--- /dev/null
+{
+ "metadata": {
+ "name": "",
+ "signature": "sha256:866e05d3ba3d4529d70b8ae9ad703cd34a42995d3ac2f4f9abf24ad016c51485"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+ {
+ "cells": [
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import matplotlib.pyplot as plt\n",
+ "import pandas as pd\n",
+ "import collections\n",
+ "import string\n",
+ "%matplotlib inline\n",
+ "\n",
+ "from cipherbreak import *\n",
+ "\n",
+ "c4a = open('2014/4a.ciphertext').read()\n",
+ "c4b = open('2014/4b.ciphertext').read()"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "freqs = pd.Series(english_counts)\n",
+ "freqs.plot(kind='bar')"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "pyout",
+ "prompt_number": 8,
+ "text": [
+ "<matplotlib.axes.AxesSubplot at 0x7fab5a892908>"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": 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8t6ulZdPJtO0b/rb51H+o7RyTO8bmtS1vm5H4GWgnm6SO4VTgReBJt90NrAd2AOuArljZ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\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x7fab5a892a58>"
+ ]
+ }
+ ],
+ "prompt_number": 8
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "c4bs = sanitise(c4b)\n",
+ "c4bs"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "pyout",
+ "prompt_number": 17,
+ "text": [
+ "'prsaoegerauiadmwehdnisnrasawuaaessrefgdosogvorbeeeaartesctdfmenuibrttlmeytumtmeuaikwhutkwerwahmnpwraeesononesebatoihacineetbrotadaktgfeesyioflttlstiiaeosvieonsrrtaupmnnoaencocnuvrsclvdrgctaiihriciaihrsduomrlemcrngleomarfhiuewhalcsasracufrawwsmehulstoaohceletmtoilsepdmumtptrslyrhhntpanwpmoadppdwbeseoassltmlpesletuncorerlclitaosvsiniifwseafortaaduyenenonnsopfhontwkoertcslyvoeiohlufoeioetsthtsbreneveaouepgieesobduorsfeercdyadutaepeadrdigseebfuoggopogalyfewsoeemdntohrebhaaesneworgnfiaulnlwadueodcotrargvuenewhiertlauilmsoniotmuinewaiuewloerstttisdrsasnussiesmerdhetryrhpnlrtereadmredebnntrnenwmoutrdosaneowomcgidciasaontiioiascesissupcrmoybrineyweelaylewtyrtilhsto'"
+ ]
+ }
+ ],
+ "prompt_number": 17
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "key_a, score = keyword_break_mp(c4a)\n",
+ "key_a, score"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "pyout",
+ "prompt_number": 5,
+ "text": [
+ "(('stern', <KeywordWrapAlphabet.from_largest: 3>), -830.5838133421847)"
+ ]
+ }
+ ],
+ "prompt_number": 5
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "print(' '.join(segment(keyword_decipher(sanitise(c4a), key_a[0], key_a[1]))))"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "harry we completed the survey and you are not going to believe what we found behind the false bulkhead in the stern there was a large pumping station connected to a number of sea facing outlets it looks like a scuttling valve system similar to the ones used on u boats in world war two icant understand why they would goto so much effort when they could have scuttled her at anytime with a small quantity of plastic explosive the team back at nsa have run some analytics on the remaining text files we extracted from the servers onboard these ciphers are going to be pretty hard to crack the attached report has frequency analysis matching usual english text so we can assume that the sender was a native speaker did you have any thoughts on what the nautilus system might have been or what it was for\n"
+ ]
+ }
+ ],
+ "prompt_number": 6
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "key_b, score = column_transposition_break_mp(c4bs)\n",
+ "key_b, score"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "pyout",
+ "prompt_number": 39,
+ "text": [
+ "(((6, 0, 1, 7, 9, 4, 2, 3, 5, 8, 10), False, True), -1777.161911681522)"
+ ]
+ }
+ ],
+ "prompt_number": 39
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "print(' '.join(segment(sanitise(column_transposition_decipher(sanitise(c4bs), key_b[0], key_b[1], key_b[2])))))"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "rar rrc tee eat flen var rire epymeslntnkeeeeepbln suce lnrsdreowaeyahsdaebt ture t be sonr is nu ahl drool ciano it vs ref ytnlowmesnhtbuoosbys ghuoaeywmoaaiarnvimo art ttt plnas yfcutuuadgserarriuii yaro i iue ted as an thn nc do etc dcr mla oop pdt coeehsfseodioobgdgt oeser dns do pyyeewdemekhnhtyirel roe hfs mmnpsutwuptlhodyrgw row a en its re tdg is nw rna or uuup eia foa or ilac wait a wmo san olobprugpehnuvltwdsh me acic wrp in so srm wa be gti muth ch smc elp seri row o on eeee a dead nii earl dmos colla ms fed laws or et nos idge cue mha a elias eos eoc a ufo ent hsw tue ent mn irl tai eg tim twsnklsucgaerswolrn blrvfenyergstsoeafeu am lrm prnn i are to wage f miao ios is a chul wultuhdstifdorhtabd doe hwl rio at strn rcts ieoussvebtkreettvpnc imf as hss we peso ntvieifaegmaioeuuose new e as me i\n"
+ ]
+ }
+ ],
+ "prompt_number": 40
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "key_b, score = column_transposition_break_mp(c4bs, fitness=Ptrigrams)\n",
+ "key_b, score"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "pyout",
+ "prompt_number": 41,
+ "text": [
+ "(((4, 8, 0, 6, 9, 3, 1, 2, 5, 7, 10), False, True), -2823.7851213306785)"
+ ]
+ }
+ ],
+ "prompt_number": 41
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "print(' '.join(segment(sanitise(column_transposition_decipher(sanitise(c4bs), key_b[0], key_b[1], key_b[2])))))"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "sda ebt ture t be sonr is nu ahl drool ciano it vs ref ytnlowmesnhtbuoosbys ghuoaeywmoaaiarnvimo art ttt plnas yfcutuuadgserarriuii yaro i iue ted as an thn nc do etc dcr mla oop pdt coeehsfseodioobgdgt oeser dns do pyyeewdemekhnhtyirel roe hfs mmnpsutwuptlhodyrgw row a en its re tdg is nwp in so srm wa be gti muth ch smc elp seri row o on eeee a dead nii earl dmos coll rna or uuup eia foa or ilac wait a wmo san olobprugpehnuvltwdsh meac icw rams fed laws or et nos idge cue mha a elias eos eoc a ufo ent hsw tue ent mn irl tai eg tim twsnklsucgaerswolrn blrvfenyergstsoeafeu am lrm prnn i are tra rrr c tee eat flen var rireepymeslntnkeeeee pblnsucelnrsdreowaey a how age f miao ios is a chul wultuhdstifdorhtabd doe hwl rio at strn rcts ieoussvebtkreettvpnc imf as hss we peso ntvieifaegmaioeuuose new e as me i\n"
+ ]
+ }
+ ],
+ "prompt_number": 42
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "freqs_4b = pd.Series(collections.Counter([l.lower() for l in c4b if l in string.ascii_letters]))\n",
+ "freqs_4b.plot(kind='bar')"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "pyout",
+ "prompt_number": 9,
+ "text": [
+ "<matplotlib.axes.AxesSubplot at 0x7fab6b06ce10>"
+ ]
+ },
+ {
+ "metadata": {},
+ "output_type": "display_data",
+ "png": 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j/JKkOjDvKVZ7iquc3cb2o5WH7VY/qh72CcAccAiYBb4FLIvLxH+XFYouhBDCGpuH8D6G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\nhBBCCCGEEEIIIYQQQgghhBBCCJGD/wdbsUjhLuQm+wAAAABJRU5ErkJggg==\n",
+ "text": [
+ "<matplotlib.figure.Figure at 0x7fab6b07f438>"
+ ]
+ }
+ ],
+ "prompt_number": 9
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "c4bs = sanitise(c4b)\n",
+ "c4bs"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "pyout",
+ "prompt_number": 17,
+ "text": [
+ "'prsaoegerauiadmwehdnisnrasawuaaessrefgdosogvorbeeeaartesctdfmenuibrttlmeytumtmeuaikwhutkwerwahmnpwraeesononesebatoihacineetbrotadaktgfeesyioflttlstiiaeosvieonsrrtaupmnnoaencocnuvrsclvdrgctaiihriciaihrsduomrlemcrngleomarfhiuewhalcsasracufrawwsmehulstoaohceletmtoilsepdmumtptrslyrhhntpanwpmoadppdwbeseoassltmlpesletuncorerlclitaosvsiniifwseafortaaduyenenonnsopfhontwkoertcslyvoeiohlufoeioetsthtsbreneveaouepgieesobduorsfeercdyadutaepeadrdigseebfuoggopogalyfewsoeemdntohrebhaaesneworgnfiaulnlwadueodcotrargvuenewhiertlauilmsoniotmuinewaiuewloerstttisdrsasnussiesmerdhetryrhpnlrtereadmredebnntrnenwmoutrdosaneowomcgidciasaontiioiascesissupcrmoybrineyweelaylewtyrtilhsto'"
+ ]
+ }
+ ],
+ "prompt_number": 17
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "len(c4bs)/(7*5*19)"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "metadata": {},
+ "output_type": "pyout",
+ "prompt_number": 28,
+ "text": [
+ "1.0"
+ ]
+ }
+ ],
+ "prompt_number": 28
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "print('\\n'.join(chunks(c4bs, 19)))"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "prsaoegerauiadmwehd\n",
+ "nisnrasawuaaessrefg\n",
+ "dosogvorbeeeaartesc\n",
+ "tdfmenuibrttlmeytum\n",
+ "tmeuaikwhutkwerwahm\n",
+ "npwraeesononesebato\n",
+ "ihacineetbrotadaktg\n",
+ "feesyioflttlstiiaeo\n",
+ "svieonsrrtaupmnnoae\n",
+ "ncocnuvrsclvdrgctai\n",
+ "ihriciaihrsduomrlem\n",
+ "crngleomarfhiuewhal\n",
+ "csasracufrawwsmehul\n",
+ "stoaohceletmtoilsep\n",
+ "dmumtptrslyrhhntpan\n",
+ "wpmoadppdwbeseoassl\n",
+ "tmlpesletuncorerlcl\n",
+ "itaosvsiniifwseafor\n",
+ "taaduyenenonnsopfho\n",
+ "ntwkoertcslyvoeiohl\n",
+ "ufoeioetsthtsbrenev\n",
+ "eaouepgieesobduorsf\n",
+ "eercdyadutaepeadrdi\n",
+ "gseebfuoggopogalyfe\n",
+ "wsoeemdntohrebhaaes\n",
+ "neworgnfiaulnlwadue\n",
+ "odcotrargvuenewhier\n",
+ "tlauilmsoniotmuinew\n",
+ "aiuewloerstttisdrsa\n",
+ "snussiesmerdhetryrh\n",
+ "pnlrtereadmredebnnt\n",
+ "rnenwmoutrdosaneowo\n",
+ "mcgidciasaontiioias\n",
+ "cesissupcrmoybriney\n",
+ "weelaylewtyrtilhsto\n"
+ ]
+ }
+ ],
+ "prompt_number": 29
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "print('\\n'.join(chunks(c4bs, 35)))"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "prsaoegerauiadmwehdnisnrasawuaaessr\n",
+ "efgdosogvorbeeeaartesctdfmenuibrttl\n",
+ "meytumtmeuaikwhutkwerwahmnpwraeeson\n",
+ "onesebatoihacineetbrotadaktgfeesyio\n",
+ "flttlstiiaeosvieonsrrtaupmnnoaencoc\n",
+ "nuvrsclvdrgctaiihriciaihrsduomrlemc\n",
+ "rngleomarfhiuewhalcsasracufrawwsmeh\n",
+ "ulstoaohceletmtoilsepdmumtptrslyrhh\n",
+ "ntpanwpmoadppdwbeseoassltmlpesletun\n",
+ "corerlclitaosvsiniifwseafortaaduyen\n",
+ "enonnsopfhontwkoertcslyvoeiohlufoei\n",
+ "oetsthtsbreneveaouepgieesobduorsfee\n",
+ "rcdyadutaepeadrdigseebfuoggopogalyf\n",
+ "ewsoeemdntohrebhaaesneworgnfiaulnlw\n",
+ "adueodcotrargvuenewhiertlauilmsonio\n",
+ "tmuinewaiuewloerstttisdrsasnussiesm\n",
+ "erdhetryrhpnlrtereadmredebnntrnenwm\n",
+ "outrdosaneowomcgidciasaontiioiasces\n",
+ "issupcrmoybrineyweelaylewtyrtilhsto\n"
+ ]
+ }
+ ],
+ "prompt_number": 30
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "print('\\n'.join(chunks(c4bs, 5)))"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "prsao\n",
+ "egera\n",
+ "uiadm\n",
+ "wehdn\n",
+ "isnra\n",
+ "sawua\n",
+ "aessr\n",
+ "efgdo\n",
+ "sogvo\n",
+ "rbeee\n",
+ "aarte\n",
+ "sctdf\n",
+ "menui\n",
+ "brttl\n",
+ "meytu\n",
+ "mtmeu\n",
+ "aikwh\n",
+ "utkwe\n",
+ "rwahm\n",
+ "npwra\n",
+ "eeson\n",
+ "onese\n",
+ "batoi\n",
+ "hacin\n",
+ "eetbr\n",
+ "otada\n",
+ "ktgfe\n",
+ "esyio\n",
+ "flttl\n",
+ "stiia\n",
+ "eosvi\n",
+ "eonsr\n",
+ "rtaup\n",
+ "mnnoa\n",
+ "encoc\n",
+ "nuvrs\n",
+ "clvdr\n",
+ "gctai\n",
+ "ihric\n",
+ "iaihr\n",
+ "sduom\n",
+ "rlemc\n",
+ "rngle\n",
+ "omarf\n",
+ "hiuew\n",
+ "halcs\n",
+ "asrac\n",
+ "ufraw\n",
+ "wsmeh\n",
+ "ulsto\n",
+ "aohce\n",
+ "letmt\n",
+ "oilse\n",
+ "pdmum\n",
+ "tptrs\n",
+ "lyrhh\n",
+ "ntpan\n",
+ "wpmoa\n",
+ "dppdw\n",
+ "beseo\n",
+ "asslt\n",
+ "mlpes\n",
+ "letun\n",
+ "corer\n",
+ "lclit\n",
+ "aosvs\n",
+ "iniif\n",
+ "wseaf\n",
+ "ortaa\n",
+ "duyen\n",
+ "enonn\n",
+ "sopfh\n",
+ "ontwk\n",
+ "oertc\n",
+ "slyvo\n",
+ "eiohl\n",
+ "ufoei\n",
+ "oetst\n",
+ "htsbr\n",
+ "eneve\n",
+ "aouep\n",
+ "giees\n",
+ "obduo\n",
+ "rsfee\n",
+ "rcdya\n",
+ "dutae\n",
+ "peadr\n",
+ "digse\n",
+ "ebfuo\n",
+ "ggopo\n",
+ "galyf\n",
+ "ewsoe\n",
+ "emdnt\n",
+ "ohreb\n",
+ "haaes\n",
+ "newor\n",
+ "gnfia\n",
+ "ulnlw\n",
+ "adueo\n",
+ "dcotr\n",
+ "argvu\n",
+ "enewh\n",
+ "iertl\n",
+ "auilm\n",
+ "sonio\n",
+ "tmuin\n",
+ "ewaiu\n",
+ "ewloe\n",
+ "rsttt\n",
+ "isdrs\n",
+ "asnus\n",
+ "siesm\n",
+ "erdhe\n",
+ "tryrh\n",
+ "pnlrt\n",
+ "eread\n",
+ "mrede\n",
+ "bnntr\n",
+ "nenwm\n",
+ "outrd\n",
+ "osane\n",
+ "owomc\n",
+ "gidci\n",
+ "asaon\n",
+ "tiioi\n",
+ "asces\n",
+ "issup\n",
+ "crmoy\n",
+ "brine\n",
+ "yweel\n",
+ "aylew\n",
+ "tyrti\n",
+ "lhsto\n"
+ ]
+ }
+ ],
+ "prompt_number": 32
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [],
+ "language": "python",
+ "metadata": {},
+ "outputs": []
+ }
+ ],
+ "metadata": {}
+ }
+ ]
+}
\ No newline at end of file
projects / cipher-training.git / commitdiff