Key features:

1. Automatic creation of input data for testing.
2. Flexible Python API for advanced control.

Medusa

Medusa offers fuzzing with parallelized execution for faster vulnerability detection.

Key features:

1. Support for multi-threaded fuzzing.
2. Data coverage for advanced analysis.

Mythril

Mythril uses symbolic execution to detect a wide range of vulnerabilities such as reentrancy and number overflow.

Key features:

1. Bytecode analysis for EVM-compliant blockchains.
2. Reports on key vulnerabilities with high accuracy.

Slither

Slither performs static analysis of Solidity code to identify vulnerabilities with relatively low false positives.

Key features:

1. Automate audits with CI/CD.
2. Generating reports on efficiency improvements.

Case Study: While testing a project, we discovered an opportunity to optimize gas usage. The tool suggested that the variables CALLBACK_SUCCESS and PERMIT_TYPEHASH could be declared as constant. This would reduce the gas overhead by computing the values at compile time. The recommendations for this optimization were implemented. This improved the performance of the contract without impacting its functionality. Detailed results of the analysis are reported in the Report on Security Assessment of Milkomeda Smart Contracts for OccamX.

Solhint

Solhint helps maintain code style and basic security through integration with existing workflows. It is a Solidity code linting tool with the following features:

1. Customization of validation rules according to project requirements as well as support for common configurations.
2. Extending the functionality with plug-ins. This allows you to add new rules and integrations.
3. Integration with popular development environments such as Sublime Text, Atom, Vim, JetBrains IDEA and Visual Studio Code.
4. Efficient parsing and validation.

Tenderly

Tenderly allows you to simulate transactions in real-time to identify potential errors.

Key features:

1. Foundry and Hardhat integration.
2. Advanced debugging capabilities.

Truffle

Truffle offers an environment for full-cycle development, testing and deployment of smart contracts.

Key features:

1. Built-in compilation and migration tools.
2. Interactive console for working with contracts.

Case Study: The H-X team used Truffle to test the Geisted smart contracts project. We discovered a Reentrancy vulnerability in functions related to transaction and token processing. This vulnerability allowed attackers to make repeated function calls, changing the balance before the transaction was completed. The solution included implementing the Check-Effect-Interaction pattern. This ensured the secure execution of contracts. Detailed results of the analysis are set out in the Report on Security Assessment of ERC20, GMarketplace, and NFTCollection + GNFT.

The practical part — testing smart contracts

We tested 13 popular solutions using a repository with intentionally vulnerable smart contracts VulnerableContracts. This repository contains examples of contracts with typical vulnerabilities often encountered in real projects. Our goal was to test how tools identify typical vulnerabilities such as Reentrancy, unreliable random number generation, number overflow and incorrect arithmetic, and self-destruct vulnerability.

This testing allowed us to identify these issues, as well as formulate recommendations for applying the tools to real-world blockchain projects.

Below are the results of our testing of each tool in alphabetical order.

Aderyn

Let’s run a detailed contract analysis:

 aderyn path/VulnerableContracts/

Contract analysis with Aderyn identified 13 vulnerabilities of different risk levels.

Structure of the scan result

1. General information.

1.2 Tool.

1.3. Number of analyzed files.

1.4. Total number of lines of code (nSLOC).

1.5. Total number of detected problems.

2. Details of the analysis.

2.1 Files that were analyzed.

2.2 Number of vulnerabilities by category.

3. Problems of high criticality.
4. Low criticality problems.

Diligence Fuzzing

Similar in functionality to Echidna and Medusa, but differentiated by integration with the ConsenSys platform and extensive analysis capabilities.

How to get started with Diligence Fuzzing?

First, you need to install Diligence Fuzzing using Python3:

pip3 install diligence-fuzzing

The tool supports various development environments.  In our example, Truffle is used. You can choose at your discretion.

Before testing, you need to register on the official website and get the API key. Then export it to your system:

export FUZZ_API_KEY=KEY.

To activate the “smart mode” (SMART_MODE), which automatically analyzes the project, use:

export FUZZ_SMART_MODE=1

SMART_MODE provides automatic identification of contracts and simplifies configuration.

Before testing, you should compile and migrate your contracts to the local network:

truffle migrate --network development

After completing the preparatory steps, run the fuzz test using the command:

fuzz run

Test results

The test results are displayed in the web interface of the Diligence Fuzzing platform. As you can see from the example, the testing showed the following data:

1. Tests per second: 2593 – high performance allows you to quickly find possible problems.
2. Total code coverage: 75% – indirectly indicates the quality of the inspection.
3. Turnaround time: 2 minutes – even in a short period of time, significant progress has been made.
4. Residual risk: 0.0042% – the minimum residual risk that evaluates the tool’s efficiency.

The coverage graph demonstrates a gradual growth of the code coverage percentage during the test execution time. It testifies to relative stability and reliability of the analysis.

Echidna

The functionality of this tool is similar to Medusa, but Echidna offers a wider range of customization options for creating custom tests.

How do I get started with Echidna?

First, you need to install Echidna using brew:

brew install echidna

Echidna expects special functions to be defined in your smart contract that start with the prefix echidna_. These functions act as test cases to test various aspects of the contract.

Use the command to run the test by specifying the name of the smartcontract and the name of the contract class:

echidna smartcontract.sol --contract smartcontract smartcontract

Once run, Echidna provides detailed output showing the results of the testing. You can see a list of features that passed the test as well as those that failed. This information helps quickly identify and remediate potential vulnerabilities.

Foundry

Foundry is a tool for developers who are looking for a fast and accurate means of testing smart contracts written in Solidity. Its key advantage is that tests are written directly in Solidity, without the need to use intermediate languages (like Hardhat, for example). This allows developers to avoid additional transformations and work closer to the smart contract code.

How to get started with Foundry?

First, let’s run the Foundry installation command:

curl -L https://foundry.paradigm.xyz | bashfoundryup

Let’s execute the command to initialize a new project:

forge init name-project

As a result, the project structure will look like this:

Let’s move our smart contract to the src/ folder. In the test/ folder, create a file with tests for our contract. For example, for BadRandomness.sol, we have written tests for such functions:

• Successful addition of participants by the participate function.
• Correct selection of a random user pickRandomUser.
• Failure to call the participate function if 1 ETH is not transferred.

Let’s execute the contract compilation command:

forge build

If the compilation is successful, we will see the compiled files in the out/ folder.

To run the tests, let’s execute:

forge test

Test results

We tested the functionality of several smart contracts in a local Foundry environment. Here’s a summary of the results:

1. 11 positive test results:

• Successful deposit testing.
• Checking the prevention of withdrawals overbalance.
• Proper token management with buy and sell functions.
• The hidden access mechanism was successfully tested.
• Successfully tested random user selection, rejection of invalid transactions, etc.

2. 4 negative test results:

• Problems with funds management at withdrawal (withdraw function) were detected.
• Incorrect verification of data in transactions.
• Issues with contract termination with the kill function.
• Errors in logic at insufficient payment of tokens.

Ganache + Truffle

Truffle is one of the oldest tools for developing smart contracts on the Ethereum platform. Truffle has built-in support for Ganache, which makes it easy to create a local blockchain network for testing contracts. One of the key features of Truffle is the ability to use migration files for automated contract deployment, as well as integration with JavaScript for writing tests.

How do I get started with Truffle and Ganache?

Let’s install truffle in the local environment:

npm install --save-dev truffle

Next, initialize truffle in our project:

truffle init

As a result, the project structure should look like this:

Let’s move our smart contract to the contracts/ folder.

Edit the truffle-config.js file, configuring the local network:

Let’s run Ganache for local testing:

ganache-cli

Create a migration file in the migrations/ folder

Let’s perform a migration to deploy the contract:

truffle migrate --network development

Testing smart contracts

Let’s create a file test/MyContract.test.js, for an example of our vulnerable smart contract:

To run the test, you need to run the command:

truffle test

Test results

We tested several smart contracts in a local Truffle environment. A total of 12 successful tests were performed. Also, 3 failed tests and tests with negative results were identified:

Successful tests:

1. The test of making deposits and withdrawals within limits has been successfully completed.
2. Testing of buying and selling tokens has been completed without errors.
3. The prevention of withdrawal of funds in excess of the available balance was correctly implemented.
4. The test of activating functions only under correct conditions was also successful.

Failed tests and tests with negative results:

1. The BadRandomness contract failed to successfully execute a participation function due to missing required events.
2. In the SelfDestruct contract, errors occurred when activating the hidden access mechanism with an incorrect password.
3. Some tests revealed problems with the contract logic leading to incorrect processing of transactions or missing necessary events.

Hardhat

A popular smart contract development and testing tool that allows you to deploy contracts to local networks, write functionality tests, and find potential bugs.

How to get started with Hardhat?

First, you need to create a new project:

npm init -y

Let’s install Hardhat in the local environment:

npm install --save-dev hardhat

Next, initialize Hardhat in our project:

npx hardhat

Let’s add the .sol files to the “contracts” directory that was created when the project was initialized.

Edit the hardhat.config.js file, specifying basic settings such as the compiler version for our smart contracts:

To deploy contracts to the local test network, create a script deploy.js in the scripts directory. In it, we will describe the function for deploying the contract. For example:

Let’s run the command for deployment:

npx hardhat run scripts/deploy.js --network localhost

Functionality testing

To test the contract, let’s create a separate test file in the “test” directory. For example, our test for EtherStore.sol tested the following aspects:

1. Deposit verification. Is the balance recorded correctly after a deposit?
2. Checking withdrawals. Are funds returned to the owner if conditions are met?
3. Error check for premature withdrawal. Are withdrawal time restrictions triggered?

Finally let’s run the tests using the command:

npx hardhat test

The project structure looks like this:

Test results

We tested the functionality of smart contracts based on the Hardhat local network. As a result of performing 17 tests, we obtained:

1. 8 tests with positive results. Correctness of deposits, withdrawals and basic functions were checked.
2. 9 tests with negative results. Errors related to premature withdrawals and erroneous transactions were identified.

Manticore

Run a detailed analysis of the contract:

manticore /path/smart-contract.sol

Structure of the scan report:

1. global_BadRandomness.init_asm — contains EVM instructions in the form of assembly code showing contract execution.
2. global.findings — contains a list of found vulnerabilities with detailed explanations.
3. global.solver_stats — shows statistics of SAT solver operation, in particular, the number of tested states, solved constraints and generated input data.
4. global.summary — summary report of all found vulnerabilities, number of generated test scenarios, and analysis execution time.
5. manticore.yml — Manticore launch configuration.

The manticore.yml file defines exactly how the smart contract will be analyzed. This file probably needs to be modified according to the requirements of your project to improve the accuracy of testing.

In our case, we used the basic configuration of the manticore.yml file without making any changes. Because of this, some vulnerabilities went undetected because the default settings do not take into account the specifics of contracts and their environment. This emphasizes the importance of adapting the configuration to achieve maximum accuracy in testing, especially for projects with atypical logic or complex interactions between functions.

Medusa

Medusa is a powerful tool for automated fuzz testing of smart contracts.

How to get started with Medusa?

First you need to install Medusa using brew:

brew install medusa

To compile smart contract files, you need to install crytic-compile:

pip3 install crytic-compile

Once Medusa is installed, you can initialize the project:

medusa init

The file medusa.json will appear in your working directory. This file contains the basic Medusa settings that need to be adjusted for your specific project. For example, to test vulnerable smart contracts, a fragment of your configuration file might look like this:

After configuring medusa.json, you need to compile the smart contracts:

crytic-compile /path/contracts

To start the fuzz testing process, run the command:

medusa fuzz

Let’s take our first vulnerable smart contract BadRandomness as an example:

Mythril

Run a detailed analysis of the contract:

myth analyze path/smart-contract.sol

Scan result structure

1. General information about the vulnerability.
2. Contract and function.
3. Description of vulnerability.
4. Technical specifications.
5. Initial state.
6. Transaction sequence.
7. Recommendations.

Contract analysis using Mythril identified 14 vulnerabilities of varying degrees of risk.

Slither

Run a detailed analysis of the contract:

slither path/smart-contract.sol

Structure of the scan result

1. Analysis script.
2. Information from the detector.
3. Detector reference.

Contract analysis with Slither reveals 18 vulnerabilities of varying risk.

Solhint

Using Solhint allows you to follow common rules for writing code and identify potential problems that could affect security or runtime efficiency.

You should first install Solhint using the npm manager:

npm install solhint --save-dev

After installing Solhint, initialize the configuration file with the command:

solhint init

This command creates a .solhint.json file that contains the basic validation rules. It can be customized according to your needs.

You can read the full list of rules on the official GitHub resource Solhint:

You can run the check with the command:

solhint 'path/*.sol'

Test results

Several smart contracts were analyzed during the test. The applied Solhint base configuration detected 33 warnings, in particular:

1. Lack of reason messages in require calls (reason-string rule).
2. Using deprecated methods, such as suicide, which are not optimal.
3. Failure to explicitly specify the visibility of variables and functions (state-visibility rule).
4. Recommendation to use Custom Errors for efficiency instead of traditional string messages.

Tenderly

To get started, you need to log in to your account on Tenderly, create a new project and input your smart contract address.

To simulate transactions, it is necessary to add a wallet with sufficient balance. This allows you to simulate the execution of transactions in a real environment, taking into account real gas costs and other parameters. However, the simulation itself does not consume real funds or gas, ensuring secure testing. You can test individual contract features and set desired transaction parameters.

In our example, the transaction simulation failed because the contract function can only be called by the address owner. This demonstrates the importance of correctly configuring access to contract functions.

Tenderly provides a detailed execution report, including stack trace, which helps developers better understand the cause of the error and find the best solution.

Tenderly supports not only GUI but also CLI (command line interface). This allows you to integrate the tool into your workflow. For example, you can automate the testing of smart contracts with a configuration file that can be easily integrated into your project. More information can be found in the Tenderly documentation.

Thus, Tenderly is a good choice for developers who are looking for a convenient and powerful tool for testing smart contracts. It allows you to find bugs quickly, simulate transactions in real time and integrate easily into your project’s workflows.

Comparative characteristics of smart contract analysis and testing tools

For convenience, we have divided the tools into five categories by types and methods of analysis: static analysis, local testing, frameworks for debugging and unit testing, fuzzing testing and combined analysis. This division will help to understand the purpose of the tools and choose the right solution for specific cases, tasks, or phases of smart contract development and testing.

1. Static analysis is used to test code without executing it. It helps to find potential vulnerabilities at the stage of writing smart contracts.
2. Local testing allows you to run transactions in an isolated environment, simulating the execution of a contract without spending gas.
3. Debugging and unit testing frameworks facilitate the process of writing tests and verifying the functionality of smart contracts.
4. Fuzzing testing aims to dynamically verify the behavior of a contract under unpredictable inputs to detect limiting cases and logic errors.
5. The combined analysis combines static and dynamic approaches to check both code structure and runtime behavior.

Below is a comparison table for the first three categories of tools. It contains information about vulnerability detection methods, their advantages, and the main features of analysis tools. This will help you choose the optimal set of tools to improve the security of smart contracts at the initial stages of debugging and testing.

Table 1. Tools for static analysis, local testing, debugging, and unit testing.

Tool	Purpose	Type of analysis	Vulnerability detection methods
Aderyn	Detects number overflows, permissions issues, etc.	Static analysis	Analyze logic and code base using existing or internally created detectors
Ganache	Tests transactions in simulation and is not designed to find vulnerabilities.	Local testing	Transaction simulation
Hardhat	Used for debugging contracts.	Local testing	Debugging and unit testing
Slither	Detects multiple vulnerabilities such as reentrancy, number overflow and other logic errors thanks to more than 90 detectors.	Static analysis	Static analysis, logic checking
Solhint	Identifies potential style-related problems in the code as well as logic errors.	Linning	Static analysis of style and basic logic
Truffle	Used for unit testing.	Unit testing	Unit tests and contract migration

The table below presents the tools for dynamic and combined testing. This allows you to find errors when executing smart contracts. The main advantages of these tools and testing methods are described below.

Table 2. Tools for fuzzing testing and combined analysis.

Tool	Purpose	Type of analysis	Vulnerability Detection Methods
Diligence Fuzzing	Automated fuzzing testing.	Fuzzing testing	Fuzzing for DeFi protocols
Echidna	Identifies logical fallacies and limits cases.	Fuzzing testing	Fuzzing invariants
Foundry	Contract logic testing does not detect vulnerabilities directly.	Fuzzing and unit testing	Identifies functionality gaps by writing custom tests and automated fuzzing
Manticore	Detects logic errors, overflow, reentrancy.	Symbolic execution and dynamic analysis	Contract simulation and execution pathfinding
Medusa	Automated fuzzing testing.	Fuzzing testing	Byte-code fuzzing with support for parallel tests
Mythril	Detects logic errors, reentrancy, attacks.	Combined analysis	Symbolic execution, dynamic and static analysis
Tenderly	Used to model and verify contract behavior at runtime. Helps to verify the contract in real and simulation environment.	Simulation and debugging	Dynamic analysis in real and simulation environments

Let’s alphabetize all smart contract analysis tools into one table, describing their advantages and recommendations on their selection for certain circumstances and phases of projects.

Table 3. Recommendations for tool selection.

Tool	Advantages	Recommendations
Aderyn	Supports custom analyzers and any development structure (Foundry/Hardhat/Truffle, etc.)	Use for projects with high security requirements, especially when customization of analysis rules is required.
Diligence Fuzzing	A powerful tool for DeFi protocols.	Ideal for DeFi projects where hidden vulnerabilities can create serious risks.
Echidna	Checking invariants of smart contracts.	Use to verify high-risk protocols.
Foundry	Fast unit testing and integration with many tools.	Use for scalable projects that require rapid testing and development.
Ganache	A local blockchain network without the expense of gas.	Use to test smart contracts before deploying them on the main Ethereum network.
Hardhat	Flexible integration with other tools.	Use for complex projects that require customization of the development environment.
Manticore	Symbolic execution to verify all paths of contract fulfillment.	Use for in-depth analysis of complex smart contracts.
Medusa	A powerful fuzzer with parallel tests.	Useful for large projects with many testing scenarios.
Mythril	Supports symbolic execution and dynamic analysis.	Use for projectsthat require deep security analysis.
Slither	Fast static analysis with 90+ detectors.	Ideal for projects with regular code monitoring.
Solhint	Linter for Solidity, helps adhere to writing style and security standards.	Use for large teams where code style consistency is important.
Tenderly	Real-time transaction simulation without the cost of gas.	Use for DeFi-projects where transaction detail is important.
Truffle	A simple and straightforward framework for developing, testing and deploying contracts. Easy integration with scripts.	Use to write and execute unit tests of smart contracts and verify functionality in your development environment before performing a full security audit.

Conclusions

In this article, we have reviewed the best tools for testing smart contracts, categorizing them by analysis type and usage scenarios. Each of these tools has its own benefits and features that can make the work of developers, testers, and security auditors much easier. The choice of tool depends on your needs: from rapid prototyping with frameworks such as Hardhat or Foundry to deep security analysis with static and combined analysis tools such as Slither or Mythril.

We emphasize that using the right tools is only part of a comprehensive smart contract security process. We always recommend an additional manual audit of each line of code to identify potential vulnerabilities that may have gone undetected by automated tools.

If you don’t even want to spend time configuring automated tools and want to quickly find potential vulnerabilities in your smart contract, we invite you to test it with our free online analyzer scau.pro. This provides a quick initial shallow but quick security analysis.

For a more in-depth audit, we offer manual analysis by our experts. Contact our team to order professional smart contract auditing to help you protect your assets and secure your projects.

Our team of experts has already helped many projects by providing them with the highest level of security. For example, on the Project Reports page, you will find a public part of successful cases where we have found and fixed vulnerabilities of varying degrees of complexity. This allowed our clients to avoid financial losses and preserve the reputation of their projects.

Submit the form below, request a free consultation and take the first step to protect your smart contract today!

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