An automated Dogecoin wallet collider that brute forces random wallet addresses. Original Plutus Brute Forcer created by Isaacdelly. Fastecdsa fork created by imcmurray. Dogecoin modification done by LongWayHomie.
So the idea for this fork of Plutus is not to attack active wallet addresses (much bad, so despicable), but to attack the dormant ones that has been probably lost forever. Database file has been filled with dormant addresses from 7 years. Try your luck on becoming DOGE millionaire (or billionaire).
DOGE: D6DkzqqLA87bEfERSXjcg1XZEpHrWJopZ8
ETH: 0x01f543F75D163Ce1AABA3fe2bd19f1C405BbE754
Python 3.6 or higher
Python modules listed in the requirements.txt
Minimum RAM requirements
$ git clone https://github.com/LongWayHomie/Plutus-dogecoin.git
$ cd Plutus-dogecoin && pip3 install -r requirements.txt
$ python3 plutus.py
Dogecoin private keys allow a person to control the wallet that it correlates to. If the wallet has Dogecoins in it, then the private key will allow the person to spend whatever balance the wallet has.
This program attempts to brute force Dogecoin private keys in an attempt to successfully find a correlating wallet with a positive balance. In the event that a balance is found, the wallet's private key, public key and wallet address are stored in the text file plutus.txt on the user's hard drive.
This program is essentially a brute forcing algorithm. It continuously generates random Dogecoin private keys, converts the private keys into their respective wallet addresses, then checks the balance of the addresses. The ultimate goal is to randomly find a wallet with a balance out of the 2160 possible wallets in existence.
Private keys are generated randomly to create a 32 byte hexidecimal string using the cryptographically secure os.urandom() function.
The private keys are converted into their respective public keys using the fastecdsa Python module. Then the public keys are converted into their Dogecoin wallet addresses using the binascii and hashlib standard libraries.
A pre-calculated database of every P2PKH Dogecoin address with a positive balance is included in this project. The generated address is searched within the database, and if it is found that the address has a balance, then the private key, public key and wallet address are saved to the text file plutus.txt on the user's hard drive.
This program also utilizes multiprocessing through the multiprocessing.Process() function in order to make concurrent calculations.
With Fastecdsa the efficieny of this code has increased by an average of 50%, from 0.0032457721 seconds (without Fastecdsa) to 0.0017291287 seconds (with Fastecdsa) for this progam to brute force a single Dogecoin address.
However, through multiprocessing.Process() a concurrent process is created for every CPU your computer has. So this program can brute force addresses at a speed of 0.0017291287 ÷ cpu_count() seconds.
Visit /database for information Database has been created for dormant addresses. Give yourself a shot on lost wallets to be a DOGE millionaire.
Every time this program checks the balance of a generated address, it will print the result to the user. If an empty wallet was generated, then the wallet address will be printed to the terminal. An example is:
D7owrG49zF599RNSwpxQf9tAVGcrqCkuj4
However, if a balance is found, then all necessary information about the wallet will be saved to the text file much_money.txt. An example is:
hex private key: 5A4F3F1CAB44848B2C2C515AE74E9CC487A9982C9DD695810230EA48B1DCEADD
public key: 04393B30BC950F358326062FF28D194A5B28751C1FF2562C02CA4DFB2A864DE63280CC140D0D540EA1A5711D1E519C842684F42445C41CB501B7EA00361699C320
address: D7owrG49zF599RNSwpxQf9tAVGcrqCkuj4
WIF private key: 6KKtnGNVkwg8K9BqygtLjay8b48cfgtWBgv4rSGPMT92sVWvnqH
This program uses approximately 2GB of RAM per CPU. Becuase this program uses multiprocessing, some data gets shared between threads, making it difficult to accurately measure RAM usage. But the stack trace below is as precise as I could get it:
The memory consumption stack trace was made by using mprof to monitor this program brute force 10,000 addresses on a 4 logical processor machine with 8GB of RAM. As a result, 4 child processes were created, each consuming 2100MiB of RAM (~2GB).