analysis.ipynb

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    "import pandas as pd\n",
    "from pymongo import MongoClient\n",
    "from configparser import ConfigParser\n",
    "import plotly.express as px"
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    "config = ConfigParser()\n",
    "config.read(\"creds.cfg\")\n",
    "client = MongoClient(f'mongodb://admin:{config[\"mongodb\"][\"passwd\"]}@76.10.62.77:27017/?authSource=admin&readPreference=primary&appname=MongoDB+Compass&directConnection=true&ssl=false')"
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   "source": [
    "# Vulnerabilities\n",
    "\n",
    "results = client['tls_data']['endpoints'].aggregate([\n",
    "    {\n",
    "        '$group': {\n",
    "            '_id': None, \n",
    "            'HeartBleed': {\n",
    "                '$sum': {\n",
    "                    '$cmp': [\n",
    "                        '$heartbleed', False\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'BEAST': {\n",
    "                '$sum': {\n",
    "                    '$cmp': [\n",
    "                        '$vulnBeast', False\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'FREAK': {\n",
    "                '$sum': {\n",
    "                    '$cmp': [\n",
    "                        '$freak', False\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'DROWN': {\n",
    "                '$sum': {\n",
    "                    '$cmp': [\n",
    "                        '$drownVulnerable', False\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'LOGJAM': {\n",
    "                '$sum': {\n",
    "                    '$cmp': [\n",
    "                        '$logjam', False\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'POODLE': {\n",
    "                '$sum': {\n",
    "                    '$cmp': [\n",
    "                        '$poodle', False\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'ocspStapling': {\n",
    "                '$sum': {\n",
    "                    '$cmp': [\n",
    "                        '$ocspStapling', False\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'total': {\n",
    "                '$sum': 1\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "])\n",
    "\n",
    "\n",
    "results = [(k, v) for k, v in list(results)[0].items()][1:]\n",
    "df = pd.DataFrame(results, columns=[\"Exploit\", \"Percentage\"])\n",
    "df.loc[:, 'Percentage'] = df.loc[:, \"Percentage\"].div(df.iloc[-1]['Percentage']).mul(100)\n",
    "df.drop(df.tail(2).index, inplace=True)\n",
    "fig = px.bar(df, x=\"Exploit\", y=\"Percentage\", log_y=True, range_y=[0.001, 100], text=\"Percentage\")\n",
    "fig.update_traces(texttemplate='%{text:.2}%', textposition='outside', marker_color=\"#FF8200\")\n",
    "fig.update_layout(title={'text': \"Percentage of Endpoints Vulnerable to Well-Known Exploits\", 'xanchor': \"center\", 'yanchor': 'top', 'x': 0.5})\n"
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  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_29329/154621390.py:92: FutureWarning:\n",
      "\n",
      "The default value of regex will change from True to False in a future version.\n",
      "\n"
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    "# TLS Versions\n",
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    "results = client['tls_data']['endpoints'].aggregate([\n",
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    "        '$group': {\n",
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    "                '$sum': {\n",
    "                    '$cond': [\n",
    "                        {\n",
    "                            '$not': [\n",
    "                                {\n",
    "                                    '$ifNull': [\n",
    "                                        '$SSL_3_0', False\n",
    "                                    ]\n",
    "                                }\n",
    "                            ]\n",
    "                        }, 0, 1\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'TLS_1_0': {\n",
    "                '$sum': {\n",
    "                    '$cond': [\n",
    "                        {\n",
    "                            '$not': [\n",
    "                                {\n",
    "                                    '$ifNull': [\n",
    "                                        '$TLS_1_0', False\n",
    "                                    ]\n",
    "                                }\n",
    "                            ]\n",
    "                        }, 0, 1\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'TLS_1_1': {\n",
    "                '$sum': {\n",
    "                    '$cond': [\n",
    "                        {\n",
    "                            '$not': [\n",
    "                                {\n",
    "                                    '$ifNull': [\n",
    "                                        '$TLS_1_1', False\n",
    "                                    ]\n",
    "                                }\n",
    "                            ]\n",
    "                        }, 0, 1\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'TLS_1_2': {\n",
    "                '$sum': {\n",
    "                    '$cond': [\n",
    "                        {\n",
    "                            '$not': [\n",
    "                                {\n",
    "                                    '$ifNull': [\n",
    "                                        '$TLS_1_2', False\n",
    "                                    ]\n",
    "                                }\n",
    "                            ]\n",
    "                        }, 0, 1\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'TLS_1_3': {\n",
    "                '$sum': {\n",
    "                    '$cond': [\n",
    "                        {\n",
    "                            '$not': [\n",
    "                                {\n",
    "                                    '$ifNull': [\n",
    "                                        '$TLS_1_3', False\n",
    "                                    ]\n",
    "                                }\n",
    "                            ]\n",
    "                        }, 0, 1\n",
    "                    ]\n",
    "                }\n",
    "            }, \n",
    "            'total': {\n",
    "                '$sum': 1\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "])\n",
    "\n",
    "\n",
    "results = [(k, v) for k, v in list(results)[0].items()][1:]\n",
    "df = pd.DataFrame(results, columns=[\"Protocol\", \"# of Endpoints\"])\n",
    "df.loc[:, \"Protocol\"] = df.loc[:, \"Protocol\"].str.replace(r\"([TLS|SSL])_(\\d)_(\\d)\", r\"\\1 v\\2.\\3\")\n",
    "df.drop(df.tail(1).index, inplace=True)\n",
    "fig = px.bar(df, x=\"Protocol\", y=\"# of Endpoints\", range_y=[1, 30000], text=\"# of Endpoints\")\n",
    "fig.update_traces(texttemplate='%{text:,}', textposition='outside', marker_color=\"#FF8200\")\n",
    "fig.update_layout(title={'text': \"Number of Endpoints Per Protocol\", 'xanchor': \"center\", 'yanchor': 'top', 'x': 0.5})\n"
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   ],
   "source": [
    "# Grades\n",
    "\n",
    "results = client['tls_data']['endpoints'].aggregate([\n",
    "    {\n",
    "        '$group': {\n",
    "            '_id': {\n",
    "                '$toString': '$grade'\n",
    "            }, \n",
    "            'count': {\n",
    "                '$sum': 1\n",
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    "    }, {\n",
    "        '$sort': {\n",
    "            'count': -1\n",
    "        }\n",
    "    }, {\n",
    "        '$group': {\n",
    "            '_id': None, \n",
    "            'counts': {\n",
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    "            }\n",
    "        }\n",
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    "        '$replaceRoot': {\n",
    "            'newRoot': {\n",
    "                '$arrayToObject': '$counts'\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "])\n",
    "\n",
    "results = [(k, v) for k, v in list(results)[0].items()]\n",
    "print(results)\n",
    "df = pd.DataFrame(results, columns=[\"Grade\", \"Count\"])\n",
    "fig = px.bar(df, x=\"Grade\", y=\"Count\",  range_y=[1, 15000], text=\"Count\")\n",
    "fig.update_traces(texttemplate='%{text:,}', textposition='outside', marker_color=\"#FF8200\")\n",
    "fig.update_layout(title={'text': \"Grades of Top 10,000 Commercial Domains' Endpoints\", 'xanchor': \"center\", 'yanchor': 'top', 'x': 0.5})\n"
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   "source": [
    "# Grades with trust ignored\n",
    "\n",
    "results = client['tls_data']['endpoints'].aggregate([\n",
    "    {\n",
    "        '$lookup': {\n",
    "            'from': 'websites', \n",
    "            'localField': 'domain', \n",
    "            'foreignField': 'domain', \n",
    "            'as': 'website'\n",
    "        }\n",
    "    }, {\n",
    "        '$unwind': {\n",
    "            'path': '$website', \n",
    "            'preserveNullAndEmptyArrays': True\n",
    "        }\n",
    "    }, {\n",
    "        '$addFields': {\n",
    "            'rank': '$website.rank'\n",
    "        }\n",
    "    }, {\n",
    "        '$unset': 'website'\n",
    "    }, {\n",
    "        '$group': {\n",
    "            '_id': {\n",
    "                '$toString': '$grade'\n",
    "            }, \n",
    "            'count': {\n",
    "                '$sum': 1\n",
    "            }\n",
    "        }\n",
    "    }, {\n",
    "        '$sort': {\n",
    "            'count': -1\n",
    "        }\n",
    "    }, {\n",
    "        '$group': {\n",
    "            '_id': None, \n",
    "            'counts': {\n",
    "                '$push': {\n",
    "                    'k': '$_id', \n",
    "                    'v': '$count'\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "    }, {\n",
    "        '$replaceRoot': {\n",
    "            'newRoot': {\n",
    "                '$arrayToObject': '$counts'\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "])\n",
    "\n",
    "results = [(k, v) for k, v in list(results)[0].items()]\n",
    "print(results)\n",
    "df = pd.DataFrame(results, columns=[\"Grade\", \"Count\"])\n",
    "fig = px.bar(df, x=\"Grade\", y=\"Count\", log_y=True, range_y=[1, 100000], text=\"Count\")\n",
    "fig.update_traces(texttemplate='%{text:,}', textposition='outside', marker_color=\"#FF8200\")\n",
    "fig.update_layout(title={'text': \"Grades of Top 10,000 Commercial Domain's Endpoints Without Trust\", 'xanchor': \"center\", 'yanchor': 'top', 'x': 0.5})\n"
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     "metadata": {},
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   ],
   "source": [
    "results = client['tls_data']['endpoints'].aggregate([\n",
    "    {\n",
    "        '$unwind': {\n",
    "            'path': '$TLS_1_3.list', \n",
    "            'preserveNullAndEmptyArrays': False\n",
    "        }\n",
    "    }, {\n",
    "        '$group': {\n",
    "            '_id': {\n",
    "                '$toString': '$TLS_1_3.list.name'\n",
    "            }, \n",
    "            'count': {\n",
    "                '$sum': 1\n",
    "            }\n",
    "        }\n",
    "    }, {\n",
    "        '$sort': {\n",
    "            'count': -1\n",
    "        }\n",
    "    }, {\n",
    "        '$group': {\n",
    "            '_id': None, \n",
    "            'counts': {\n",
    "                '$push': {\n",
    "                    'k': '$_id', \n",
    "                    'v': '$count'\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "    }, {\n",
    "        '$replaceRoot': {\n",
    "            'newRoot': {\n",
    "                '$arrayToObject': '$counts'\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "])\n",
    "\n",
    "results = [(k, v) for k, v in list(results)[0].items()]\n",
    "print(results)\n",
    "df = pd.DataFrame(results, columns=[\"Protocol\", \"Count\"])\n",
    "fig = px.bar(df, x=\"Protocol\", y=\"Count\",  range_y=[1, 20000], text=\"Count\")\n",
    "fig.update_traces(texttemplate='%{text:,}', textposition='outside', marker_color=\"#FF8200\")\n",
    "fig.update_layout(title={'text': \"TLS v1.3 Cipher Suites\", 'xanchor': \"center\", 'yanchor': 'top', 'x': 0.5})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "113\n"
     ]
    },
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          "TLS_ECDHE_RSA_WITH_AES_128_CBC_SHA256",
          "TLS_ECDHE_RSA_WITH_AES_256_CBC_SHA384",
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          "TLS_DHE_RSA_WITH_CAMELLIA_128_CBC_SHA",
          "TLS_RSA_WITH_AES_128_CCM_8",
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          "TLS_RSA_WITH_AES_256_CCM",
          "TLS_RSA_WITH_AES_256_CCM_8",
          "TLS_ECDHE_RSA_WITH_CAMELLIA_256_CBC_SHA384",
          "TLS_ECDHE_RSA_WITH_CAMELLIA_128_CBC_SHA256",
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          "TLS_DHE_RSA_WITH_AES_256_CCM_8",
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          "TLS_ECDHE_ECDSA_WITH_AES_128_CCM_8",
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          "TLS_ECDHE_ECDSA_WITH_AES_256_CCM",
          "TLS_ECDHE_ECDSA_WITH_CAMELLIA_128_CBC_SHA256",
          "TLS_ECDHE_ECDSA_WITH_CAMELLIA_256_CBC_SHA384",
          "TLS_DH_anon_WITH_AES_128_GCM_SHA256",
          "TLS_DH_anon_WITH_AES_256_GCM_SHA384",
          "TLS_ECDHE_ECDSA_WITH_ARIA_128_GCM_SHA256",
          "TLS_ECDHE_ECDSA_WITH_ARIA_256_GCM_SHA384",
          "TLS_ECDH_anon_WITH_RC4_128_SHA",
          "TLS_RSA_WITH_DES_CBC_SHA",
          "TLS_ECDH_anon_WITH_3DES_EDE_CBC_SHA",
          "TLS_ECDH_anon_WITH_AES_128_CBC_SHA",
          "TLS_ECDH_anon_WITH_AES_256_CBC_SHA",
          "TLS_DHE_RSA_WITH_DES_CBC_SHA",
          "TLS_RSA_EXPORT_WITH_DES40_CBC_SHA",
          "TLS_RSA_EXPORT_WITH_RC4_40_MD5",
          "OLD_TLS_DHE_RSA_WITH_CHACHA20_POLY1305_SHA256",
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          "TLS_DH_anon_WITH_CAMELLIA_256_CBC_SHA",
          "TLS_DH_anon_WITH_AES_128_CBC_SHA256",
          "TLS_RSA_WITH_NULL_SHA256",
          "TLS_DH_anon_WITH_AES_256_CBC_SHA256",
          "TLS_DH_anon_WITH_CAMELLIA_128_CBC_SHA256",
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     "metadata": {},
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   ],
   "source": [
    "results = client['tls_data']['endpoints'].aggregate([\n",
    "    {\n",
    "        '$unwind': {\n",
    "            'path': '$TLS_1_2.list', \n",
    "            'preserveNullAndEmptyArrays': False\n",
    "        }\n",
    "    }, {\n",
    "        '$group': {\n",
    "            '_id': {\n",
    "                '$toString': '$TLS_1_2.list.name'\n",
    "            }, \n",
    "            'count': {\n",
    "                '$sum': 1\n",
    "            }\n",
    "        }\n",
    "    }, {\n",
    "        '$sort': {\n",
    "            'count': -1\n",
    "        }\n",
    "    }, {\n",
    "        '$group': {\n",
    "            '_id': None, \n",
    "            'counts': {\n",
    "                '$push': {\n",
    "                    'k': '$_id', \n",
    "                    'v': '$count'\n",
    "                }\n",
    "            }\n",
    "        }\n",
    "    }, {\n",
    "        '$replaceRoot': {\n",
    "            'newRoot': {\n",
    "                '$arrayToObject': '$counts'\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "])\n",
    "\n",
    "results = [(k, v) for k, v in list(results)[0].items()]\n",
    "print(len(results))\n",
    "df = pd.DataFrame(results, columns=[\"Protocol\", \"Count\"])\n",
    "fig = px.bar(df, x=\"Protocol\", y=\"Count\", log_y=True, range_y=[1, 100000], text=\"Count\")\n",
    "fig.update_traces(texttemplate='%{text:,}', textposition='outside', marker_color=\"#FF8200\")\n",
    "fig.update_layout(title={'text': \"TLS v1.2 Cipher Suites\", 'xanchor': \"center\", 'yanchor': 'top', 'x': 0.5})"
   ]
  }
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