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Reverse decode decrypt attempt 64bits python code

 

import hashlib

import io

import time

import numpy as np

from PIL import Image

import csv

import random

# -------------------------------------------------------------

# 1. LOAD IMAGE AND RETURN RAW BUFFER

# -------------------------------------------------------------

def get_image_buffer(path):

    img = Image.open(path).convert("RGB")

    buf = io.BytesIO()

    img.save(buf, format="PNG")

    return buf.getvalue()

# -------------------------------------------------------------

# 2. 64-BIT ONE-WAY HASH

# -------------------------------------------------------------

def hash64(data):

    full = hashlib.sha256(data).digest()

    return full[:8]  # 64 bits

# -------------------------------------------------------------

# 3. HASH DISTANCE (Hamming)

# -------------------------------------------------------------

def hash_distance(h1, h2):

    return sum(bin(a ^ b).count("1") for a, b in zip(h1, h2))

# -------------------------------------------------------------

# 4. TIMESTAMP + MUTATION ENGINE

# -------------------------------------------------------------

def mutate_buffer(base_bytes, timestamp):

    candidate = bytearray(base_bytes)

    # timestamp XOR

    ts_bytes = int(timestamp).to_bytes(8, "little")

    for i in range(min(len(candidate), len(ts_bytes))):

        candidate[i] ^= ts_bytes[i]

    # random micro-mutation

    idx = random.randint(0, len(candidate)-1)

    candidate[idx] ^= random.randint(0, 255)

    return bytes(candidate)

# -------------------------------------------------------------

# 5. REVERSE ATTEMPT LOOP

# -------------------------------------------------------------

def reverse_attempt(target_hash, base_bytes, iterations=50000):

    results = []

    best_candidate = None

    best_distance = 999

    for i in range(iterations):

        ts = time.time_ns()

        candidate = mutate_buffer(base_bytes, ts)

        h = hash64(candidate)

        dist = hash_distance(h, target_hash)

        if dist < best_distance:

            best_distance = dist

            best_candidate = candidate

            print(f"New best distance: {dist}")

        match = (h == target_hash)

        results.append((ts, h.hex(), dist, match))

        if match:

            print("Exact pre-image found!")

            return candidate, results

    return best_candidate, results

# -------------------------------------------------------------

# 6. RUN PIPELINE

# -------------------------------------------------------------

buf = get_image_buffer("input.png")

target_hash = hash64(buf)

print("Target 64-bit hash:", target_hash.hex())

candidate, results = reverse_attempt(target_hash, buf)

# -------------------------------------------------------------

# 7. LOG RESULTS

# -------------------------------------------------------------

with open("reverse_attempt_log.csv", "w", newline="") as f:

    writer = csv.writer(f)

    writer.writerow(["timestamp_ns", "hash", "distance", "match"])

    writer.writerows(results)

print("Pipeline complete.")