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Meng is a Python application that analyzes the security and potential risks of Ethereum tokens using the GoPlus Token Security API and Rug Pull Detection API. It generates a detailed report in Markdown format and stores the analysis data in an SQLite database. The results should not be considered financial/investment advice and are for informational purposes only. Users should perform their own due diligence andDYOR.

• Retrieves token security and rug pull risk data from the GoPlus API
• Generates a comprehensive Markdown report with the analysis results
• Saves the report to a file named after the token symbol and current date
• Stores the JSON data returned by each API, along with the contract address and the current date, in an SQLite database

• Python 3.x
• goplus library

1. Clone the repository:git clone https://github.com/your-username/meng.git

2. Install the required dependencies:pip install goplus

1. Run the script:python main.py

2. Enter the token contract address when prompted.

3. The script will analyze the token and generate a report. The report will be displayed in the console and saved as a Markdown file in thereports folder with the filename format<token_symbol>_<current_date>.md.

4. The JSON data returned by each API, along with the contract address and the current date, will be stored in an SQLite database namedtoken_data.db.

The generated report includes the following sections:

• Token Analysis Report
• Date
• Report date
• Token Security Analysis
• Raw JSON data from the token security API
• Token Security Analysis Breakdown
• Open Source
• Proxy Contract
• Mint Function
• Owner Address
• Can Take Back Ownership
• Owner Can Change Balance
• Hidden Owner
• Selfdestruct
• External Call
• In DEX
• Buy Tax
• Sell Tax
• Can't Buy
• Can't Sell All
• Slippage Modifiable
• Honeypot
• Transfer Pausable
• Blacklist
• Whitelist
• Anti Whale
• Anti Whale Modifiable
• Trading Cooldown
• Personal Slippage Modifiable
• Token Name
• Token Symbol
• Holder Count
• Total Supply
• Creator Address
• Creator Balance
• Creator Percent
• LP Holder Count
• LP Total Supply
• Is True Token
• Is Airdrop Scam
• Is In Trust List
• Other Potential Risks
• Note
• Fake Token
• Rug Pull Security Analysis
• Raw JSON data from the rug pull security API
• Rug Pull Security Analysis Breakdown
• Owner Name
• Owner Address
• Owner Type
• Privilege Withdraw
• Cannot Withdraw
• Contract Verified
• Blacklist Function
• Contract Name
• Self-Destruct
• Potential Approval Abuse
• Proxy Contract

The SQLite databasetoken_data.db contains a table namedtoken_data with the following schema:

• id (INTEGER): Primary key
• contract_address (TEXT): The token contract address
• token_security_data (TEXT): The JSON data returned by the token security API
• rug_pull_data (TEXT): The JSON data returned by the rug pull security API
• date (TEXT): The date when the analysis was performed

This project is licensed under theMIT License.