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 and DYOR.
- 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
-
Clone the repository:
git clone https://github.com/your-username/meng.git
-
Install the required dependencies:
pip install goplus
-
Run the script:
python main.py
-
Enter the token contract address when prompted.
-
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 the
reports
folder with the filename format<token_symbol>_<current_date>.md
. -
The JSON data returned by each API, along with the contract address and the current date, will be stored in an SQLite database named
token_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 database token_data.db
contains a table named token_data
with the following schema:
id
(INTEGER): Primary keycontract_address
(TEXT): The token contract addresstoken_security_data
(TEXT): The JSON data returned by the token security APIrug_pull_data
(TEXT): The JSON data returned by the rug pull security APIdate
(TEXT): The date when the analysis was performed
This project is licensed under the MIT License.