Chain-Fox automates security detection for blockchains and smart contracts. Operations teams use it to identify vulnerabilities and ensure compliance. It integrates with existing development workflows and supports Python.
git clone https://github.com/Chain-Fox/Chain-Fox.githttps://www.chain-fox.com
Automate security audits for smart contracts to identify vulnerabilities before deployment.
Integrate automated risk checks into CI/CD pipelines to ensure continuous security monitoring.
Utilize multi-language support to analyze code written in Rust, Go, and Solidity for potential bugs.
Implement rug pull detection to safeguard against malicious on-chain behaviors.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/Chain-Fox/Chain-FoxCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Analyze the following smart contract code for vulnerabilities using Chain-Fox: [CONTRACT_CODE]. Focus on [SPECIFIC_CONCERNS] like reentrancy, integer overflow, or gas optimization issues. Provide a detailed report with remediation steps.
# Smart Contract Security Analysis ## Vulnerability Report ### High Risk Issues - **Reentrancy Vulnerability**: Detected in the `withdrawFunds` function. Attackers could drain funds by recursively calling the function before state updates. - **Integer Overflow**: Found in the `transfer` function. Large value transfers could overflow the balance tracking. ### Medium Risk Issues - **Unchecked External Calls**: The contract interacts with external contracts without verifying their integrity. ## Recommendations 1. Implement the **Checks-Effects-Interactions** pattern to prevent reentrancy. 2. Use SafeMath library to handle arithmetic operations securely. 3. Add input validation for external contract addresses. ## Gas Optimization - Replace `uint` with `uint256` for clarity and consistency. - Consider using `mapping` instead of arrays for large datasets.
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