Quote from: sdhgfdsjfgsiujdgf on December 24, 2024, 11:46:37 PM

Quote from: bit_mind on December 24, 2024, 10:00:54 PM

How long do you think the hash 160 can break?
How long can it take?

Code:

import hashlib
import time
from itertools import product
import string

def ripemd160(data):
"""
Compute the RIPEMD-160 hash of the given data.
"""
h = hashlib.new('ripemd160')
h.update(data.encode('utf-8'))
return h.hexdigest()

def brute_force_ripemd160(target_hash, max_length=5):
"""
Simulate brute-forcing a RIPEMD-160 hash.
Test all combinations of characters up to a given length.
"""
characters = string.ascii_letters + string.digits
start_time = time.time()
attempt_count = 0 # Track number of attempts

print(f"Brute-forcing RIPEMD-160 hash: {target_hash}")
print(f"Using characters: {characters}")

# Brute-force attempt
for length in range(1, max_length + 1):
print(f"\nTesting all combinations of length: {length}")
for attempt in product(characters, repeat=length):
attempt_count += 1
guess = ''.join(attempt)
guess_hash = ripemd160(guess)

# Show progress every 100,000 attempts
if attempt_count % 100000 == 0:
elapsed_time = time.time() - start_time
print(f"Attempts: {attempt_count:,} | Time elapsed: {elapsed_time:.2f} seconds")

if guess_hash.upper() == target_hash.upper():
elapsed_time = time.time() - start_time
print(f"\nMatch found: {guess}")
print(f"Attempts: {attempt_count:,}")
print(f"Time taken: {elapsed_time:.2f} seconds")
return guess

elapsed_time = time.time() - start_time
print(f"\nNo match found within {max_length}-character keyspace.")
print(f"Total attempts: {attempt_count:,}")
print(f"Time taken: {elapsed_time:.2f} seconds")
return None

target_hash = "1234567890123456789012345678912345678..." # Replace with your hash
print(f"Target Hash: {target_hash}")

# Run the brute-force simulation
brute_force_ripemd160(target_hash, max_length=5)

The answer is simple, longer than the universe will exist. This means that the universe will collapse onto itself in deflation and basically end, before your script will finish.

December 9, 2024

Google today introduced its latest quantum chip — Willow (~100 qubits) — coinciding with two key achievements run on the new chip: breaking of the so-called Quantum Error Correction Threshold and posting a new benchmark for quantum performance against classical computing; Willow ran a benchmark task in five minutes that Google said would take ten septillion years (1024) on Frontier, which until a few weeks ago was the fastest supercomputer in the world.

It’s rare to catch Google in a talkative mood, but the technology giant held a media/analyst briefing before today’s announcement with handful of prominent members of the Google Quantum-AI team including Hartmut Neven, founder and lead; Michael Newman, research scientist; Julian Kelly, director of quantum hardware; and Carina Chou, director and COO. Currently, the Google Quantum-AI team has roughly 300 people with, plans for growth, and its own state of the art fabrication facility at UCSB.

This an important moment for Google’s quantum effort:

Breaking the QEC threshold (error rate decreases as number of qubits rises) is a long-sought goal in the community and basically proves it will be possible to build large error-corrected useful quantum computer.
The company also walked through its roadmap, discussing on technical goals (though not in great granularity) and business milestones. While the main focus is on achieving error-corrected QC fault-tolerance sometime around the end of the decade, it’s also looking at nearer term applications.
It also discussed its broad quantum business plans which include everything from fabbing its own chips and building its own system to offering quantum services via the cloud (naturally) but also plans for potential on-premise deployments.