its_a_ko_magic/rhme3-itsakindofmagic.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# RHme3: It's a Kind of Magic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You managed to get a spare key fob for the car you like. However you want to duplicate it so that you can maintain your access to it. Through extensive reverse engineering, you figure out that the device accepts an input challenge performs AES-128 encryption (or decryption) and returns the response. It is also identified that the device operates on masked input and returns masked output. Extract the key so you can get free rides!\n",
    "\n",
    "The device expects 18 bytes of input: the first byte should be either 0xAE (for encryption) or 0xAD (for decryption) followed by 16 bytes of data, followed by a newline."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load the tools\n",
    "using Jlsca.Sca\n",
    "using Jlsca.Trs\n",
    "using Jlsca.Align\n",
    "using Jlsca.Aes\n",
    "using PyCall\n",
    "using PyPlot.plot,PyPlot.figure\n",
    "\n",
    "@pyimport numpy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Explore the traces"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we can mount any kind of attack, we need to understand what's happening. To do that, we need to visualize the data, and check out what we can see."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[x] Skipping unknown tag 70 with length 5\n",
      "[x] Skipping unknown tag 73 with length 1\n",
      "[x] Skipping unknown tag 74 with length 1\n",
      "[x] Skipping unknown tag 75 with length 4\n",
      "[x] Skipping unknown tag 76 with length 4\n",
      "[x] Skipping unknown tag 104 with length 4\n",
      "[x] Skipping unknown tag 105 with length 1\n",
      "[x] Skipping unknown tag 106 with length 1\n",
      "Opened IKM-500 + Resampled (sync) + StaticAlign + Trim.trs, #traces 500"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Jlsca.Trs.InspectorTrace(45, Nullable{Int64}(500), 32, 4, Float32, 33050, 61, IOStream(<file IKM-500 + Resampled (sync) + StaticAlign + Trim.trs>), \"IKM-500 + Resampled (sync) + StaticAlign + Trim.trs\", 61, false, 2, false, Jlsca.Trs.MetaData(0, Jlsca.Trs.Pass[], Jlsca.Trs.Pass[], Nullable{Jlsca.Trs.PostProcessor}(), Nullable{Range}(), Nullable{Range}(), true, #undef, #undef, #undef))"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ", #samples 33050 (Float32), #data 32, #title 45\n"
     ]
    }
   ],
   "source": [
    "# load the traceset\n",
    "trs = InspectorTrace(\"IKM-500 + Resampled (sync) + StaticAlign + Trim.trs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PyPlot.Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# read and plot 10 traces with some zoom\n",
    "((data,samples),eof) = readTraces(trs, 1:5);\n",
    "plot(samples[1:end,1:end]', linewidth=.3); # note the transpose; and here you can play with the zoom\n",
    "; # suppress output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Above we can clearly see the AES structure. Just by counting the sections, we can get a good idea of what is what.\n",
    "* There are 11 AddRoundKeys, and those are the first and last operations\n",
    "* There are 10 each SubBytes and ShiftRows\n",
    "* There are 9 MixColumns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PyPlot.Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot data correlations\n",
    "((data,samples),eof) = readTraces(trs, 1:500)\n",
    "plot(cor(samples[1:end,1:end], data[:,1:32]))\n",
    ";"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PyPlot.Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "PyPlot.Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot up to the end of the first round, and the input data correlations\n",
    "firstRound = 400:4600\n",
    "((data,samples),eof) = readTraces(trs, 1:10);\n",
    "plot(samples[1:10,firstRound]', linewidth=.3);\n",
    "figure()\n",
    "((data,samples),eof) = readTraces(trs, 1:500);\n",
    "plot(cor(samples[1:end,firstRound], data[:,1:16]))\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The four visible sections are the initial AddRoundKey, then SubBytes, ShiftRows, MixColumns, and AddRoundKey. The input data correlations are clustered in the initial AddRoundKey step, with significant correlations still visible in SubBytes. While correlations often persist through an XOR, SubBytes, doing what it does, breaks all input correlations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run correlation power analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is the actual run section. Even though it's using AES-128, we are going to launch a AES-256 attack."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Jlsca running in Julia version: 0.6.2, 1 processes/1 workers/1 threads per worker\n",
      "\n",
      "DPA parameters\n",
      "attack:       AES Sbox\n",
      "mode:         CIPHER\n",
      "key length:   KL256\n",
      "direction:    FORWARD\n",
      "xor:          false\n",
      "analysis:     CPA\n",
      "leakages:     HW\n",
      "maximization: abs global max\n",
      "data at:      1\n",
      "\n",
      "phase: 1 / 2, #targets 16\n",
      "\n",
      "Attacking columns 1:4301 out of 4301 columns (run 1 out of 1)\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 1, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0xfb, peak: 0.783756 @ 1090\n",
      "rank:   2, candidate: 0x70, peak: 0.264503 @ 3566\n",
      "rank:   3, candidate: 0x2f, peak: 0.237630 @ 112\n",
      "rank:   4, candidate: 0xae, peak: 0.236492 @ 1096\n",
      "rank:   5, candidate: 0x7c, peak: 0.232591 @ 133\n",
      "recovered key material: fb\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 2, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x22, peak: 0.599933 @ 2148\n",
      "rank:   2, candidate: 0x95, peak: 0.251147 @ 322\n",
      "rank:   3, candidate: 0x21, peak: 0.232256 @ 1076\n",
      "rank:   4, candidate: 0xe4, peak: 0.223667 @ 3708\n",
      "rank:   5, candidate: 0xfc, peak: 0.220000 @ 2302\n",
      "recovered key material: 22\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 3, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x88, peak: 0.706023 @ 1813\n",
      "rank:   2, candidate: 0x0c, peak: 0.232518 @ 4289\n",
      "rank:   3, candidate: 0xbc, peak: 0.224680 @ 366\n",
      "rank:   4, candidate: 0xc3, peak: 0.219267 @ 2100\n",
      "rank:   5, candidate: 0xe3, peak: 0.216936 @ 1607\n",
      "recovered key material: 88\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 4, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0xb9, peak: 0.761223 @ 1058\n",
      "rank:   2, candidate: 0x76, peak: 0.238563 @ 745\n",
      "rank:   3, candidate: 0x4c, peak: 0.236807 @ 1058\n",
      "rank:   4, candidate: 0x1e, peak: 0.235831 @ 735\n",
      "rank:   5, candidate: 0x93, peak: 0.231217 @ 745\n",
      "recovered key material: b9\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 5, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0xbf, peak: 0.640751 @ 1431\n",
      "rank:   2, candidate: 0xdf, peak: 0.236335 @ 164\n",
      "rank:   3, candidate: 0x30, peak: 0.229520 @ 1189\n",
      "rank:   4, candidate: 0x4b, peak: 0.228237 @ 160\n",
      "rank:   5, candidate: 0xa2, peak: 0.226449 @ 188\n",
      "recovered key material: bf\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 6, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x47, peak: 0.687008 @ 1111\n",
      "rank:   2, candidate: 0x8e, peak: 0.265410 @ 1112\n",
      "rank:   3, candidate: 0x5a, peak: 0.225404 @ 1847\n",
      "rank:   4, candidate: 0x9c, peak: 0.223693 @ 393\n",
      "rank:   5, candidate: 0xf8, peak: 0.220136 @ 4121\n",
      "recovered key material: 47\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 7, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x33, peak: 0.546909 @ 609\n",
      "rank:   2, candidate: 0x0d, peak: 0.275984 @ 609\n",
      "rank:   3, candidate: 0x30, peak: 0.212615 @ 604\n",
      "rank:   4, candidate: 0xf9, peak: 0.210561 @ 589\n",
      "rank:   5, candidate: 0x2e, peak: 0.208324 @ 609\n",
      "recovered key material: 33\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 8, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x87, peak: 0.647548 @ 1051\n",
      "rank:   2, candidate: 0x5c, peak: 0.261099 @ 814\n",
      "rank:   3, candidate: 0xb2, peak: 0.256793 @ 800\n",
      "rank:   4, candidate: 0xf2, peak: 0.233776 @ 800\n",
      "rank:   5, candidate: 0x14, peak: 0.231443 @ 815\n",
      "recovered key material: 87\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 9, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0xe8, peak: 0.582239 @ 1953\n",
      "rank:   2, candidate: 0x26, peak: 0.212687 @ 400\n",
      "rank:   3, candidate: 0x0d, peak: 0.211739 @ 232\n",
      "rank:   4, candidate: 0x2a, peak: 0.209590 @ 2088\n",
      "rank:   5, candidate: 0x77, peak: 0.207494 @ 1866\n",
      "recovered key material: e8\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 10, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x41, peak: 0.670207 @ 1574\n",
      "rank:   2, candidate: 0xad, peak: 0.236485 @ 422\n",
      "rank:   3, candidate: 0x18, peak: 0.234291 @ 422\n",
      "rank:   4, candidate: 0x81, peak: 0.229614 @ 424\n",
      "rank:   5, candidate: 0x1b, peak: 0.228707 @ 421\n",
      "recovered key material: 41\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 11, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x4b, peak: 0.681056 @ 1123\n",
      "rank:   2, candidate: 0xbe, peak: 0.245803 @ 1123\n",
      "rank:   3, candidate: 0xca, peak: 0.243395 @ 653\n",
      "rank:   4, candidate: 0x33, peak: 0.233760 @ 992\n",
      "rank:   5, candidate: 0x7b, peak: 0.219718 @ 653\n",
      "recovered key material: 4b\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 12, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x9b, peak: 0.560986 @ 2488\n",
      "rank:   2, candidate: 0x39, peak: 0.267571 @ 842\n",
      "rank:   3, candidate: 0xc9, peak: 0.238731 @ 864\n",
      "rank:   4, candidate: 0x6e, peak: 0.233356 @ 2488\n",
      "rank:   5, candidate: 0x23, peak: 0.224947 @ 2539\n",
      "recovered key material: 9b\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 13, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x0b, peak: 0.575910 @ 269\n",
      "rank:   2, candidate: 0x79, peak: 0.278665 @ 293\n",
      "rank:   3, candidate: 0x6e, peak: 0.256535 @ 293\n",
      "rank:   4, candidate: 0xa1, peak: 0.233530 @ 292\n",
      "rank:   5, candidate: 0x73, peak: 0.229170 @ 293\n",
      "recovered key material: 0b\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 14, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0xf2, peak: 0.622311 @ 1801\n",
      "rank:   2, candidate: 0x35, peak: 0.246250 @ 474\n",
      "rank:   3, candidate: 0xed, peak: 0.233435 @ 3367\n",
      "rank:   4, candidate: 0x23, peak: 0.232825 @ 472\n",
      "rank:   5, candidate: 0x46, peak: 0.224262 @ 504\n",
      "recovered key material: f2\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 15, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x0f, peak: 0.651129 @ 1468\n",
      "rank:   2, candidate: 0xdb, peak: 0.257177 @ 715\n",
      "rank:   3, candidate: 0x0d, peak: 0.244313 @ 685\n",
      "rank:   4, candidate: 0x61, peak: 0.240010 @ 685\n",
      "rank:   5, candidate: 0x7c, peak: 0.239733 @ 685\n",
      "recovered key material: 0f\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (1515 rows consumed)\n",
      "target: 16, phase: 1, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x6f, peak: 0.598681 @ 1032\n",
      "rank:   2, candidate: 0x79, peak: 0.250492 @ 935\n",
      "rank:   3, candidate: 0xa0, peak: 0.236100 @ 895\n",
      "rank:   4, candidate: 0x42, peak: 0.233837 @ 935\n",
      "rank:   5, candidate: 0x9f, peak: 0.231389 @ 935\n",
      "recovered key material: 6f\n",
      "\n",
      "phase: 2 / 2, #targets 16\n",
      "phase input: fb2288b9bf473387e8414b9b0bf20f6f\n",
      "\n",
      "Attacking columns 1:4301 out of 4301 columns (run 1 out of 1)\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 1, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x76, peak: 0.436601 @ 3408\n",
      "rank:   2, candidate: 0x7f, peak: 0.223219 @ 4075\n",
      "rank:   3, candidate: 0xf1, peak: 0.222214 @ 3422\n",
      "rank:   4, candidate: 0x88, peak: 0.220304 @ 3401\n",
      "rank:   5, candidate: 0x16, peak: 0.220113 @ 1932\n",
      "recovered key material: 76\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 2, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x8a, peak: 0.549574 @ 3618\n",
      "rank:   2, candidate: 0xea, peak: 0.256240 @ 3613\n",
      "rank:   3, candidate: 0xfe, peak: 0.245311 @ 3613\n",
      "rank:   4, candidate: 0x21, peak: 0.228436 @ 3631\n",
      "rank:   5, candidate: 0xe0, peak: 0.226822 @ 468\n",
      "recovered key material: 8a\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 3, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0xe1, peak: 0.547180 @ 4283\n",
      "rank:   2, candidate: 0x8d, peak: 0.261055 @ 3821\n",
      "rank:   3, candidate: 0xc9, peak: 0.242233 @ 4269\n",
      "rank:   4, candidate: 0xb6, peak: 0.230010 @ 2618\n",
      "rank:   5, candidate: 0x4b, peak: 0.213551 @ 984\n",
      "recovered key material: e1\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 4, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x35, peak: 0.513289 @ 4057\n",
      "rank:   2, candidate: 0x79, peak: 0.257279 @ 4024\n",
      "rank:   3, candidate: 0x75, peak: 0.252306 @ 4050\n",
      "rank:   4, candidate: 0x0b, peak: 0.248047 @ 2657\n",
      "rank:   5, candidate: 0xba, peak: 0.232239 @ 1689\n",
      "recovered key material: 35\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 5, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x37, peak: 0.623074 @ 3477\n",
      "rank:   2, candidate: 0x29, peak: 0.240013 @ 2147\n",
      "rank:   3, candidate: 0x5a, peak: 0.238575 @ 3598\n",
      "rank:   4, candidate: 0x9e, peak: 0.230346 @ 3458\n",
      "rank:   5, candidate: 0x50, peak: 0.213498 @ 3472\n",
      "recovered key material: 37\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 6, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x2a, peak: 0.575006 @ 3668\n",
      "rank:   2, candidate: 0x0b, peak: 0.229948 @ 3682\n",
      "rank:   3, candidate: 0x83, peak: 0.224379 @ 4087\n",
      "rank:   4, candidate: 0x14, peak: 0.221732 @ 3681\n",
      "rank:   5, candidate: 0x52, peak: 0.213445 @ 3308\n",
      "recovered key material: 2a\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 7, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x64, peak: 0.512470 @ 3879\n",
      "rank:   2, candidate: 0x11, peak: 0.269333 @ 4289\n",
      "rank:   3, candidate: 0xdc, peak: 0.228579 @ 2542\n",
      "rank:   4, candidate: 0x48, peak: 0.225753 @ 3873\n",
      "rank:   5, candidate: 0x22, peak: 0.213239 @ 4289\n",
      "recovered key material: 64\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 8, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0xce, peak: 0.517127 @ 4088\n",
      "rank:   2, candidate: 0x97, peak: 0.287037 @ 4081\n",
      "rank:   3, candidate: 0xa2, peak: 0.253167 @ 4081\n",
      "rank:   4, candidate: 0x44, peak: 0.249968 @ 1307\n",
      "rank:   5, candidate: 0x99, peak: 0.224107 @ 4081\n",
      "recovered key material: ce\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 9, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x44, peak: 0.449735 @ 3508\n",
      "rank:   2, candidate: 0xd6, peak: 0.221290 @ 3626\n",
      "rank:   3, candidate: 0x70, peak: 0.219042 @ 3522\n",
      "rank:   4, candidate: 0x65, peak: 0.212436 @ 730\n",
      "rank:   5, candidate: 0x5d, peak: 0.209349 @ 3522\n",
      "recovered key material: 44\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 10, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x75, peak: 0.548380 @ 3737\n",
      "rank:   2, candidate: 0xf3, peak: 0.251344 @ 2987\n",
      "rank:   3, candidate: 0xf0, peak: 0.241172 @ 1843\n",
      "rank:   4, candidate: 0x78, peak: 0.239921 @ 3027\n",
      "rank:   5, candidate: 0x69, peak: 0.231353 @ 3732\n",
      "recovered key material: 75\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 11, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0xa3, peak: 0.599237 @ 4277\n",
      "rank:   2, candidate: 0x4c, peak: 0.238604 @ 4277\n",
      "rank:   3, candidate: 0x31, peak: 0.215655 @ 3324\n",
      "rank:   4, candidate: 0x7e, peak: 0.211560 @ 3942\n",
      "rank:   5, candidate: 0x16, peak: 0.211002 @ 4278\n",
      "recovered key material: a3\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 12, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0xcf, peak: 0.601499 @ 4157\n",
      "rank:   2, candidate: 0xbb, peak: 0.235398 @ 4133\n",
      "rank:   3, candidate: 0x12, peak: 0.235173 @ 4133\n",
      "rank:   4, candidate: 0x22, peak: 0.229896 @ 4133\n",
      "rank:   5, candidate: 0x8e, peak: 0.226669 @ 4133\n",
      "recovered key material: cf\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 13, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x7b, peak: 0.455439 @ 3558\n",
      "rank:   2, candidate: 0xfa, peak: 0.288024 @ 3582\n",
      "rank:   3, candidate: 0xa0, peak: 0.238848 @ 3582\n",
      "rank:   4, candidate: 0x4a, peak: 0.238010 @ 3582\n",
      "rank:   5, candidate: 0x53, peak: 0.230091 @ 3194\n",
      "recovered key material: 7b\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 14, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x22, peak: 0.482869 @ 3768\n",
      "rank:   2, candidate: 0x73, peak: 0.224972 @ 3761\n",
      "rank:   3, candidate: 0x44, peak: 0.224435 @ 3761\n",
      "rank:   4, candidate: 0x6c, peak: 0.219847 @ 3618\n",
      "rank:   5, candidate: 0x47, peak: 0.219352 @ 3793\n",
      "recovered key material: 22\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 15, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x20, peak: 0.564326 @ 3978\n",
      "rank:   2, candidate: 0xdc, peak: 0.301486 @ 4002\n",
      "rank:   3, candidate: 0x8a, peak: 0.237271 @ 4003\n",
      "rank:   4, candidate: 0x90, peak: 0.233361 @ 3968\n",
      "rank:   5, candidate: 0x02, peak: 0.232899 @ 4002\n",
      "recovered key material: 20\n",
      "CPA on samples shape (500, 4301) (range 1:4301) and data shape (500,)\n",
      "Results @ 500 rows, 4301 cols (500 rows consumed)\n",
      "target: 16, phase: 2, #candidates 256, \"Sbox out\"\n",
      "rank:   1, candidate: 0x63, peak: 0.475374 @ 4187\n",
      "rank:   2, candidate: 0x2b, peak: 0.239576 @ 4223\n",
      "rank:   3, candidate: 0x29, peak: 0.232466 @ 4224\n",
      "rank:   4, candidate: 0x57, peak: 0.225408 @ 4224\n",
      "rank:   5, candidate: 0x95, peak: 0.213894 @ 3637\n",
      "recovered key material: 63\n",
      "recovered key: fb2288b9bf473387e8414b9b0bf20f6f768ae135372a64ce4475a3cf7b222063\n"
     ]
    }
   ],
   "source": [
    "params = DpaAttack(AesSboxAttack(), CPA())\n",
    "params.attack.mode = CIPHER       # attack encrypt\n",
    "params.attack.keyLength = KL256\n",
    "params.dataOffset = 1             # the input data is at the beginning\n",
    "params.attack.direction = FORWARD # attack the start of encrypt, not the end\n",
    "\n",
    "params.analysis.leakages = [HW()]\n",
    "params.maximization = AbsoluteGlobalMaximization()\n",
    "\n",
    "range = 1300:5600 # we need to include the first two rounds\n",
    "addSamplePass(trs, x -> x[range])\n",
    "sca(trs, params, 1, length(trs))\n",
    "popSamplePass(trs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the correlations, they're pretty solid, but we don't have the flag yet. What we have is the masked first round key, and the actual second round key. The reason this works, is because the second round key is derived using the expected input to the second round SBox, which Jlsca now can accurately compute.\n",
    "\n",
    "We on the other hand, want the key, which we can derive from the second round key by reversing the key schedule:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recovered key: 2c66704041a085fb735fc7013f5783ac\n",
      "Which is the correct flag."
     ]
    }
   ],
   "source": [
    "phaseInput = get(params.phaseInput)\n",
    "maskedRoundKey1 = phaseInput[1:16]\n",
    "roundKey2 = phaseInput[17:32]\n",
    "roundKeyLength = div(length(roundKey2),Aes.wz)\n",
    "keySchedule = KeyExpansionBackwards(roundKey2, Aes.keylength2Nr(length(roundKey2)), roundKeyLength, roundKeyLength)\n",
    "finalKey = keySchedule[1:16]\n",
    "print(\"Recovered key: \", bytes2hex(finalKey),\"\\n\")\n",
    "if finalKey == hex2bytes(\"2c66704041a085fb735fc7013f5783ac\")\n",
    "    print(\"Which is the correct flag.\")\n",
    "else\n",
    "    print(\"but something messed up!\")\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Can we prove it?\n",
    "Yes. Just for fun, we'll prove it's the right key, by checking from the other side, deriving the masks, and doing an encryption. To do that, we need to recover the input and output masks. We can recover the input mask already, but we need to repeat the SCA above on the last two rounds to get the output mask:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Jlsca running in Julia version: 0.6.2, 1 processes/1 workers/1 threads per worker\n",
      "\n",
      "DPA parameters\n",
      "attack:       AES Sbox\n",
      "mode:         CIPHER\n",
      "key length:   KL256\n",
      "direction:    BACKWARD\n",
      "xor:          false\n",
      "analysis:     CPA\n",
      "leakages:     HW\n",
      "maximization: abs global max\n",
      "data at:      17\n",
      "\n",
      "phase: 1 / 2, #targets 16\n",
      "\n",
      "Attacking columns 1:4501 out of 4501 columns (run 1 out of 1)\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 1, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x13, peak: 0.648035 @ 3520\n",
      "rank:   2, candidate: 0xc2, peak: 0.213914 @ 3521\n",
      "rank:   3, candidate: 0xc4, peak: 0.212886 @ 1669\n",
      "rank:   4, candidate: 0x9a, peak: 0.209826 @ 2294\n",
      "rank:   5, candidate: 0xd1, peak: 0.209307 @ 3520\n",
      "recovered key material: 13\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 2, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x59, peak: 0.671923 @ 3781\n",
      "rank:   2, candidate: 0xe8, peak: 0.225108 @ 3734\n",
      "rank:   3, candidate: 0x67, peak: 0.208538 @ 3649\n",
      "rank:   4, candidate: 0x61, peak: 0.207042 @ 3784\n",
      "rank:   5, candidate: 0x88, peak: 0.202874 @ 2893\n",
      "recovered key material: 59\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 3, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x8e, peak: 0.726778 @ 4041\n",
      "rank:   2, candidate: 0x09, peak: 0.219684 @ 696\n",
      "rank:   3, candidate: 0x63, peak: 0.212466 @ 4031\n",
      "rank:   4, candidate: 0x11, peak: 0.211726 @ 4070\n",
      "rank:   5, candidate: 0xfd, peak: 0.210845 @ 4070\n",
      "recovered key material: 8e\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 4, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0xd2, peak: 0.816352 @ 4303\n",
      "rank:   2, candidate: 0x0d, peak: 0.222437 @ 4303\n",
      "rank:   3, candidate: 0xa1, peak: 0.221624 @ 4347\n",
      "rank:   4, candidate: 0xba, peak: 0.219283 @ 4303\n",
      "rank:   5, candidate: 0xae, peak: 0.217962 @ 3280\n",
      "recovered key material: d2\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 5, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x6d, peak: 0.627123 @ 3563\n",
      "rank:   2, candidate: 0xaf, peak: 0.232613 @ 3573\n",
      "rank:   3, candidate: 0x28, peak: 0.226990 @ 2228\n",
      "rank:   4, candidate: 0x96, peak: 0.213136 @ 2446\n",
      "rank:   5, candidate: 0xfa, peak: 0.211622 @ 536\n",
      "recovered key material: 6d\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 6, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0xcb, peak: 0.477905 @ 3148\n",
      "rank:   2, candidate: 0x3a, peak: 0.223686 @ 3822\n",
      "rank:   3, candidate: 0x82, peak: 0.223091 @ 2199\n",
      "rank:   4, candidate: 0x73, peak: 0.218425 @ 1225\n",
      "rank:   5, candidate: 0xa8, peak: 0.215148 @ 3841\n",
      "recovered key material: cb\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 7, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0xd0, peak: 0.482701 @ 4091\n",
      "rank:   2, candidate: 0xb2, peak: 0.281889 @ 4094\n",
      "rank:   3, candidate: 0x52, peak: 0.232802 @ 4471\n",
      "rank:   4, candidate: 0x4f, peak: 0.221060 @ 2454\n",
      "rank:   5, candidate: 0xa1, peak: 0.205847 @ 2828\n",
      "recovered key material: d0\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 8, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0xb2, peak: 0.602101 @ 2832\n",
      "rank:   2, candidate: 0xaa, peak: 0.237829 @ 708\n",
      "rank:   3, candidate: 0xaf, peak: 0.218807 @ 4146\n",
      "rank:   4, candidate: 0x11, peak: 0.208193 @ 4176\n",
      "rank:   5, candidate: 0x2b, peak: 0.207881 @ 3869\n",
      "recovered key material: b2\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 9, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x8f, peak: 0.845099 @ 3621\n",
      "rank:   2, candidate: 0x5e, peak: 0.236399 @ 3620\n",
      "rank:   3, candidate: 0x51, peak: 0.233632 @ 3069\n",
      "rank:   4, candidate: 0x02, peak: 0.220906 @ 3620\n",
      "rank:   5, candidate: 0x65, peak: 0.217956 @ 3620\n",
      "recovered key material: 8f\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 10, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0xa9, peak: 0.778461 @ 3882\n",
      "rank:   2, candidate: 0xcd, peak: 0.241395 @ 3881\n",
      "rank:   3, candidate: 0x78, peak: 0.240589 @ 3881\n",
      "rank:   4, candidate: 0xbe, peak: 0.219501 @ 2833\n",
      "rank:   5, candidate: 0x4f, peak: 0.213952 @ 4379\n",
      "recovered key material: a9\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 11, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x69, peak: 0.694121 @ 3937\n",
      "rank:   2, candidate: 0xe4, peak: 0.230022 @ 2745\n",
      "rank:   3, candidate: 0x78, peak: 0.218979 @ 1014\n",
      "rank:   4, candidate: 0x4a, peak: 0.215929 @ 2568\n",
      "rank:   5, candidate: 0x72, peak: 0.208881 @ 989\n",
      "recovered key material: 69\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 12, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x43, peak: 0.770762 @ 4202\n",
      "rank:   2, candidate: 0x2d, peak: 0.253867 @ 4205\n",
      "rank:   3, candidate: 0x00, peak: 0.226053 @ 4207\n",
      "rank:   4, candidate: 0xdb, peak: 0.218946 @ 4205\n",
      "rank:   5, candidate: 0xc7, peak: 0.218611 @ 1457\n",
      "recovered key material: 43\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 13, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x80, peak: 0.678557 @ 3671\n",
      "rank:   2, candidate: 0x2a, peak: 0.242141 @ 3273\n",
      "rank:   3, candidate: 0x6c, peak: 0.214767 @ 3673\n",
      "rank:   4, candidate: 0x4e, peak: 0.208071 @ 3817\n",
      "rank:   5, candidate: 0xf0, peak: 0.207611 @ 349\n",
      "recovered key material: 80\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 14, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x59, peak: 0.612785 @ 2719\n",
      "rank:   2, candidate: 0xc4, peak: 0.232368 @ 4351\n",
      "rank:   3, candidate: 0x5c, peak: 0.228133 @ 4018\n",
      "rank:   4, candidate: 0x95, peak: 0.223800 @ 2876\n",
      "rank:   5, candidate: 0x96, peak: 0.222122 @ 1394\n",
      "recovered key material: 59\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 15, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0xfc, peak: 0.529505 @ 3985\n",
      "rank:   2, candidate: 0xaf, peak: 0.218610 @ 4433\n",
      "rank:   3, candidate: 0x08, peak: 0.214234 @ 3909\n",
      "rank:   4, candidate: 0x95, peak: 0.210364 @ 3736\n",
      "rank:   5, candidate: 0x93, peak: 0.208388 @ 1650\n",
      "recovered key material: fc\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 16, phase: 1, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x4a, peak: 0.437761 @ 3264\n",
      "rank:   2, candidate: 0xec, peak: 0.226553 @ 4452\n",
      "rank:   3, candidate: 0x47, peak: 0.222689 @ 800\n",
      "rank:   4, candidate: 0x45, peak: 0.221956 @ 1811\n",
      "rank:   5, candidate: 0xbf, peak: 0.213848 @ 4259\n",
      "recovered key material: 4a\n",
      "\n",
      "phase: 2 / 2, #targets 16\n",
      "phase input: 13598ed26dcbd0b28fa969438059fc4a\n",
      "\n",
      "Attacking columns 1:4501 out of 4501 columns (run 1 out of 1)\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 1, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x12, peak: 0.516947 @ 222\n",
      "rank:   2, candidate: 0x8e, peak: 0.238290 @ 1261\n",
      "rank:   3, candidate: 0x77, peak: 0.230839 @ 1208\n",
      "rank:   4, candidate: 0x00, peak: 0.225810 @ 1204\n",
      "rank:   5, candidate: 0x2f, peak: 0.223021 @ 40\n",
      "recovered key material: 12\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 2, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0xfa, peak: 0.375456 @ 480\n",
      "rank:   2, candidate: 0x5a, peak: 0.246035 @ 1386\n",
      "rank:   3, candidate: 0x63, peak: 0.215348 @ 1379\n",
      "rank:   4, candidate: 0x06, peak: 0.209752 @ 2157\n",
      "rank:   5, candidate: 0x20, peak: 0.209066 @ 3573\n",
      "recovered key material: fa\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 3, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x5d, peak: 0.543924 @ 750\n",
      "rank:   2, candidate: 0xbe, peak: 0.226511 @ 1407\n",
      "rank:   3, candidate: 0xb0, peak: 0.220112 @ 772\n",
      "rank:   4, candidate: 0x1f, peak: 0.218677 @ 1343\n",
      "rank:   5, candidate: 0xc1, peak: 0.216119 @ 1453\n",
      "recovered key material: 5d\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 4, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x2d, peak: 0.604432 @ 1303\n",
      "rank:   2, candidate: 0x31, peak: 0.241144 @ 1417\n",
      "rank:   3, candidate: 0xbb, peak: 0.234085 @ 3818\n",
      "rank:   4, candidate: 0x16, peak: 0.230491 @ 1562\n",
      "rank:   5, candidate: 0x32, peak: 0.221908 @ 2921\n",
      "recovered key material: 2d\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 5, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0xfb, peak: 0.683341 @ 279\n",
      "rank:   2, candidate: 0x88, peak: 0.230506 @ 302\n",
      "rank:   3, candidate: 0x08, peak: 0.224614 @ 1551\n",
      "rank:   4, candidate: 0xc9, peak: 0.212660 @ 293\n",
      "rank:   5, candidate: 0x92, peak: 0.211135 @ 1556\n",
      "recovered key material: fb\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 6, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x69, peak: 0.456708 @ 541\n",
      "rank:   2, candidate: 0xfa, peak: 0.208125 @ 817\n",
      "rank:   3, candidate: 0xca, peak: 0.206815 @ 1732\n",
      "rank:   4, candidate: 0x65, peak: 0.206792 @ 651\n",
      "rank:   5, candidate: 0xb5, peak: 0.206484 @ 1735\n",
      "recovered key material: 69\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 7, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x81, peak: 0.665428 @ 800\n",
      "rank:   2, candidate: 0xf2, peak: 0.257043 @ 804\n",
      "rank:   3, candidate: 0xe5, peak: 0.237376 @ 799\n",
      "rank:   4, candidate: 0xc1, peak: 0.225711 @ 833\n",
      "rank:   5, candidate: 0x5e, peak: 0.221181 @ 1689\n",
      "recovered key material: 81\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 8, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x80, peak: 0.799096 @ 860\n",
      "rank:   2, candidate: 0x08, peak: 0.234896 @ 859\n",
      "rank:   3, candidate: 0xde, peak: 0.228623 @ 1871\n",
      "rank:   4, candidate: 0x45, peak: 0.219556 @ 903\n",
      "rank:   5, candidate: 0x5f, peak: 0.211058 @ 860\n",
      "recovered key material: 80\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 9, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x0b, peak: 0.614538 @ 328\n",
      "rank:   2, candidate: 0x9d, peak: 0.243682 @ 2594\n",
      "rank:   3, candidate: 0x41, peak: 0.235373 @ 4477\n",
      "rank:   4, candidate: 0xa7, peak: 0.225663 @ 1509\n",
      "rank:   5, candidate: 0x95, peak: 0.222951 @ 1954\n",
      "recovered key material: 0b\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 10, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x09, peak: 0.582146 @ 589\n",
      "rank:   2, candidate: 0xab, peak: 0.243851 @ 2079\n",
      "rank:   3, candidate: 0xb4, peak: 0.238217 @ 2072\n",
      "rank:   4, candidate: 0x53, peak: 0.218701 @ 265\n",
      "rank:   5, candidate: 0x94, peak: 0.215562 @ 1922\n",
      "recovered key material: 09\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 11, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x04, peak: 0.636198 @ 643\n",
      "rank:   2, candidate: 0x64, peak: 0.243126 @ 1935\n",
      "rank:   3, candidate: 0xd9, peak: 0.233054 @ 1934\n",
      "rank:   4, candidate: 0x8a, peak: 0.227336 @ 2036\n",
      "rank:   5, candidate: 0xad, peak: 0.223531 @ 3699\n",
      "recovered key material: 04\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 12, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x8e, peak: 0.443672 @ 902\n",
      "rank:   2, candidate: 0xed, peak: 0.219113 @ 919\n",
      "rank:   3, candidate: 0x03, peak: 0.217648 @ 1776\n",
      "rank:   4, candidate: 0xe6, peak: 0.209976 @ 3537\n",
      "rank:   5, candidate: 0xec, peak: 0.208945 @ 912\n",
      "recovered key material: 8e\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 13, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0xfc, peak: 0.760583 @ 379\n",
      "rank:   2, candidate: 0xee, peak: 0.242139 @ 1159\n",
      "rank:   3, candidate: 0x82, peak: 0.234354 @ 2443\n",
      "rank:   4, candidate: 0xe0, peak: 0.218913 @ 2300\n",
      "rank:   5, candidate: 0xe7, peak: 0.218483 @ 2066\n",
      "recovered key material: fc\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 14, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0xc5, peak: 0.717383 @ 439\n",
      "rank:   2, candidate: 0x34, peak: 0.242969 @ 462\n",
      "rank:   3, candidate: 0x59, peak: 0.242371 @ 1059\n",
      "rank:   4, candidate: 0x1a, peak: 0.217530 @ 438\n",
      "rank:   5, candidate: 0x58, peak: 0.216458 @ 1061\n",
      "recovered key material: c5\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 15, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x95, peak: 0.674761 @ 700\n",
      "rank:   2, candidate: 0xb4, peak: 0.243914 @ 2382\n",
      "rank:   3, candidate: 0xb5, peak: 0.219008 @ 3431\n",
      "rank:   4, candidate: 0xf6, peak: 0.217841 @ 2382\n",
      "rank:   5, candidate: 0xd7, peak: 0.217745 @ 3154\n",
      "recovered key material: 95\n",
      "CPA on samples shape (500, 4501) (range 1:4501) and data shape (500,)\n",
      "Results @ 500 rows, 4501 cols (500 rows consumed)\n",
      "target: 16, phase: 2, #candidates 256, \"Inverse sbox out\"\n",
      "rank:   1, candidate: 0x82, peak: 0.498074 @ 959\n",
      "rank:   2, candidate: 0x20, peak: 0.225933 @ 2562\n",
      "rank:   3, candidate: 0xe1, peak: 0.223018 @ 988\n",
      "rank:   4, candidate: 0x43, peak: 0.219782 @ 1162\n",
      "rank:   5, candidate: 0xf1, peak: 0.209448 @ 981\n",
      "recovered key material: 82\n",
      "recovered key: eeb0c6c70976682b3e3f4cf28f4432ae4d1317184dbeb3bbea89c08954d09a4c\n"
     ]
    }
   ],
   "source": [
    "backParams = DpaAttack(AesSboxAttack(), CPA())\n",
    "backParams.attack.mode = CIPHER        # attack encrypt\n",
    "backParams.attack.keyLength = KL256\n",
    "backParams.dataOffset = 17             # the output data is at the end\n",
    "backParams.attack.direction = BACKWARD # attack the end of encrypt\n",
    "\n",
    "backParams.analysis.leakages = [HW()]\n",
    "backParams.maximization = AbsoluteGlobalMaximization()\n",
    "\n",
    "range = 27500:32000 # we need to include the last two rounds\n",
    "addSamplePass(trs, x -> x[range])\n",
    "sca(trs, backParams, 1, length(trs))\n",
    "popSamplePass(trs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recovered key: 2c66704041a085fb735fc7013f5783ac\n",
      "Which matches the forward direction."
     ]
    }
   ],
   "source": [
    "backPhaseInput = get(backParams.phaseInput)\n",
    "maskedRoundKey11 = backPhaseInput[1:16]\n",
    "roundKey10 = reshape(Aes.MixColumns(reshape(backPhaseInput[17:32], (4,4))), 16)\n",
    "roundKeyLength = div(length(roundKey10),Aes.wz)\n",
    "backKeySchedule = KeyExpansionBackwards(roundKey10, Aes.keylength2Nr(length(roundKey10)), roundKeyLength, roundKeyLength*9)\n",
    "\n",
    "backKey = keySchedule[1:16]\n",
    "print(\"Recovered key: \", bytes2hex(backKey),\"\\n\")\n",
    "if backKey == finalKey\n",
    "    print(\"Which matches the forward direction.\")\n",
    "else\n",
    "    print(\"but something messed up!\")\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note the bit of hackery above. The \"recovered key material\" isn't the 10th round key, it's the InvMixColumns of the 10th round key. This is because the code is designed to be able to keep going to the 9th, 8th, etc, so it has to deal in complete rounds, but the last round is an abbreviated round. We fix that by applying MixColumns to it.\n",
    "\n",
    "And now, to derive the output masks:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Successful decrypt with key: 2c66704041a085fb735fc7013f5783ac\n",
      "Input mask: d744f8f9fee7b67c9b1e8c9a34a58cc3\n",
      "Output mask: d744f8f9fee7b67c9b1e8c9a34a58cc3\n"
     ]
    }
   ],
   "source": [
    "# Check the key to see if it decrypts the data\n",
    "keySchedule = KeyExpansion(finalKey, Aes.keylength2Nr(length(roundKey2)), roundKeyLength)\n",
    "inputMask = xor.(maskedRoundKey1, keySchedule[1:16])\n",
    "outputMask = xor.(maskedRoundKey11, keySchedule[161:176])\n",
    "plaintext = trs[1][1][1:16]\n",
    "ciphertext = trs[1][1][17:32]\n",
    "\n",
    "w = KeyExpansion(finalKey, 10, 4)\n",
    "if Cipher(xor.(plaintext, inputMask), w) == xor.(ciphertext, outputMask)\n",
    "    print(\"Successful decrypt with key: \",bytes2hex(finalKey),\"\\n\")\n",
    "    print(\"Input mask: \",bytes2hex(inputMask),\"\\n\")\n",
    "    print(\"Output mask: \",bytes2hex(outputMask),\"\\n\")\n",
    "else\n",
    "    print(\"Failure! Recovered key: \",bytes2hex(finalKey),\" does not match the data\\n\")\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Solved."
   ]
  }
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