ThetaS-firmware-opening.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "DECIMAL       HEXADECIMAL     DESCRIPTION\n",
      "--------------------------------------------------------------------------------\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!binwalk ap1_v131.frm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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R6hvTtEaj0zbSdBYKbPLCt0eqy5YtLBUMfX/6afz8+OPyOojIJhCUzsRtf/44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\nMngwwFFH+ffxcxMAFy5Mzs/IC91tINKUnrQLPHGmKpo50zm3bNooVb1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WAAAg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\naxAHk5GRodTU1NbRwADc6f8DAmsL7iun9oQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image at 0x7f82f4d6de10>"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename='entropy.png')\n",
    "# entropy.png was generated from binwalk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "UNITY FILE V1.10 / RICOH COMPANY\u0000O8\u0000\u0000\u0000\u0000\u0002������������������������\u0000\u0000\u0000\u0004\u0000*R@z01firm6\u0000\u0000\u0000 ENQ'ENENQ'\u0001\u0001��������������������������������\u0000\u0000\u0015.\u0000$�\u0000ap1_v131up\u0000 ENQ'ENENQ'�\u0001�����������������������������������������������������������������������������������������������\n",
      "--------------------------------------------------------------------------------\n",
      "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\n"
     ]
    }
   ],
   "source": [
    "data = open('ap1_v131.frm','rb').read()\n",
    "import binascii\n",
    "print data[:0xff]\n",
    "print '-'*80\n",
    "print binascii.hexlify(data[:0xff])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def hexdump(src, offset=0, length=16):\n",
    "    FILTER = ''.join([(len(repr(chr(x))) == 3) and chr(x) or '.' for x in range(256)])\n",
    "    lines = []\n",
    "    for c in xrange(0, len(src), length):\n",
    "        chars = src[c:c+length]\n",
    "        hex = ' '.join([\"%02x\" % ord(x) for x in chars])\n",
    "        printable = ''.join([\"%s\" % ((ord(x) <= 127 and FILTER[ord(x)]) or '.') for x in chars])\n",
    "        lines.append(\"%04x  %-*s  %s\\n\" % (c+offset, length*3, hex, printable))\n",
    "    return ''.join(lines)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 0000  11 22 33 44 11 22 33 44 11 22 33 44               .\"3D.\"3D.\"3D\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from itertools import cycle\n",
    "def xor(data, key):\n",
    "    return ''.join([chr(ord(c1) ^ ord(c2)) for c1,c2 in zip(data, cycle(key))])\n",
    "print hexdump(xor('\\x00'*12,'\\x11\\x22\\x33\\x44'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0000  55 4e 49 54 59 20 46 49 4c 45 20 56 31 2e 31 30   UNITY FILE V1.10\n",
      "0010  20 2f 20 52 49 43 4f 48 20 43 4f 4d 50 41 4e 59    / RICOH COMPANY\n",
      "0020  00 4f 38 00 00 00 00 02 ff ff ff ff ff ff ff ff   .O8.............\n",
      "0030  ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff   ................\n",
      "0040  00 00 00 04 00 2a 52 40 7a 30 31 66 69 72 6d 36   .....*R@z01firm6\n",
      "0050  00 00 00 20 45 4e 51 27 45 4e 45 4e 51 27 01 01   ... ENQ'ENENQ'..\n",
      "0060  ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff   ................\n",
      "0070  ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff   ................\n",
      "0080  00 00 15 2e 00 24 dc 00 61 70 31 5f 76 31 33 31   .....$..ap1_v131\n",
      "0090  75 70 00 20 45 4e 51 27 45 4e 45 4e 51 27 80 01   up. ENQ'ENENQ'..\n",
      "00a0  ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff   ................\n",
      "00b0  ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff   ................\n",
      "00c0  ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff   ................\n",
      "00d0  ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff   ................\n",
      "00e0  ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff   ................\n",
      "00f0  ff ff ff ff ff ff ff ff ff ff ff ff ff ff ff      ...............\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print hexdump(data[:0xff], 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0800  2a 39 57 c2 49 39 44 d7 3e 2a 53 d1 2c 29 44 92   *9W.I9D.>*S.,)D.\n",
      "0810  fa e6 97 23 f8 e6 96 12 d8 f2 86 06 f8 f6 9f 06   ...#............\n",
      "0820  f8 e6 96 12 07 19 69 ed 07 19 69 ed 07 19 69 ed   ......i...i...i.\n",
      "0830  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0840  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0850  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0860  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0870  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0880  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0890  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "08a0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "08b0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "08c0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "08d0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "08e0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "08f0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0900  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0910  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0920  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0930  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0940  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0950  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "0960  f8 e6 96 12 f8 cc c6 52 f8 cc c4 52 b1 eb 3c d7   .......R...R..<.\n",
      "0970  f8 e6 96 13 f8 e6 96 13 f8 e6 96 13 f8 e6 96 13   ................\n",
      "0980  2a 25 46 c6 4a 56 27 a1 78 66 16 92 78 66 16 92   *%F.JV'.xf..xf..\n",
      "0990  f8 e6 88 08 3a 35 26 a2 49 66 16 92 78 66 16 92   ....:5&.If..xf..\n",
      "09a0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "09b0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "09c0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "09d0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "09e0  07 19 69 ed 07 19 69 ed 07 19 69 ed 07 19 69 ed   ..i...i...i...i.\n",
      "09f0  2a 39 57 c2 49 39 43 c2 3c 27 42 d7 3c 47 37 b3   *9W.I9C.<'B.<G7.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "section1 = data[0x800:0xa00]\n",
    "print hexdump(section1, 0x800)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0800  2d 20 3e 2f 4e 20 2d 3a 39 33 3a 3c 2b 30 2d 7f   - >/N -:93:<+0-.\n",
      "0810  fd ff fe ce ff ff ff ff df eb ef eb ff ef f6 eb   ................\n",
      "0820  ff ff ff ff 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0830  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0840  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0850  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0860  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0870  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0880  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0890  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "08a0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "08b0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "08c0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "08d0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "08e0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "08f0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0900  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0910  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0920  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0930  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0940  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0950  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0960  ff ff ff ff ff d5 af bf ff d5 ad bf b6 f2 55 3a   ..............U:\n",
      "0970  ff ff ff fe ff ff ff fe ff ff ff fe ff ff ff fe   ................\n",
      "0980  2d 3c 2f 2b 4d 4f 4e 4c 7f 7f 7f 7f 7f 7f 7f 7f   -</+MONL........\n",
      "0990  ff ff e1 e5 3d 2c 4f 4f 4e 7f 7f 7f 7f 7f 7f 7f   ....=,OON.......\n",
      "09a0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "09b0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "09c0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "09d0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "09e0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "09f0  2d 20 3e 2f 4e 20 2a 2f 3b 3e 2b 3a 3b 5e 5e 5e   - >/N */;>+:;^^^\n",
      "\n"
     ]
    }
   ],
   "source": [
    "section1_xor = xor(section1, binascii.unhexlify('071969ed'))\n",
    "print hexdump(section1_xor, 0x800)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0xc00\n",
      "0a00  b7 0a 75 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   ..u.. G.. G.. G.\n",
      "0a10  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0a20  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0a30  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0a40  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0a50  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0a60  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0a70  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0a80  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0a90  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0aa0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0ab0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0ac0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0ad0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0ae0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0af0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0b00  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0b10  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0b20  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0b30  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0b40  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0b50  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0b60  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0b70  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0b80  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0b90  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0ba0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0bb0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0bc0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0bd0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0be0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "0bf0  b7 20 47 a5 b7 20 47 a5 b7 20 47 a5 b7 20 47 a5   . G.. G.. G.. G.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print hex(0xa00+0x200)\n",
    "section2 = data[0xa00:0xc00]\n",
    "print hexdump(section2, 0xa00)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0a00  00 2a 32 00 00 00 00 00 00 00 00 00 00 00 00 00   .*2.............\n",
      "0a10  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0a20  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0a30  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0a40  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0a50  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0a60  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0a70  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0a80  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0a90  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0aa0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0ab0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0ac0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0ad0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0ae0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0af0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0b00  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0b10  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0b20  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0b30  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0b40  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0b50  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0b60  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0b70  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0b80  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0b90  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0ba0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0bb0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0bc0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0bd0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0be0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "0bf0  00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00   ................\n",
      "\n"
     ]
    }
   ],
   "source": [
    "section2_xor = xor(section2, binascii.unhexlify('b72047a5'))\n",
    "print hexdump(section2_xor, 0xa00)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0c00  75 59 f9 3f 75 59 f9 39 75 59 f9 3d 75 59 f9 3c   uY.?uY.9uY.=uY.<\n",
      "0c10  75 59 f9 39 75 59 f9 38 75 59 f9 38 75 59 f9 f0   uY.9uY.8uY.8uY..\n",
      "0c20  75 59 de 28 75 59 f9 38 75 59 f9 26 75 59 f9 f0   uY.(uY.8uY.&uY..\n",
      "0c30  75 59 f9 3c 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.<uY.8uY.8uY.8\n",
      "0c40  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0c50  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0c60  75 59 f9 38 75 59 f9 3c 75 59 f9 38 75 59 f9 38   uY.8uY.<uY.8uY.8\n",
      "0c70  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0c80  75 59 f9 38 75 59 f9 38 75 59 f9 3f 75 59 f9 3f   uY.8uY.8uY.?uY.?\n",
      "0c90  75 59 f9 3f 75 59 f9 3f 75 59 f9 3c 75 59 f9 7d   uY.?uY.?uY.<uY.}\n",
      "0ca0  75 59 f9 38 75 59 f9 38 75 59 f9 38 2c 1c bf 71   uY.8uY.8uY.8,..q\n",
      "0cb0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 39   uY.8uY.8uY.8uY.9\n",
      "0cc0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 3c   uY.8uY.8uY.8uY.<\n",
      "0cd0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0ce0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0cf0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0d00  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0d10  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0d20  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0d30  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0d40  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0d50  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0d60  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0d70  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0d80  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0d90  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0da0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0db0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0dc0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0dd0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0de0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "0df0  75 59 f9 38 75 59 f9 38 75 59 f9 38 75 59 f9 38   uY.8uY.8uY.8uY.8\n",
      "\n",
      "0e00  dd 82 a5 db d0 13 aa 4b dd 92 a5 db d6 0c 5a 9f   .......K......Z.\n",
      "0e10  d6 0c ba 9f dd 8a a5 da d2 13 aa ca dd 9a a5 da   ................\n",
      "0e20  dd 82 a5 db d0 33 b2 ce d2 13 aa ca dd 92 a5 db   .....3..........\n",
      "0e30  d0 b2 5a 18 d6 0c 7a ff d0 b2 5a 10 d6 0c 7a fb   ..Z...z...Z...z.\n",
      "0e40  d0 b2 5a 1c d6 0c 7a e3 d0 b2 5a 1a d6 0c 7a eb   ..Z...z...Z...z.\n",
      "0e50  d0 b2 5a 19 d6 0c 7a d7 d0 b2 5a 14 d6 0c 7a d3   ..Z...z...Z...z.\n",
      "0e60  d9 93 aa cd d9 93 ab bc cc 6c aa db 33 93 ea cb   .........l..3...\n",
      "0e70  33 93 d6 4b cc 6c bb 8b 33 93 d7 cb 33 93 2a cb   3..K.l..3...3.*.\n",
      "0e80  d8 93 aa cb d8 93 95 38 d1 1c aa e7 db 03 a6 cb   .......8........\n",
      "0e90  d3 19 0a cb d3 18 1a cb d1 d9 da ca d2 c9 aa c0   ................\n",
      "0ea0  29 93 aa cb d8 93 95 20 db 29 aa c4 d1 dc 4a d3   )...... .)....J.\n",
      "0eb0  d0 80 aa ca 23 d4 5a c8 d2 33 5a c8 33 93 a4 4b   ....#.Z..3Z.3..K\n",
      "0ec0  33 93 a4 1b d1 c1 8a db 1b 23 aa b3 1b 32 aa b3   3........#...2..\n",
      "0ed0  b9 6c 55 30 d2 23 84 49 1b 23 aa fb 1b 32 aa fb   .lU0.#.I.#...2..\n",
      "0ee0  76 03 ea cb 76 12 ea cb d2 33 5a c5 d0 23 9a cb   v...v....3Z..#..\n",
      "0ef0  d0 23 ea cb d0 23 fa cb d0 23 ca cb d1 c1 8a db   .#...#...#......\n",
      "0f00  1b 32 aa b3 b9 6c 55 37 d2 23 84 49 1b 32 aa fb   .2...lU7.#.I.2..\n",
      "0f10  76 12 9a cb d2 33 5a c5 d6 0c ac 7f d6 03 aa cb   v....3Z.........\n",
      "0f20  d2 bc 55 d5 d6 0c bc 67 d0 33 aa c5 d6 02 bb db   ..U....g.3......\n",
      "0f30  d3 93 a3 6a d6 0c bc 6b d2 02 ba 7b d6 0c ac 57   ...j...k...{...W\n",
      "0f40  d9 93 e2 d1 d6 0c bc 53 da be ea db d3 12 ba cb   .......S........\n",
      "0f50  d0 33 aa ca d8 93 e2 59 d0 c3 aa cb 26 0c ac 4f   .3.....Y....&..O\n",
      "0f60  db 2e 2a db d6 0c 9c 4b d6 02 6a cb d6 0c 8c b7   ..*....K..j.....\n",
      "0f70  d3 10 98 4b d6 10 6a c3 d6 02 6a cf d6 10 6a cb   ...K..j...j...j.\n",
      "0f80  d6 02 9a cb d0 80 aa ca 30 33 9a ca 20 33 9a cb   ........03.. 3..\n",
      "0f90  d4 51 9a cb d6 0c 9c 93 d6 02 8a c3 d4 10 8b cb   .Q..............\n",
      "0fa0  d6 02 8a c3 d1 10 9a c3 d4 10 8b cb d6 02 ba c7   ................\n",
      "0fb0  d1 10 8a c3 d4 11 bb cb d0 33 aa cb d2 bc 55 d5   .........3....U.\n",
      "0fc0  d6 0c 8c e7 d0 33 ba cb d4 11 bb cb d1 11 8a c3   .....3..........\n",
      "0fd0  d4 11 bb cb d1 d1 8a d9 d4 51 ba cb d1 11 8a d1   .........Q......\n",
      "0fe0  d4 11 bb cb d1 d1 8a d7 d4 51 ba cb d2 33 aa ca   .........Q...3..\n",
      "0ff0  d2 bc 55 d5 d6 0c bf 3b d3 12 a8 4b d6 03 ba c3   ..U....;...K....\n",
      "\n",
      "1000  12 4c 4c de 14 4d 4c 56 12 6d 5c 5e 10 e2 a3 40   .LL..MLV.m.^...@\n",
      "1010  14 52 49 8a 11 4c 5e de 14 5d 4c 56 12 0c 4c fe   .RI..L^..]LV..L.\n",
      "1020  14 4d 4c 56 14 5d 4c 56 12 0c 4c fe 14 4d 4c 56   .MLV.]LV..L..MLV\n",
      "1030  12 6d 5c 5e 10 e2 a3 40 14 52 49 f2 14 52 79 ee   .m.^...@.RI..Ry.\n",
      "1040  12 6d 6c 5e 11 4c 4e de 14 4c 6c 52 16 5f 6d 5e   .ml^.LN..LlR._m^\n",
      "1050  12 9e 5c 5f 73 8e 4c 5f 76 4f 4d 5e 70 e2 a3 40   ..._s.L_vOM^p..@\n",
      "1060  14 5c 6c 56 12 de 5c 5f eb cd 5c 5d 14 52 69 22   ..lV..._...].Ri\"\n",
      "1070  16 1e 6c 5e 12 9e 5c 5f fb cd 5c 54 14 5c 7c 56   ..l^..._...T..|V\n",
      "1080  12 0f 7c fe 14 4c 7c 56 14 5c 7c 56 12 0f 7c fe   ..|..L|V..|V..|.\n",
      "1090  14 4c 7c 56 14 52 49 02 16 5c 5d 5e 12 9d 5c 5e   .L|V.RI...]^...^\n",
      "10a0  f0 e2 a3 40 10 e2 a3 4e 14 52 49 12 16 5c 4d 5e   ...@...N.RI...M^\n",
      "10b0  16 4f 4d 5e 1b 32 a3 a8 14 52 59 1e 10 1d 48 ee   .OM^.2...RY...H.\n",
      "10c0  12 0c 45 5d 12 4c 45 5f 10 0d 48 ee 12 6d 4c 5c   ..E].LE_..H..mL.\n",
      "10d0  10 1d 78 ee 10 9c 5b 7c eb 32 a3 a2 10 1d 4d e2   ..x...[|.2....M.\n",
      "10e0  12 4c 45 5c 10 0d 4d e2 10 e2 a3 40 14 52 58 ae   .LE...M....@.RX.\n",
      "10f0  14 5d 4c 5a 13 4c 4c 5f 14 4d 4c 5a 10 e2 a3 40   .]LZ.LL_.MLZ...@\n",
      "1100  14 52 58 ba 14 52 48 b6 12 6d 7c 5e 14 4d 7c 52   .RX..RH..m|^.M|R\n",
      "1110  14 5c 7c 5e 12 9f 5c 5f 73 8f 5c 5f 74 4c 5c 5e   ..|^..._s.._tL.^\n",
      "1120  70 e2 a3 40 14 5d 7c 56 12 df 5c 5f eb cd 5c 5d   p..@.]|V..._...]\n",
      "1130  14 52 78 e6 14 1f 7c 5e 12 9f 5c 5f fb cd 5c 54   .Rx...|^..._...T\n",
      "1140  14 5d 4c 56 12 0c 4c fe 14 4d 4c 56 14 5d 4c 56   .]LV..L..MLV.]LV\n",
      "1150  12 0c 4c fe 14 4d 4c 56 14 52 58 c6 14 5d 5c 5e   ..L..MLV.RX..].^\n",
      "1160  12 9d 5c 5e f0 e2 a3 40 10 e2 a3 4e 14 52 58 d6   ...^...@...N.RX.\n",
      "1170  14 5d 5c 5e 14 4c 5c 5e 1b 32 a3 a8 14 52 58 3e   .].^.L.^.2...RX>\n",
      "1180  14 5d 5c 5a 10 e2 a3 40 14 52 48 0a 14 5c 7c 5a   .].Z...@.RH...|Z\n",
      "1190  11 4d 5c 5c 13 4d 5c 5f 14 5c 7c 5a 10 9f 5c 5e   .M...M._..|Z...^\n",
      "11a0  6b 32 a3 a2 10 e2 a3 40 14 52 48 6a 14 5c 7c 5a   k2.....@.RHj..|Z\n",
      "11b0  11 4d 5c 5c 13 4d 5c 5f 14 5c 7c 5a 10 9f 5c 5e   .M...M._..|Z...^\n",
      "11c0  6b 32 a3 a2 12 6d 5c 5e 10 e2 a3 40 13 cd 7c 41   k2...m.^...@..|A\n",
      "11d0  18 e0 1c 4e 11 4c 4c 5c 12 0d 5c 41 1e cd 5c 55   ...N.LL....A...U\n",
      "11e0  19 70 dc 4e 13 cd 7c 41 18 e0 1c 4e 11 4c 4c 5c   .p.N..|A...N.LL.\n",
      "11f0  12 0d 5c 41 1e cd 5c 52 14 52 58 5e 10 1d 48 ee   ...A...R.RX^..H.\n",
      "\n",
      "1200  53 c6 14 f2 53 86 14 f0 51 c7 19 41 53 a7 1d f3   S...S...Q..AS...\n",
      "1210  51 d7 29 41 51 56 0a d3 aa f8 f2 0d 51 d7 1c 4d   Q.)AQV......Q..M\n",
      "1220  53 86 14 f3 51 c7 1c 4d 58 ba 8d e1 55 98 2e 25   S...Q..MX...U..%\n",
      "1230  55 98 0e 3d 55 95 3c b1 53 a7 1d f0 54 87 3d f5   U..=U.<.S...T.=.\n",
      "1240  50 85 3c f0 55 94 cc b1 52 86 1d f3 54 87 cd f5   P.<.U...R...T...\n",
      "1250  55 94 3c b5 53 56 0d f8 54 87 3d f5 0a f8 f2 06   U.<.SV..T.=.....\n",
      "1260  53 a7 0d f0 55 85 0c e5 55 98 1e 85 55 86 0d f9   S...U...U...U...\n",
      "1270  51 28 f2 ef 55 98 1e 61 52 86 2d f1 55 86 0d f1   Q(..U..aR.-.U...\n",
      "1280  55 98 1e 71 55 96 14 f1 51 b7 12 f0 f1 28 f2 ef   U..qU...Q....(..\n",
      "1290  53 a7 cd f3 53 a7 3d f0 55 98 1e 99 55 86 cc 71   S...S.=.U...U..q\n",
      "12a0  52 85 2d f5 55 86 cc 61 55 96 cc 75 53 cb cd f6   R.-.U..aU..uS...\n",
      "12b0  53 8b cd f5 55 86 cc 75 55 86 0c 31 54 95 cd f5   S...U..uU..1T...\n",
      "12c0  50 86 0c f2 52 84 3d f3 55 87 cc 31 54 95 cd f5   P...R.=.U..1T...\n",
      "12d0  53 54 0d f8 55 87 cc 35 0a f8 f2 06 55 96 0c 79   ST..U..5....U..y\n",
      "12e0  53 87 0d f0 55 86 0c 79 51 28 f2 ef 59 2a 0d fe   S...U..yQ(..Y*..\n",
      "12f0  59 2a 4d e1 55 98 0e e5 55 9a 1d f9 53 a7 2d e2   Y*M.U...U...S.-.\n",
      "1300  5b 07 48 65 55 98 0e f5 53 a7 1d f1 55 c7 1d e2   [.HeU...S...U...\n",
      "1310  55 9a 1d fd 55 87 1d e5 55 9a 1d e1 55 87 1d e9   U...U...U...U...\n",
      "1320  55 9a 1d e5 55 87 1d ed 55 9a 1d e9 55 87 1d d1   U...U...U...U...\n",
      "1330  55 98 1f 21 55 96 14 f1 51 b7 13 70 fa f8 f2 0a   U..!U...Q..p....\n",
      "1340  55 98 1f 31 53 a7 3d f5 53 a7 2d f0 55 86 3f f1   U..1S.=.S.-.U.?.\n",
      "1350  55 86 3f e1 55 96 3f f5 53 c4 3d f6 53 84 3d f5   U.?.U.?.S.=.S.=.\n",
      "1360  55 86 3f f5 54 97 3d f5 55 86 3f b1 54 97 cd f5   U.?.T.=.U.?.T...\n",
      "1370  50 86 3c f3 52 85 2d f3 55 84 cf b1 54 97 cd f5   P.<.R.-.U...T...\n",
      "1380  53 55 0d f8 55 84 cf b5 0a f8 f2 06 55 96 0f f9   SU..U.......U...\n",
      "1390  53 87 0d f0 55 86 0f f9 54 9a 4d f5 54 9a fd e5   S...U...T.M.T...\n",
      "13a0  55 98 1f 91 55 96 14 f1 51 b7 13 70 fa f8 f2 0a   U...U...Q..p....\n",
      "13b0  55 98 1f a1 53 a7 3d f5 53 a7 2d f0 55 86 3f f1   U...S.=.S.-.U.?.\n",
      "13c0  55 86 3f e1 55 96 3f f5 53 c4 3d f6 53 84 3d f5   U.?.U.?.S.=.S.=.\n",
      "13d0  55 86 3f f5 54 97 3d f5 55 86 3f b1 54 97 cd f5   U.?.T.=.U.?.T...\n",
      "13e0  50 86 3c f3 52 85 2d f3 55 84 cf b1 54 97 cd f5   P.<.R.-.U...T...\n",
      "13f0  53 55 0d f8 55 84 cf b5 0a f8 f2 06 55 96 0f f9   SU..U.......U...\n",
      "\n"
     ]
    }
   ],
   "source": [
    "section_keys = ['071969ed', 'b72047a5']\n",
    "start = 0xc00\n",
    "length = 0x200\n",
    "for i in [0,1,2,3]:\n",
    "    print hexdump(data[start+i*length:start+(i+1)*length], start+i*length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counter({'7559f938': 108, '7559f93f': 5, '7559f93c': 5, '7559f939': 3, '7559f9f0': 2, '7559f93d': 1, '2c1cbf71': 1, '7559f926': 1, '7559f97d': 1, '7559de28': 1})\n"
     ]
    }
   ],
   "source": [
    "from collections import Counter\n",
    "section3 = data[0xc00:0xe00]\n",
    "# collect all 0x00000000 to find keys\n",
    "words = map(''.join, zip(*[iter( binascii.hexlify(section3) )]*8))\n",
    "freqs = Counter(words)\n",
    "print freqs\n",
    "# xor 0xffffffff and add these keys\n",
    "#for w in list(words):\n",
    "#    words.append(binascii.hexlify(xor(binascii.unhexlify(w), binascii.unhexlify('ffffffff'))))\n",
    "#"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def find_xor_key(_section):\n",
    "    # collect stats on null values\n",
    "    words = map(''.join, zip(*[iter( binascii.hexlify(_section) )]*8))\n",
    "    # xor 0xffffffff and add these keys\n",
    "    #for w in list(words):\n",
    "    #    words.append(binascii.hexlify(xor(binascii.unhexlify(w), binascii.unhexlify('ffffffff'))))\n",
    "    # now look at stats\n",
    "    freqs = Counter(words)\n",
    "    return freqs.most_common(1)[0][0], freqs\n",
    "# Counter.most_common() is the winner"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "section1 071969ed\n",
      "section2 b72047a5\n"
     ]
    }
   ],
   "source": [
    "key, _ = find_xor_key(section1)\n",
    "print 'section1', key\n",
    "key, _ = find_xor_key(section2)\n",
    "print 'section2', key"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "start = 0xc00\n",
    "length = 0x200\n",
    "section_freqs = dict()\n",
    "section_keys = dict()\n",
    "sections = []\n",
    "data_out = data[:0x800]\n",
    "#for start in range(0x800, 0x1000, length):\n",
    "for start in range(0x800, len(data), length):\n",
    "    section = data[start:start+length]\n",
    "    key, stats = find_xor_key(section)\n",
    "    section_keys[hex(start)] = key\n",
    "    section_freqs[hex(start)] = stats\n",
    "    section_xor = xor(section, binascii.unhexlify(key))\n",
    "    sections.append(section_xor)\n",
    "    data_out += section_xor\n",
    "    #print hexdump(section_xor, start)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# write to file\n",
    "with open('firm.xor.1','wb') as fout:\n",
    "    fout.write(data_out)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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B98nlmNbw5z+3R8M+8wwTeAcMQAHyz39mmsh8Hgfrb30LzbHZrLUtrVyJQuwll+AzeP55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\nMngwwFFH+ffxcxMAFy5Mzs/IC91tINKUnrQLPHGmKpo50zm3bNooVb1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WAAAg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\naxAHk5GRodTU1NbRwADc6f8DAmsL7iun9oQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image at 0x7f8310468110>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename='entropy.png')\n",
    "# entropy.png was generated from binwalk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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2DutMqR99FK9bZ2fpvSwW8VnLzp2FNunll/GzUIinV5HVmwvbNkLP009juW++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\n",
      "text/plain": [
       "<IPython.core.display.Image at 0x7f8310468150>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename='entropy_after_section_xor.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "DECIMAL       HEXADECIMAL     DESCRIPTION\n",
      "--------------------------------------------------------------------------------\n",
      "2384780       0x24638C        LZMA compressed data, properties: 0x5D, dictionary size: 16777216 bytes, missing uncompressed size\n",
      "2401215       0x24A3BF        HTML document header\n",
      "2408339       0x24BF93        PEM certificate\n",
      "2410547       0x24C833        HTML document footer\n",
      "2565856       0x2726E0        HTML document footer\n",
      "3055257       0x2E9E99        GPG key trust database version 112\n",
      "3259807       0x31BD9F        LZMA compressed data, properties: 0x5E, dictionary size: 16777216 bytes, uncompressed size: 513719291 bytes\n",
      "3716999       0x38B787        LZMA compressed data, properties: 0x5D, dictionary size: 16777216 bytes, missing uncompressed size\n",
      "3736989       0x39059D        GPG key trust database version 112\n",
      "3818863       0x3A456F        SQLite 3.x database\n",
      "3869404       0x3B0ADC        PEM RSA private key\n",
      "4064021       0x3E0315        GPG key trust database version 112\n",
      "4788635       0x49119B        LZMA compressed data, properties: 0x90, dictionary size: 1048576 bytes, uncompressed size: 671094016 bytes\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!binwalk firm.xor.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'CERTIFICATE' in data_out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 10136.0 sections\n",
      "and 10013 distinct keys\n"
     ]
    }
   ],
   "source": [
    "nb_sections = float(len(data)-0x800)/0x200\n",
    "print \"There are\", nb_sections, \"sections\"\n",
    "nb_distinct = len(Counter(section_keys.values()).most_common())\n",
    "print \"and\", nb_distinct, \"distinct keys\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Oh-oh...\n",
    "so evidently, the heuristic to find the XOR keys is bad, but the obfuscation routine is to XOR 0x200 blocks of data.\n",
    "Starting at 0x800."
   ]
  }
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