PoisonF is a powerful tool designed to automate address poisoning attacks for blockchain security research and simulation purposes. It supports multiple networks and helps red-teamers test user interface vulnerabilities in transaction history views on major wallets and explorers.
🧪 PoisonF: Address Poisoning Tool PoisonF is a Python-based tool designed to simulate, detect, and analyze Ethereum address poisoning attacks. With support for multiple EVM-compatible networks, it enables researchers and developers to understand this vector, test its impact, and build defenses.
PoisonF streamlines the full address poisoning workflow for automated blockchain security simulations:
PoisonF continuously monitors blockchain activity for USDT transfers and automatically initiates poisoning if a wallet exceeds the user-defined balance threshold.
It leverages optimized algorithms to create vanity addresses that mimic the first and last characters of a target wallet or its counterparties.
By connecting to an Ethereum-compatible node via RPC and using a provided private key, PoisonF handles all gas fees from a designated funder account during poisoning execution.
For each crafted vanity address, the tool sends a transaction mimicking the exact USDT value from the original ETH transaction, creating deceptive entries in the recipient’s transaction history.
Logs all generated addresses, transaction hashes, and the result of each poisoning attempt with real-time feedback.
- Ethereum Mainnet
- Binance Smart Chain
- Polygon
- Avalanche
- Arbitrum
- Optimism
- ... and more via custom RPC support
Clone the repository Rename env.example to .env Edit .env with your private key & RPC url Install dependencies pip install -r requirements.txt Run the bot py poison.py
This tool is intended strictly for educational and ethical testing purposes in controlled environments. Any misuse of this tool may be illegal and is solely the responsibility of the user.
git clone https://github.com/yourname/poisonf
cd poisonf
pip install -r requirements.txt
python poisonf.py
If you need support, contact on telegram at **@drainerf**