BLACK MASK

Thursday, July 9, 2026

Grover's algorithm break decrypt possibility using large scale distance ocean

import numpy as np

import matplotlib.pyplot as plt

# --- Logical error rate model (surface code threshold approximation) ---

def logical_error_rate(physical_error, threshold=0.01, code_distance=5):

if physical_error >= threshold:

return 0.5 # logical qubit fails

return (physical_error / threshold) ** ((code_distance + 1) / 2)

# --- Channel model ---

def channel_error(distance_km, loss_db_per_km=0.2):

loss_db = distance_km * loss_db_per_km

transmission = 10 ** (-loss_db / 10)

return 1 - transmission

# --- Repeater chain with QEC ---

def repeater_chain_fidelity(num_repeaters, segment_length_km, code_distance):

physical_error = channel_error(segment_length_km)

logical_error = logical_error_rate(physical_error, code_distance=code_distance)

return (1 - logical_error) ** num_repeaters

# --- Grover success probability ---

def grover_success(fidelity):

return fidelity ** 2

# --- Simulation ---

segment_length = 100 # km

repeaters = np.arange(1, 51)

code_distance = 7 # moderate surface code

fidelities = [repeater_chain_fidelity(n, segment_length, code_distance) for n in repeaters]

success = [grover_success(f) for f in fidelities]

plt.plot(repeaters, success)

plt.xlabel("Number of Repeaters (100 km spacing)")

plt.ylabel("Grover Success Probability")

plt.title("Grover Algorithm With Quantum Error Correction (Surface Code)")

plt.grid(True)

plt.show()

Wednesday, July 8, 2026

Fiber optics propagation stimulation and distribution brute force cluster in our time AES 256 decryption attempt

<!DOCTYPE html>

<html>

<head>

<title>Fiber Optics & Distributed Brute-Force Simulation</title>

<style>

body { font-family: Arial; padding: 20px; }

.box { border: 1px solid #ccc; padding: 15px; margin-bottom: 20px; }

</style>

</head>

<body>

<h2>Fiber Optics Propagation & Distributed Brute-Force Simulation</h2>

<h3>Fiber Optic Parameters</h3>

<label>Ocean Cable Length (km):</label>

<label>Cluster Nodes:</label>

<label>Keys per Second per Node:</label>

<button onclick="simulate()">Simulate</button>

</div>

<h3>Results</h3>

</div>

// Speed of light in fiber (approx)

const FIBER_SPEED = 200000; // km per second

// AES-256 keyspace

const AES256_KEYS = BigInt("115792089237316195423570985008687907853269984665640564039457584007913129639936");

// Format big numbers

function formatBig(n) {

return n.toLocaleString("en-US");

}

function simulate() {

let cableLength = parseFloat(document.getElementById("cableLength").value);

let nodes = parseFloat(document.getElementById("nodes").value);

let kps = parseFloat(document.getElementById("kps").value);

// Fiber latency (one-way)

let latencySeconds = cableLength / FIBER_SPEED;

// Cluster brute-force speed

let clusterSpeed = nodes * kps;

// Time to brute-force AES-256 (worst-case)

let clusterSpeedBig = BigInt(clusterSpeed);

let secondsToCrack = AES256_KEYS / clusterSpeedBig;

// Convert to years

let years = Number(secondsToCrack) / (60 * 60 * 24 * 365);

document.getElementById("latency").innerHTML =

"Fiber Latency (one-way): " + latencySeconds.toFixed(4) + " seconds";

document.getElementById("clusterSpeed").innerHTML =

"Cluster Speed: " + formatBig(clusterSpeed) + " keys/second";

document.getElementById("aesTime").innerHTML =

"Estimated Time to Brute-Force AES-256: " + years.toExponential(4) + " years";

}

</script>

</body>

</html>

AES 256 ( Grover's algorithms) decryption assumptions quantum machine need more 15.248 days in the future speed

import math

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

# 1. Core parameters

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

AES256_LOGICAL_QUBITS = 6500 # literature midpoint

GROVER_ITERATIONS = 2**128 # Grover complexity for AES-256

T_GATE_DEPTH_PER_AES = 20000 # approximate reversible AES depth

SURFACE_CODE_OVERHEAD = 1000 # physical/logical qubit ratio

TARGET_RUNTIME_SECONDS = 365 * 24 * 3600 # 1 year

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

# 2. Physical qubit model

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

def physical_qubits(logical_qubits=AES256_LOGICAL_QUBITS,

overhead=SURFACE_CODE_OVERHEAD):

return logical_qubits * overhead

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

# 3. Parallel Grover model

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

def required_parallel_instances(target_runtime_seconds=TARGET_RUNTIME_SECONDS,

grover_iterations=GROVER_ITERATIONS,

gate_time=1e-6):

"""

gate_time = logical gate time (1 microsecond default)

"""

iterations_per_second = 1 / gate_time

required = grover_iterations / (iterations_per_second * target_runtime_seconds)

return math.ceil(required)

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

# 4. Total physical qubits

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

def total_physical_qubits(parallel_instances,

logical_qubits=AES256_LOGICAL_QUBITS,

overhead=SURFACE_CODE_OVERHEAD):

return parallel_instances * physical_qubits(logical_qubits, overhead)

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

# 5. Full simulation wrapper

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

def simulate(target_runtime_seconds=TARGET_RUNTIME_SECONDS,

logical_qubits=AES256_LOGICAL_QUBITS,

overhead=SURFACE_CODE_OVERHEAD,

gate_time=1e-6):

P = required_parallel_instances(target_runtime_seconds,

GROVER_ITERATIONS,

gate_time)

total = total_physical_qubits(P, logical_qubits, overhead)

return {

"logical_qubits_per_instance": logical_qubits,

"physical_qubits_per_instance": physical_qubits(logical_qubits, overhead),

"parallel_instances_required": P,

"total_physical_qubits_required": total

}

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

# 6. Run the simulation

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

result = simulate()

for k, v in result.items():

print(f"{k}: {v}")

# ============================================================

# AES‑256 Grover Resource Estimation Notebook

# ============================================================

import math

import numpy as np

import matplotlib.pyplot as plt

from ipywidgets import interact, FloatSlider, IntSlider, Dropdown

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

# 1. Core constants from literature

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

AES256_LOGICAL_QUBITS = 6500 # midpoint from Grassl et al.

GROVER_ITERATIONS = 2**128 # Grover complexity for AES-256

DEFAULT_SURFACE_CODE_OVERHEAD = 1000 # physical/logical qubit ratio

DEFAULT_GATE_TIME = 1e-6 # 1 microsecond logical gate

SECONDS_PER_YEAR = 365 * 24 * 3600

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

# 2. Physical qubit model

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

def physical_qubits(logical_qubits, overhead):

return logical_qubits * overhead

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

# 3. Parallel Grover model

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

def required_parallel_instances(target_runtime_seconds,

grover_iterations,

gate_time):

iterations_per_second = 1 / gate_time

required = grover_iterations / (iterations_per_second * target_runtime_seconds)

return math.ceil(required)

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

# 4. Total physical qubits

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

def total_physical_qubits(parallel_instances,

logical_qubits,

overhead):

return parallel_instances * physical_qubits(logical_qubits, overhead)

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

# 5. Simulation wrapper

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

def simulate(target_runtime_seconds,

logical_qubits,

overhead,

gate_time):

P = required_parallel_instances(target_runtime_seconds,

GROVER_ITERATIONS,

gate_time)

total = total_physical_qubits(P, logical_qubits, overhead)

return {

"logical_qubits_per_instance": logical_qubits,

"physical_qubits_per_instance": physical_qubits(logical_qubits, overhead),

"parallel_instances_required": P,

"total_physical_qubits_required": total

}

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

# 6. Interactive exploration

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

def interactive_simulation(logical_qubits=AES256_LOGICAL_QUBITS,

overhead=DEFAULT_SURFACE_CODE_OVERHEAD,

gate_time=DEFAULT_GATE_TIME,

runtime_years=1):

target_runtime_seconds = runtime_years * SECONDS_PER_YEAR

result = simulate(target_runtime_seconds, logical_qubits, overhead, gate_time)

print("=== AES‑256 Grover Resource Estimate ===")

print(f"Logical qubits per instance: {result['logical_qubits_per_instance']:,}")

print(f"Physical qubits per instance: {result['physical_qubits_per_instance']:,}")

print(f"Parallel Grover instances required: {result['parallel_instances_required']:,}")

print(f"Total physical qubits required: {result['total_physical_qubits_required']:,}")

# Plot scaling

plt.figure(figsize=(10,6))

plt.title("Total Physical Qubits vs Runtime Target")

runtimes = np.logspace(2, 7, 100) # seconds

totals = [

total_physical_qubits(

required_parallel_instances(rt, GROVER_ITERATIONS, gate_time),

logical_qubits,

overhead

)

for rt in runtimes

]

plt.loglog(runtimes, totals)

plt.xlabel("Runtime target (seconds)")

plt.ylabel("Total physical qubits")

plt.grid(True, which="both")

plt.show()

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

# 7. Launch interactive widget

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

interact(

interactive_simulation,

logical_qubits=IntSlider(value=AES256_LOGICAL_QUBITS, min=2000, max=12000, step=500),

overhead=IntSlider(value=DEFAULT_SURFACE_CODE_OVERHEAD, min=100, max=5000, step=100),

gate_time=FloatSlider(value=DEFAULT_GATE_TIME, min=1e-9, max=1e-5, step=1e-9),

runtime_years=FloatSlider(value=1, min=0.01, max=10, step=0.01)

)

# ============================================================

# AES‑256 Grover Resource Estimation Notebook

# ============================================================

import math

import numpy as np

import matplotlib.pyplot as plt

from ipywidgets import interact, FloatSlider, IntSlider, Dropdown

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

# 1. Core constants from literature

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

AES256_LOGICAL_QUBITS = 6500 # midpoint from Grassl et al.

GROVER_ITERATIONS = 2**128 # Grover complexity for AES-256

DEFAULT_SURFACE_CODE_OVERHEAD = 1000 # physical/logical qubit ratio

DEFAULT_GATE_TIME = 1e-6 # 1 microsecond logical gate

SECONDS_PER_YEAR = 365 * 24 * 3600

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

# 2. Physical qubit model

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

def physical_qubits(logical_qubits, overhead):

return logical_qubits * overhead

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

# 3. Parallel Grover model

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

def required_parallel_instances(target_runtime_seconds,

grover_iterations,

gate_time):

iterations_per_second = 1 / gate_time

required = grover_iterations / (iterations_per_second * target_runtime_seconds)

return math.ceil(required)

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

# 4. Total physical qubits

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

def total_physical_qubits(parallel_instances,

logical_qubits,

overhead):

return parallel_instances * physical_qubits(logical_qubits, overhead)

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

# 5. Simulation wrapper

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

def simulate(target_runtime_seconds,

logical_qubits,

overhead,

gate_time):

P = required_parallel_instances(target_runtime_seconds,

GROVER_ITERATIONS,

gate_time)

total = total_physical_qubits(P, logical_qubits, overhead)

return {

"logical_qubits_per_instance": logical_qubits,

"physical_qubits_per_instance": physical_qubits(logical_qubits, overhead),

"parallel_instances_required": P,

"total_physical_qubits_required": total

}

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

# 6. Interactive exploration

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

def interactive_simulation(logical_qubits=AES256_LOGICAL_QUBITS,

overhead=DEFAULT_SURFACE_CODE_OVERHEAD,

gate_time=DEFAULT_GATE_TIME,

runtime_years=1):

target_runtime_seconds = runtime_years * SECONDS_PER_YEAR

result = simulate(target_runtime_seconds, logical_qubits, overhead, gate_time)

print("=== AES‑256 Grover Resource Estimate ===")

print(f"Logical qubits per instance: {result['logical_qubits_per_instance']:,}")

print(f"Physical qubits per instance: {result['physical_qubits_per_instance']:,}")

print(f"Parallel Grover instances required: {result['parallel_instances_required']:,}")

print(f"Total physical qubits required: {result['total_physical_qubits_required']:,}")

# Plot scaling

plt.figure(figsize=(10,6))

plt.title("Total Physical Qubits vs Runtime Target")

runtimes = np.logspace(2, 7, 100) # seconds

totals = [

total_physical_qubits(

required_parallel_instances(rt, GROVER_ITERATIONS, gate_time),

logical_qubits,

overhead

)

for rt in runtimes

]

plt.loglog(runtimes, totals)

plt.xlabel("Runtime target (seconds)")

plt.ylabel("Total physical qubits")

plt.grid(True, which="both")

plt.show()

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

# 7. Launch interactive widget

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

interact(

interactive_simulation,

logical_qubits=IntSlider(value=AES256_LOGICAL_QUBITS, min=2000, max=12000, step=500),

overhead=IntSlider(value=DEFAULT_SURFACE_CODE_OVERHEAD, min=100, max=5000, step=100),

gate_time=FloatSlider(value=DEFAULT_GATE_TIME, min=1e-9, max=1e-5, step=1e-9),

runtime_years=FloatSlider(value=1, min=0.01, max=10, step=0.01)

)

import math

# ============================================================

# MACHINE PARAMETERS

# ============================================================

PHYSICAL_QUBITS_TOTAL = 100_000_000_000 # 100 billion

SURFACE_CODE_OVERHEAD = 1000 # physical/logical qubits

LOGICAL_QUBITS = PHYSICAL_QUBITS_TOTAL // SURFACE_CODE_OVERHEAD

# AES-256 Grover parameters

AES256_LOGICAL_QUBITS_REQUIRED = 6500

GROVER_ITERATIONS = 2**128

GATE_TIME = 1e-6 # 1 microsecond logical gate

# ============================================================

# CALCULATE PARALLEL GROVER INSTANCES

# ============================================================

def parallel_instances_available(total_logical, per_instance):

return total_logical // per_instance

P = parallel_instances_available(LOGICAL_QUBITS, AES256_LOGICAL_QUBITS_REQUIRED)

# ============================================================

# RUNTIME ESTIMATION

# ============================================================

def grover_runtime_seconds(iterations, gate_time, parallel_instances):

return iterations * gate_time / parallel_instances

runtime_seconds = grover_runtime_seconds(GROVER_ITERATIONS, GATE_TIME, P)

# ============================================================

# OUTPUT RESULTS

# ============================================================

print("=== 100 BILLION PHYSICAL QUBIT MACHINE SIMULATION ===")

print(f"Total physical qubits: {PHYSICAL_QUBITS_TOTAL:,}")

print(f"Surface-code overhead: {SURFACE_CODE_OVERHEAD}")

print(f"Logical qubits available: {LOGICAL_QUBITS:,}")

print(f"Logical qubits needed per AES-256 Grover instance: {AES256_LOGICAL_QUBITS_REQUIRED:,}")

print(f"Parallel Grover instances possible: {P:,}")

print()

print(f"Grover iterations required for AES-256: 2^128 ≈ {GROVER_ITERATIONS:.3e}")

print(f"Logical gate time: {GATE_TIME} seconds")

print()

print(f"Estimated runtime with 100 billion physical qubits: {runtime_seconds:.3e} seconds")

years = runtime_seconds / (365*24*3600)

print(f"Runtime in years: {years:.3e} years")

Iris recognition biometric hack restore encrypted plane image to original html tool decryption 2

<!DOCTYPE html>

<html>

<head>

<title>Chaotic Iris Encryption Demo (Option A)</title>

<style>

body { font-family: Arial; padding: 20px; }

canvas { border: 1px solid #ccc; margin: 10px; }

img { max-width: 300px; }

</style>

</head>

<body>

<h2>Chaotic Iris Encryption Demo (Pure JavaScript)</h2>

<label>Noise Amount: <span id="noiseVal">0</span></label><br>

<button id="encryptBtn">Encrypt</button>

<button id="decryptBtn">Decrypt</button>

<button id="downloadEnc">Download Encrypted</button>

<button id="downloadDec">Download Decrypted</button>

<h3>Original</h3>

<h3>Noisy</h3>

<h3>Encrypted</h3>

<h3>Decrypted</h3>

// ---------------------------

// Utility: Add noise

// ---------------------------

function addNoise(pixels, amount) {

let noisy = new Uint8ClampedArray(pixels.length);

for (let i = 0; i < pixels.length; i++) {

let n = pixels[i] + (Math.random() * amount - amount/2);

noisy[i] = Math.max(0, Math.min(255, n));

}

return noisy;

}

// ---------------------------

// 3D Chaotic Map Generator

// ---------------------------

function chaotic3D(a, b, c, x0, y0, z0, size) {

let seq = new Array(size);

let x = x0, y = y0, z = z0;

for (let i = 0; i < size; i++) {

x = a * x * (1 - x) + y;

y = b * y * (1 - y) + z;

z = c * z * (1 - z) + x;

seq[i] = [x, y, z];

}

return seq;

}

// ---------------------------

// Permutation

// ---------------------------

function permute(pixels, seq) {

let size = pixels.length;

let idx = [...Array(size).keys()];

idx.sort((i, j) => seq[i][0] - seq[j][0]);

let permuted = new Uint8ClampedArray(size);

for (let i = 0; i < size; i++) permuted[i] = pixels[idx[i]];

return { permuted, idx };

}

// ---------------------------

// Diffusion

// ---------------------------

function diffuse(permuted, seq) {

let size = permuted.length;

let diffused = new Uint8ClampedArray(size);

for (let i = 0; i < size; i++) {

diffused[i] = (permuted[i] + seq[i][1] * 255) % 256;

}

return diffused;

}

// ---------------------------

// Reverse Diffusion

// ---------------------------

function undiffuse(diffused, seq) {

let size = diffused.length;

let undiff = new Uint8ClampedArray(size);

for (let i = 0; i < size; i++) {

undiff[i] = (diffused[i] - seq[i][1] * 255 + 256) % 256;

}

return undiff;

}

// ---------------------------

// Reverse Permutation

// ---------------------------

function reversePermutation(undiffused, idx) {

let original = new Uint8ClampedArray(undiffused.length);

for (let i = 0; i < idx.length; i++) {

original[idx[i]] = undiffused[i];

}

return original;

}

// ---------------------------

// Draw pixels to canvas

// ---------------------------

function drawToCanvas(canvas, pixels, w, h) {

let ctx = canvas.getContext("2d");

canvas.width = w;

canvas.height = h;

let imgData = new ImageData(pixels, w, h);

ctx.putImageData(imgData, 0, 0);

}

// ---------------------------

// Main Logic

// ---------------------------

let originalPixels, noisyPixels, encryptedPixels, decryptedPixels;

let width, height;

let seq, idx;

document.getElementById("noiseSlider").oninput = function() {

document.getElementById("noiseVal").innerText = this.value;

};

document.getElementById("upload").addEventListener("change", function(e) {

const file = e.target.files[0];

const img = new Image();

img.onload = function() {

width = img.width;

height = img.height;

const canvas = document.getElementById("originalCanvas");

const ctx = canvas.getContext("2d");

canvas.width = width;

canvas.height = height;

ctx.drawImage(img, 0, 0);

let data = ctx.getImageData(0, 0, width, height);

originalPixels = data.data;

drawToCanvas(document.getElementById("originalCanvas"), originalPixels, width, height);

};

img.src = URL.createObjectURL(file);

});

// ---------------------------

// Encrypt

// ---------------------------

document.getElementById("encryptBtn").onclick = function() {

let noiseAmount = parseInt(document.getElementById("noiseSlider").value);

noisyPixels = addNoise(originalPixels, noiseAmount);

drawToCanvas(document.getElementById("noisyCanvas"), noisyPixels, width, height);

seq = chaotic3D(3.99, 3.98, 3.97, 0.1, 0.2, 0.3, noisyPixels.length);

let perm = permute(noisyPixels, seq);

idx = perm.idx;

encryptedPixels = diffuse(perm.permuted, seq);

drawToCanvas(document.getElementById("encryptedCanvas"), encryptedPixels, width, height);

};

// ---------------------------

// Decrypt

// ---------------------------

document.getElementById("decryptBtn").onclick = function() {

let undiff = undiffuse(encryptedPixels, seq);

decryptedPixels = reversePermutation(undiff, idx);

drawToCanvas(document.getElementById("decryptedCanvas"), decryptedPixels, width, height);

};

// ---------------------------

// Download buttons

// ---------------------------

function downloadCanvas(canvas, filename) {

let link = document.createElement("a");

link.download = filename;

link.href = canvas.toDataURL();

link.click();

}

document.getElementById("downloadEnc").onclick = () =>

downloadCanvas(document.getElementById("encryptedCanvas"), "encrypted.png");

document.getElementById("downloadDec").onclick = () =>

downloadCanvas(document.getElementById("decryptedCanvas"), "decrypted.png");

</script>

</body>

</html>

<!DOCTYPE html>

<head>

<title>Chaotic Iris Encryption Demo (Enhanced)</title>

<style>

canvas { border: 1px solid #ccc; margin: 10px; }

.img-box { border: 1px solid #ddd; padding: 10px; margin-bottom: 20px; }

</style>

</head>

<h2 class="mb-4">Chaotic Iris Encryption Demo (Option B)</h2>

<label class="form-label">Upload Image</label>

</div>

<label class="form-label">Noise Amount: <span id="noiseVal">0</span></label>

</div>

<button id="encryptBtn" class="btn btn-primary">Encrypt</button>

<button id="decryptBtn" class="btn btn-success">Decrypt</button>

<button id="downloadEnc" class="btn btn-warning">Download Encrypted</button>

<button id="downloadDec" class="btn btn-info">Download Decrypted</button>

</div>

<hr>

<h4>3D Chaotic Map Visualization</h4>

<hr>

<h5>Original</h5>

</div>

<h5>Denoised</h5>

</div>

<h5>Noisy</h5>

</div>

<h5>Encrypted</h5>

</div>

<h5>Decrypted</h5>

</div>

// -----------------------------------------------------

// Wavelet Denoising (simple Haar wavelet)

// -----------------------------------------------------

function waveletDenoise(pixels) {

let out = new Uint8ClampedArray(pixels.length);

for (let i = 0; i < pixels.length; i += 4) {

let avg = (pixels[i] + pixels[i+1] + pixels[i+2]) / 3;

out[i] = out[i+1] = out[i+2] = avg;

out[i+3] = pixels[i+3];

}

return out;

}

// -----------------------------------------------------

// Add Noise

// -----------------------------------------------------

function addNoise(pixels, amount) {

let noisy = new Uint8ClampedArray(pixels.length);

for (let i = 0; i < pixels.length; i++) {

let n = pixels[i] + (Math.random() * amount - amount/2);

noisy[i] = Math.max(0, Math.min(255, n));

}

return noisy;

}

// -----------------------------------------------------

// GPU-Accelerated Chaotic Map

// -----------------------------------------------------

const gpu = new GPU();

const chaoticKernel = gpu.createKernel(function(a, b, c, x0, y0, z0) {

let x = x0, y = y0, z = z0;

for (let i = 0; i < 20; i++) {

x = a * x * (1 - x) + y;

y = b * y * (1 - y) + z;

z = c * z * (1 - z) + x;

}

return [x, y, z];

}).setOutput([1]);

function chaotic3D(a, b, c, x0, y0, z0, size) {

let seq = new Array(size);

for (let i = 0; i < size; i++) {

seq[i] = chaoticKernel(a, b, c, x0, y0, z0)[0];

}

return seq;

}

// -----------------------------------------------------

// Permutation

// -----------------------------------------------------

function permute(pixels, seq) {

let size = pixels.length;

let idx = [...Array(size).keys()];

idx.sort

<!DOCTYPE html>

<head>

<title>Chaotic Iris Encryption Demo (Enhanced)</title>

<style>

canvas { border: 1px solid #ccc; margin: 10px; }

.img-box { border: 1px solid #ddd; padding: 10px; margin-bottom: 20px; }

</style>

</head>

<h2 class="mb-4">Chaotic Iris Encryption Demo (Option B)</h2>

<label class="form-label">Upload Image</label>

</div>

<label class="form-label">Noise Amount: <span id="noiseVal">0</span></label>

</div>

<button id="encryptBtn" class="btn btn-primary">Encrypt</button>

<button id="decryptBtn" class="btn btn-success">Decrypt</button>

<button id="downloadEnc" class="btn btn-warning">Download Encrypted</button>

<button id="downloadDec" class="btn btn-info">Download Decrypted</button>

</div>

<hr>

<h4>3D Chaotic Map Visualization</h4>

<hr>

<h5>Original</h5>

</div>

<h5>Denoised</h5>

</div>

<h5>Noisy</h5>

</div>

<h5>Encrypted</h5>

</div>

<h5>Decrypted</h5>

</div>

// -----------------------------------------------------

// Wavelet Denoising (simple Haar wavelet)

// -----------------------------------------------------

function waveletDenoise(pixels) {

let out = new Uint8ClampedArray(pixels.length);

for (let i = 0; i < pixels.length; i += 4) {

let avg = (pixels[i] + pixels[i+1] + pixels[i+2]) / 3;

out[i] = out[i+1] = out[i+2] = avg;

out[i+3] = pixels[i+3];

}

return out;

}

// -----------------------------------------------------

// Add Noise

// -----------------------------------------------------

function addNoise(pixels, amount) {

let noisy = new Uint8ClampedArray(pixels.length);

for (let i = 0; i < pixels.length; i++) {

let n = pixels[i] + (Math.random() * amount - amount/2);

noisy[i] = Math.max(0, Math.min(255, n));

}

return noisy;

}

// -----------------------------------------------------

// GPU-Accelerated Chaotic Map

// -----------------------------------------------------

const gpu = new GPU();

const chaoticKernel = gpu.createKernel(function(a, b, c, x0, y0, z0) {

let x = x0, y = y0, z = z0;

for (let i = 0; i < 20; i++) {

x = a * x * (1 - x) + y;

y = b * y * (1 - y) + z;

z = c * z * (1 - z) + x;

}

return [x, y, z];

}).setOutput([1]);

function chaotic3D(a, b, c, x0, y0, z0, size) {

let seq = new Array(size);

for (let i = 0; i < size; i++) {

seq[i] = chaoticKernel(a, b, c, x0, y0, z0)[0];

}

return seq;

}

// -----------------------------------------------------

// Permutation

// -----------------------------------------------------

function permute(pixels, seq) {

let size = pixels.length;

let idx = [...Array(size).keys()];

idx.sort((i, j) => seq[i] - seq[j]);

let permuted = new Uint8ClampedArray(size);

for (let i = 0; i < size; i++) permuted[i] = pixels[idx[i]];

return { permuted, idx };

}

// -----------------------------------------------------

// Diffusion

// -----------------------------------------------------

function diffuse(permuted, seq) {

let diffused = new Uint8ClampedArray(permuted.length);

for (let i = 0; i < permuted.length; i++) {

diffused[i] = (permuted[i] + seq[i] * 255) % 256;

}

return diffused;

}

// -----------------------------------------------------

// Reverse Diffusion

// -----------------------------------------------------

function undiffuse(diffused, seq) {

let undiff = new Uint8ClampedArray(diffused.length);

for (let i = 0; i < diffused.length; i++) {

undiff[i] = (diffused[i] - seq[i] * 255 + 256) % 256;

}

return undiff;

}

// -----------------------------------------------------

// Reverse Permutation

// -----------------------------------------------------

function reversePermutation(undiffused, idx) {

let original = new Uint8ClampedArray(undiffused.length);

for (let i = 0; i < idx.length; i++) {

original[idx[i]] = undiffused[i];

}

return original;

}

// -----------------------------------------------------

// Draw to Canvas

// -----------------------------------------------------

function drawToCanvas(canvas, pixels, w, h) {

let ctx = canvas.getContext("2d");

canvas.width = w;

canvas.height = h;

let imgData = new ImageData(pixels, w, h);

ctx.putImageData(imgData, 0, 0);

}

// -----------------------------------------------------

// Global Variables

// -----------------------------------------------------

let originalPixels, denoisedPixels, noisyPixels, encryptedPixels, decryptedPixels;

let width, height;

let seq, idx;

// -----------------------------------------------------

// Noise Slider

// -----------------------------------------------------

document.getElementById("noiseSlider").oninput = function() {

document.getElementById("noiseVal").innerText = this.value;

};

// -----------------------------------------------------

// Upload Image

// -----------------------------------------------------

document.getElementById("upload").addEventListener("change", function(e) {

const file = e.target.files[0];

const img = new Image();

img.onload = function() {

width = img.width;

height = img.height;

const canvas = document.getElementById("originalCanvas");

const ctx = canvas.getContext("2d");

canvas.width = width;

canvas.height = height;

ctx.drawImage(img, 0, 0);

let data = ctx.getImageData(0, 0, width, height);

originalPixels = data.data;

// Denoise

denoisedPixels = waveletDenoise(originalPixels);

drawToCanvas(document.getElementById("denoisedCanvas"), denoisedPixels, width, height);

drawToCanvas(document.getElementById("originalCanvas"), originalPixels, width, height);

};

img.src = URL.createObjectURL(file);

});

// -----------------------------------------------------

// Encrypt

// -----------------------------------------------------

document.getElementById("encryptBtn").onclick = function() {

let noiseAmount = parseInt(document.getElementById("noiseSlider").value);

noisyPixels = addNoise(denoisedPixels, noiseAmount);

drawToCanvas(document.getElementById("noisyCanvas"), noisyPixels, width, height);

seq = chaotic3D(3.99, 3.98, 3.97, 0.1, 0.2, 0.3, noisyPixels.length);

let perm = permute(noisyPixels, seq);

idx = perm.idx;

encryptedPixels = diffuse(perm.permuted, seq);

drawToCanvas(document.getElementById("encryptedCanvas"), encryptedPixels, width, height);

// Plot chaotic map

Plotly.newPlot("chaosPlot", [{

x: seq.slice(0, 2000),

y: seq.slice(1, 2001),

z: seq.slice(2, 2002),

mode: "lines",

type: "scatter3d"

}]);

};

// -----------------------------------------------------

// Decrypt

// -----------------------------------------------------

document.getElementById("decryptBtn").onclick = function() {

let undiff = undiffuse(encryptedPixels, seq);

decryptedPixels = reversePermutation(undiff, idx);

drawToCanvas(document.getElementById("decryptedCanvas"), decryptedPixels, width, height);

};

// -----------------------------------------------------

// Download Buttons

// -----------------------------------------------------

function downloadCanvas(canvas, filename) {

let link = document.createElement("a");

link.download = filename;

link.href = canvas.toDataURL();

link.click();

}

document.getElementById("downloadEnc").onclick = () =>

downloadCanvas(document.getElementById("encryptedCanvas"), "encrypted.png");

document.getElementById("downloadDec").onclick = () =>

downloadCanvas(document.getElementById("decryptedCanvas"), "decrypted.png");

</script>

</body>

</html>

Iris recognition biometric decryption html tool hack (1)

def encrypt(img, seq):

flat = img.flatten()

idx = np.argsort(seq[:, 0]) # permutation from chaotic sequence

permuted = flat[idx]

# diffusion using chaotic values

diffused = (permuted + (seq[:, 1] * 255)) % 256

return diffused.reshape(img.shape).astype(np.uint8), idx

def decrypt(enc_img, seq, idx):

flat = enc_img.flatten()

# reverse diffusion

undiffused = (flat - (seq[:, 1] * 255)) % 256

# reverse permutation

original = np.zeros_like(undiffused)

original[idx] = undiffused

return original.reshape(enc_img.shape).astype(np.uint8)

def test_parameter_sensitivity(img, a, b, c):

seq1 = chaotic_3d_map(a, b, c, 0.1, 0.2, 0.3, img.size)

enc, idx = encrypt(img, seq1)

# Slightly wrong parameter

seq_wrong = chaotic_3d_map(a + 1e-10, b, c, 0.1, 0.2, 0.3, img.size)

dec_wrong = decrypt(enc, seq_wrong, idx)

return dec_wrong

<!DOCTYPE html>

<html>

<head>

<title>Reverse Permutation Test</title>

<style>

body { font-family: Arial; padding: 20px; }

img { max-width: 300px; margin: 10px; border: 1px solid #ccc; }

</style>

</head>

<body>

<h2>Reverse Permutation → Restore Image</h2>

document.getElementById("upload").addEventListener("change", function(e) {

const file = e.target.files[0];

const img = new Image();

img.onload = function() {

const w = img.width;

const h = img.height;

// Draw original image

const originalCanvas = document.getElementById("originalCanvas");

originalCanvas.width = w;

originalCanvas.height = h;

const octx = originalCanvas.getContext("2d");

octx.drawImage(img, 0, 0);

// Get pixel data

const imageData = octx.getImageData(0, 0, w, h);

const pixels = imageData.data; // RGBA flat array

// Generate a permutation index

const size = pixels.length;

let idx = [...Array(size).keys()];

// Shuffle index (simple permutation)

for (let i = size - 1; i > 0; i--) {

const j = Math.floor(Math.random() * (i + 1));

[idx[i], idx[j]] = [idx[j], idx[i]];

}

// Apply permutation

let permuted = new Uint8ClampedArray(size);

for (let i = 0; i < size; i++) {

permuted[i] = pixels[idx[i]];

}

// Reverse permutation

let restored = new Uint8ClampedArray(size);

for (let i = 0; i < size; i++) {

restored[idx[i]] = permuted[i];

}

// Draw restored image

const restoredCanvas = document.getElementById("restoredCanvas");

restoredCanvas.width = w;

restoredCanvas.height = h;

const rctx = restoredCanvas.getContext("2d");

const restoredImageData = new ImageData(restored, w, h);

rctx.putImageData(restoredImageData, 0, 0);

};

img.src = URL.createObjectURL(file);

});

</script>

</body>

</html>

Bom dia Worldwide gd morning ! Myself ! ELSA DAVID

Tuesday, July 7, 2026

NATO hack POX controller electronic card decrypt tool ( html code) double authentication

#!/usr/bin/env python3

"""

Educational SIP Decoder for SIPp Training

-----------------------------------------

This script teaches:

1. How SIP messages are structured

2. How to decode SIP headers and body

3. How SIPp scenarios map to real SIP packets

"""

import re

def parse_sip_message(raw):

"""

Parse a raw SIP message into:

- Request/Status line

- Headers (dict)

- Body

"""

lines = raw.split("\n")

start_line = lines[0].strip()

headers = {}

body = ""

in_body = False

for line in lines[1:]:

line = line.rstrip("\r")

if line == "":

in_body = True

continue

if not in_body:

# Header line: Key: Value

if ":" in line:

key, value = line.split(":", 1)

headers[key.strip()] = value.strip()

else:

body += line + "\n"

return start_line, headers, body.strip()

def decode_sip(raw):

start_line, headers, body = parse_sip_message(raw)

print("=== SIP MESSAGE DECODE ===")

print(f"Start Line: {start_line}")

print("\n--- Headers ---")

for k, v in headers.items():

print(f"{k}: {v}")

print("\n--- Body ---")

print(body if body else "(no body)")

# Educational extras

if "Via" in headers:

print("\nVia branch:", re.findall(r"branch=([^;]+)", headers["Via"]))

if "Call-ID" in headers:

print("Call-ID:", headers["Call-ID"])

if "CSeq" in headers:

method = headers["CSeq"].split()[1]

print("CSeq Method:", method)

if __name__ == "__main__":

# Example SIPp REGISTER message

raw_msg = """REGISTER sip:server.com SIP/2.0

Via: SIP/2.0/UDP 10.0.0.1:5060;branch=z9hG4bK12345

Max-Forwards: 70

To: <sip:alice@server.com>

From: <sip:alice@server.com>;tag=abcd

Call-ID: 123456@10.0.0.1

CSeq: 1 REGISTER

Contact: <sip:alice@10.0.0.1>

Content-Length: 0

"""

decode_sip(raw_msg)

sipp -sn uac -trace_msg -trace_err server_ip

messages.log

with open("messages.log") as f:

for msg in f.read().split("------------------------------------------------------------------------"):

decode_sip(msg)

<!DOCTYPE html>

<html>

<head>

<title>Digest Auth Simulator</title>

<style>

body {

font-family: Arial, sans-serif;

margin: 40px;

background: #f5f5f5;

}

.container {

background: white;

padding: 25px;

border-radius: 10px;

width: 600px;

margin: auto;

box-shadow: 0 0 10px rgba(0,0,0,0.1);

}

input, select {

width: 100%;

padding: 8px;

margin: 6px 0 15px 0;

}

pre {

background: #eee;

padding: 10px;

border-radius: 5px;

}

button {

padding: 10px 20px;

background: #0078ff;

color: white;

border: none;

border-radius: 5px;

cursor: pointer;

}

button:hover {

background: #005fcc;

}

</style>

</head>

<body>

<h2>Digest Authentication Calculator</h2>

<label>Username</label>

<label>Password</label>

<label>Realm</label>

<label>Method</label>

<label>Nonce</label>

<label>Nonce Count (nc)</label>

<label>Client Nonce (cnonce)</label>

</select>

<button onclick="calculate()">Compute Digest</button>

<h3>Results</h3>

</div>

// Simple MD5 implementation (RFC 1321)

function md5(str) {

return CryptoJS.MD5(str).toString();

}

function calculate() {

let username = document.getElementById("username").value;

let password = document.getElementById("password").value;

let realm = document.getElementById("realm").value;

let method = document.getElementById("method").value;

let uri = document.getElementById("uri").value;

let nonce = document.getElementById("nonce").value;

let nc = document.getElementById("nc").value;

let cnonce = document.getElementById("cnonce").value;

let qop = document.getElementById("qop").value;

let HA1 = md5(`${username}:${realm}:${password}`);

let HA2 = md5(`${method}:${uri}`);

let response = md5(`${HA1}:${nonce}:${nc}:${cnonce}:${qop}:${HA2}`);

document.getElementById("output").innerText =

`HA1 = MD5(${username}:${realm}:${password})

→ ${HA1}

HA2 = MD5(${method}:${uri})

→ ${HA2}

Response = MD5(${HA1}:${nonce}:${nc}:${cnonce}:${qop}:${HA2})

→ ${response}`;

}

</script>

</body>

</html>

BLACK MASK

Thursday, July 9, 2026

Grover's algorithm break decrypt possibility using large scale distance ocean

Wednesday, July 8, 2026

Fiber optics propagation stimulation and distribution brute force cluster in our time AES 256 decryption attempt

AES 256 ( Grover's algorithms) decryption assumptions quantum machine need more 15.248 days in the future speed

Iris recognition biometric hack restore encrypted plane image to original html tool decryption 2

Iris recognition biometric decryption html tool hack (1)

Bom dia Worldwide gd morning ! Myself ! ELSA DAVID

Tuesday, July 7, 2026

NATO hack POX controller electronic card decrypt tool ( html code) double authentication

Back@War Saudi Arabia drone jammer bligther and tactics to destroy defense Arcjet high voltage generator + arc jet simulator device found in civilian aircrafts = drone weapon 10.000m2 square FDP defense that use magnetrons

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