increase the search speed of the Pubkeys, dividing the search range.
First of all, let me make it clear that this script is slow and basic, I did it like this in order to explain the range division method.
If you want to apply it quickly, modify keyhunt or other c++ code before compiling to make it work with this method.
The method consists in changing the parameters of the curve by x,y of a higher point (for the script I used pk#100).
by default the curve uses pubkey #1
what works in sequence 1,2,3,4....
pubkey #100
which works in sequence 100,200,300,400....
if we want to find pk# 3922
in a range of 2000:6000
in the traditional way we would need to advance +1900 pubkeys
In this method we will only need 19 pubkeys (1900/100).
the database is done by subtracting 1 consecutively from the target pubkey (in my case I need to subtract( 1), 100 times because I chose pubkey pk# 100 as divisor.
The trick is in your ability to use fast databases, the more pubkey you store in the database, the higher the divisor will be, therefore the search range is smaller.
save as brute_div.py
import os
import hashlib
import random
import binascii
#target pk decimal 3922
#Target_Upub "042f3342152eff6aca5e7314db6d3301a28d6a90ddcfd189f96babadc2a053d3929d0e4bef850141613e6bb3d3e2c480b3634af4332f125f4edfc65b88816f541d"
#Start_Range in decimal
Start_Range = 2000
#End_Range in decimal
End_Range = 6000
#divisor pk in decimal
boost = 100
#boost_upub "X=ed3bace23c5e17652e174c835fb72bf53ee306b3406a26890221b4cef7500f88, y=e57a6f571288ccffdcda5e8a7a1f87bf97bd17be084895d0fce17ad5e335286e"
class Point:
def __init__(self,
#change x and y for boost_upub
x=0xed3bace23c5e17652e174c835fb72bf53ee306b3406a26890221b4cef7500f88,
y=0xe57a6f571288ccffdcda5e8a7a1f87bf97bd17be084895d0fce17ad5e335286e,
p=2**256 - 2**32 - 2**9 - 2**8 - 2**7 - 2**6 - 2**4 - 1):
self.x = x
self.y = y
self.p = p
def __add__(self, other):
return self.__radd__(other)
def __mul__(self, other):
return self.__rmul__(other)
def __rmul__(self, other):
n = self
q = None
for i in range(256):
if other & (1 << i):
q = q + n
n = n + n
return q
def __radd__(self, other):
if other is None:
return self
x1 = other.x
y1 = other.y
x2 = self.x
y2 = self.y
p = self.p
if self == other:
l = pow(2 * y2 % p, p-2, p) * (3 * x2 * x2) % p
else:
l = pow(x1 - x2, p-2, p) * (y1 - y2) % p
newX = (l ** 2 - x2 - x1) % p
newY = (l * x2 - l * newX - y2) % p
return Point(newX, newY)
def toBytes(self):
x = self.x.to_bytes(32, "big")
y = self.y.to_bytes(32, "big")
return b"\x04" + x + y
def getPublicKey(privkey):
SECP256k1 = Point()
pk = int.from_bytes(privkey, "big")
publickey =(((SECP256k1 * pk).toBytes()).hex())
return publickey
if __name__ == "__main__":
#range Div
for i in range((Start_Range//boost), (End_Range//boost)):
print(i)
b = hex(i)[2:]
c = str.format(b)
pk= c.zfill(64)
Seq_Bytes = binascii.unhexlify(pk)
PublicKey = getPublicKey(Seq_Bytes)
#print(PublicKey)
Privatekey = (Seq_Bytes).hex()
#print(Privatekey)
data_base = 'data-base.txt'
with open(data_base, 'r') as file:
content= file.read()
#search publickey in data-base
if PublicKey in content:
print("Range Found")
print("Decimal:", int(Privatekey, base=16)*boost)
save as data-base.txt
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I currently don't have what it takes to code in C++ using the quick search methods, my resources are limited to the basics.
I currently don't have an up-to-date pc to do the relevant tests (the disadvantages of the third world).
However, later I will share faster methods, ECC tricks.
