jgamblin/cvedata.ipynb Secret

## cvedata.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "lightweight-printing",
   "metadata": {},
   "source": [
    "# Q1 2021 CVE Reveiw"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "passive-benefit",
   "metadata": {},
   "source": [
    "This notebook will pull all [JSON Data](https://nvd.nist.gov/vuln/data-feeds#JSON_FEED) from the NVD and performs some basic data analysis of CVEd data. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "treated-scheme",
   "metadata": {},
   "source": [
    "## Getting Started"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "quick-privacy",
   "metadata": {},
   "source": [
    "### Collecting Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "acoustic-apparatus",
   "metadata": {},
   "source": [
    "This cell pulls all JSON files from the NVD that we will be working with."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "surrounded-lincoln",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "%%capture\n",
    "!mkdir -p jsondata\n",
    "%cd jsondata\n",
    "!rm *.json \n",
    "!rm *.zip \n",
    "!wget https://nvd.nist.gov/feeds/json/cve/1.1/nvdcve-1.1-{2000..2021}.json.zip \n",
    "!unzip -o \"*.zip\" "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "extreme-prototype",
   "metadata": {
    "jupyter": {
     "source_hidden": true
    },
    "tags": []
   },
   "source": [
    "### Import Python Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "vocational-december",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import calplot\n",
    "import glob\n",
    "import logging\n",
    "import json\n",
    "import matplotlib.pyplot as plt\n",
    "import missingno as msno\n",
    "import numpy as np\n",
    "import os\n",
    "import pandas as pd\n",
    "import re\n",
    "import uuid\n",
    "import warnings\n",
    "from datetime import datetime\n",
    "\n",
    "\n",
    "logging.getLogger('matplotlib.font_manager').disabled = True\n",
    "warnings.filterwarnings(\"ignore\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "rubber-nature",
   "metadata": {},
   "source": [
    "# 2021 Q1 CVE Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "academic-preparation",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Build Base DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "representative-tattoo",
   "metadata": {},
   "source": [
    "This code builds a Panda dataframe from the JSON files we downloaded, removing all CVE's marked rejected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "thermal-witch",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CVEs from NVD: 2775\n",
      "CVEs Published Per Day: 31.0\n"
     ]
    }
   ],
   "source": [
    "row_accumulator = []\n",
    "for filename in glob.glob('nvdcve-1.1-2021.json'):\n",
    "    with open(filename, 'r', encoding='utf-8') as f:\n",
    "        nvd_data = json.load(f)\n",
    "        for entry in nvd_data['CVE_Items']:\n",
    "            cve = entry['cve']['CVE_data_meta']['ID']\n",
    "            try:\n",
    "                published_date = entry['publishedDate']\n",
    "            except KeyError:\n",
    "                published_date = 'Missing_Data_JG'\n",
    "            try:\n",
    "                attack_vector = entry['impact']['baseMetricV3']['cvssV3']['attackVector']\n",
    "            except KeyError:\n",
    "                attack_vector = 'Missing_Data_JG'\n",
    "            try:\n",
    "                attack_complexity = entry['impact']['baseMetricV3']['cvssV3']['attackComplexity']\n",
    "            except KeyError:\n",
    "                attack_complexity = 'Missing_Data_JG'\n",
    "            try:\n",
    "                privileges_required = entry['impact']['baseMetricV3']['cvssV3']['privilegesRequired']\n",
    "            except KeyError:\n",
    "                privileges_required = 'Missing_Data_JG'\n",
    "            try:\n",
    "                user_interaction = entry['impact']['baseMetricV3']['cvssV3']['userInteraction']\n",
    "            except KeyError:\n",
    "                user_interaction = 'Missing_Data_JG'\n",
    "            try:\n",
    "                scope = entry['impact']['baseMetricV3']['cvssV3']['scope']\n",
    "            except KeyError:\n",
    "                scope = 'Missing_Data_JG'\n",
    "            try:\n",
    "                confidentiality_impact = entry['impact']['baseMetricV3']['cvssV3']['confidentialityImpact']\n",
    "            except KeyError:\n",
    "                confidentiality_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                integrity_impact = entry['impact']['baseMetricV3']['cvssV3']['integrityImpact']\n",
    "            except KeyError:\n",
    "                integrity_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                availability_impact = entry['impact']['baseMetricV3']['cvssV3']['availabilityImpact']\n",
    "            except KeyError:\n",
    "                availability_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                base_score = entry['impact']['baseMetricV3']['cvssV3']['baseScore']\n",
    "            except KeyError:\n",
    "                base_score = '0.0'\n",
    "            try:\n",
    "                base_severity = entry['impact']['baseMetricV3']['cvssV3']['baseSeverity']\n",
    "            except KeyError:\n",
    "                base_severity = 'Missing_Data_JG'\n",
    "            try:\n",
    "                exploitability_score = entry['impact']['baseMetricV3']['exploitabilityScore']\n",
    "            except KeyError:\n",
    "                exploitability_score = 'Missing_Data_JG'\n",
    "            try:\n",
    "                impact_score = entry['impact']['baseMetricV3']['impactScore']\n",
    "            except KeyError:\n",
    "                impact_score = 'Missing_Data_JG'\n",
    "            try:\n",
    "                cwe = entry['cve']['problemtype']['problemtype_data'][0]['description'][0]['value']\n",
    "            except IndexError:\n",
    "                cwe = 'Missing_Data_JG'\n",
    "            try:\n",
    "                description = entry['cve']['description']['description_data'][0]['value']\n",
    "            except IndexError:\n",
    "                description = ''\n",
    "            new_row = { \n",
    "                'CVE': cve, \n",
    "                'Published': published_date,\n",
    "                'AttackVector': attack_vector,\n",
    "                'AttackComplexity': attack_complexity,\n",
    "                'PrivilegesRequired': privileges_required,\n",
    "                'UserInteraction': user_interaction,\n",
    "                'Scope': scope,\n",
    "                'ConfidentialityImpact': confidentiality_impact,\n",
    "                'IntegrityImpact': integrity_impact,\n",
    "                'AvailabilityImpact': availability_impact,\n",
    "                'BaseScore': base_score,\n",
    "                'BaseSeverity': base_severity,\n",
    "                'ExploitabilityScore': exploitability_score,\n",
    "                'ImpactScore': impact_score,\n",
    "                'CWE': cwe,\n",
    "                'Description': description\n",
    "            }\n",
    "            if not description.startswith('** REJECT **'): # disputed, rejected and other non issues start with '**'\n",
    "                row_accumulator.append(new_row)\n",
    "    nvd_2021 = pd.DataFrame(row_accumulator)\n",
    "    \n",
    "\n",
    "\n",
    "nvd_2021 = nvd_2021[(nvd_2021['Published'] > '2021-01-01') & (nvd_2021['Published'] < '2021-04-01')]\n",
    "nvd_2021['Published'] = pd.to_datetime(nvd_2021['Published']).apply(lambda x: x.date())\n",
    "print ('CVEs from NVD:', nvd_2021['CVE'].count())\n",
    "nvdcount = nvd_2021['Published'].count()\n",
    "Q1Days = 90\n",
    "per_day = nvdcount/Q1Days\n",
    "per_day = round(per_day, 0)\n",
    "print('CVEs Published Per Day:', per_day)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unknown-theorem",
   "metadata": {},
   "source": [
    "### CVEs Per Day Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "growing-property",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Date')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nvd_data_2021 = nvd_2021['Published'].value_counts()\n",
    "cg = nvd_data_2021.plot(colormap='jet', marker='.', figsize=(16, 8), markersize=2, title='CVEs Per Day')\n",
    "plt.grid()\n",
    "cg.set_ylabel(\"New CVEs\")\n",
    "cg.set_xlabel(\"Date\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sublime-passage",
   "metadata": {},
   "source": [
    "### Most CVEs Per Day "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "every-editing",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2021-01-20    201\n",
       "2021-01-12    127\n",
       "2021-01-13    126\n",
       "2021-03-11    107\n",
       "2021-02-04     92\n",
       "2021-02-10     81\n",
       "2021-03-18     81\n",
       "2021-03-09     80\n",
       "2021-02-11     73\n",
       "2021-03-23     72\n",
       "Name: Published, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nvd_2021['Published'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "confidential-magnet",
   "metadata": {
    "tags": []
   },
   "source": [
    "### CVE Heat Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "portuguese-causing",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x122.4 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfs_2021 = nvd_2021['Published'].apply(lambda x: pd.to_datetime(x, errors='coerce', format='%Y/%m/%d'))\n",
    "df_2021 = dfs_2021.value_counts()\n",
    "df_2021 = df_2021.to_frame()\n",
    "df_2021.index = df_2021.index.strftime('%m/%d/%Y')\n",
    "df_2021.index = pd.to_datetime(df_2021.index, format='%m/%d/%Y')\n",
    "df_2021 = df_2021.T.squeeze()\n",
    "calplot.calplot(df_2021.T.squeeze(), cmap='coolwarm', dropzero=True, yearascending=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "religious-stevens",
   "metadata": {},
   "source": [
    "# CVSS 3 Breakdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "lasting-recall",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nvd_2021['BaseScore'] = pd.to_numeric(nvd_2021['BaseScore']);\n",
    "nvd_2021['BaseScore'] = nvd_2021['BaseScore'].replace(0, np.NaN);\n",
    "nvd_2021['BaseScore'].plot(kind=\"hist\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cathedral-management",
   "metadata": {},
   "source": [
    "Average CVSS Score:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "equal-diagram",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.100337711069419"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nvd_2021['BaseScore'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "breathing-fancy",
   "metadata": {},
   "source": [
    "# 2020 Q1 CVE Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "hired-assurance",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Build Base DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "apart-notification",
   "metadata": {},
   "source": [
    "This code builds a Panda dataframe from the JSON files we downloaded, removing all CVE's marked rejected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "specialized-fitting",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CVEs from NVD: 2484\n",
      "CVEs Published Per Day: 27.0\n"
     ]
    }
   ],
   "source": [
    "row_accumulator = []\n",
    "for filename in glob.glob('nvdcve-1.1-2020.json'):\n",
    "    with open(filename, 'r', encoding='utf-8') as f:\n",
    "        nvd_data = json.load(f)\n",
    "        for entry in nvd_data['CVE_Items']:\n",
    "            cve = entry['cve']['CVE_data_meta']['ID']\n",
    "            try:\n",
    "                published_date = entry['publishedDate']\n",
    "            except KeyError:\n",
    "                published_date = 'Missing_Data_JG'\n",
    "            try:\n",
    "                attack_vector = entry['impact']['baseMetricV3']['cvssV3']['attackVector']\n",
    "            except KeyError:\n",
    "                attack_vector = 'Missing_Data_JG'\n",
    "            try:\n",
    "                attack_complexity = entry['impact']['baseMetricV3']['cvssV3']['attackComplexity']\n",
    "            except KeyError:\n",
    "                attack_complexity = 'Missing_Data_JG'\n",
    "            try:\n",
    "                privileges_required = entry['impact']['baseMetricV3']['cvssV3']['privilegesRequired']\n",
    "            except KeyError:\n",
    "                privileges_required = 'Missing_Data_JG'\n",
    "            try:\n",
    "                user_interaction = entry['impact']['baseMetricV3']['cvssV3']['userInteraction']\n",
    "            except KeyError:\n",
    "                user_interaction = 'Missing_Data_JG'\n",
    "            try:\n",
    "                scope = entry['impact']['baseMetricV3']['cvssV3']['scope']\n",
    "            except KeyError:\n",
    "                scope = 'Missing_Data_JG'\n",
    "            try:\n",
    "                confidentiality_impact = entry['impact']['baseMetricV3']['cvssV3']['confidentialityImpact']\n",
    "            except KeyError:\n",
    "                confidentiality_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                integrity_impact = entry['impact']['baseMetricV3']['cvssV3']['integrityImpact']\n",
    "            except KeyError:\n",
    "                integrity_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                availability_impact = entry['impact']['baseMetricV3']['cvssV3']['availabilityImpact']\n",
    "            except KeyError:\n",
    "                availability_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                base_score = entry['impact']['baseMetricV3']['cvssV3']['baseScore']\n",
    "            except KeyError:\n",
    "                base_score = '0.0'\n",
    "            try:\n",
    "                base_severity = entry['impact']['baseMetricV3']['cvssV3']['baseSeverity']\n",
    "            except KeyError:\n",
    "                base_severity = 'Missing_Data_JG'\n",
    "            try:\n",
    "                exploitability_score = entry['impact']['baseMetricV3']['exploitabilityScore']\n",
    "            except KeyError:\n",
    "                exploitability_score = 'Missing_Data_JG'\n",
    "            try:\n",
    "                impact_score = entry['impact']['baseMetricV3']['impactScore']\n",
    "            except KeyError:\n",
    "                impact_score = 'Missing_Data_JG'\n",
    "            try:\n",
    "                cwe = entry['cve']['problemtype']['problemtype_data'][0]['description'][0]['value']\n",
    "            except IndexError:\n",
    "                cwe = 'Missing_Data_JG'\n",
    "            try:\n",
    "                description = entry['cve']['description']['description_data'][0]['value']\n",
    "            except IndexError:\n",
    "                description = ''\n",
    "            new_row = { \n",
    "                'CVE': cve, \n",
    "                'Published': published_date,\n",
    "                'AttackVector': attack_vector,\n",
    "                'AttackComplexity': attack_complexity,\n",
    "                'PrivilegesRequired': privileges_required,\n",
    "                'UserInteraction': user_interaction,\n",
    "                'Scope': scope,\n",
    "                'ConfidentialityImpact': confidentiality_impact,\n",
    "                'IntegrityImpact': integrity_impact,\n",
    "                'AvailabilityImpact': availability_impact,\n",
    "                'BaseScore': base_score,\n",
    "                'BaseSeverity': base_severity,\n",
    "                'ExploitabilityScore': exploitability_score,\n",
    "                'ImpactScore': impact_score,\n",
    "                'CWE': cwe,\n",
    "                'Description': description\n",
    "            }\n",
    "            if not description.startswith('** REJECT **'): # disputed, rejected and other non issues start with '**'\n",
    "                row_accumulator.append(new_row)\n",
    "    nvd_2020 = pd.DataFrame(row_accumulator)\n",
    "    \n",
    "\n",
    "\n",
    "nvd_2020 = nvd_2020[(nvd_2020['Published'] > '2020-01-01') & (nvd_2020['Published'] < '2020-04-01')]\n",
    "nvd_2020['Published'] = pd.to_datetime(nvd_2020['Published']).apply(lambda x: x.date())\n",
    "print ('CVEs from NVD:', nvd_2020['CVE'].count())\n",
    "nvdcount = nvd_2020['Published'].count()\n",
    "Q1Days = 91\n",
    "per_day = nvdcount/Q1Days\n",
    "per_day = round(per_day, 0)\n",
    "print('CVEs Published Per Day:', per_day)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "matched-investigation",
   "metadata": {},
   "source": [
    "### CVEs Per Day Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "hispanic-medicare",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nvd_data_2020 = nvd_2020['Published'].value_counts()\n",
    "cg = nvd_data_2020.plot(colormap='jet', marker='.', figsize=(16, 8), markersize=2, title='CVEs Per Day')\n",
    "plt.grid()\n",
    "cg.set_ylabel(\"New CVEs\");\n",
    "cg.set_xlabel(\"Date\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "funny-jenny",
   "metadata": {},
   "source": [
    "### Most CVEs Per Day "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "indian-skiing",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2020-03-12    284\n",
       "2020-01-15    228\n",
       "2020-02-11    163\n",
       "2020-03-25    100\n",
       "2020-02-13     79\n",
       "2020-03-10     70\n",
       "2020-03-24     69\n",
       "2020-01-14     68\n",
       "2020-02-27     68\n",
       "2020-02-12     59\n",
       "Name: Published, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nvd_2020['Published'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cheap-relevance",
   "metadata": {
    "tags": []
   },
   "source": [
    "### CVE Heat Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "lovely-directory",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x122.4 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfs_2020 = nvd_2020['Published'].apply(lambda x: pd.to_datetime(x, errors='coerce', format='%Y/%m/%d'))\n",
    "df_2020 = dfs_2020.value_counts()\n",
    "df_2020 = df_2020.to_frame()\n",
    "df_2020.index = df_2020.index.strftime('%m/%d/%Y')\n",
    "df_2020.index = pd.to_datetime(df_2020.index, format='%m/%d/%Y')\n",
    "df_2020 = df_2020.T.squeeze()\n",
    "calplot.calplot(df_2020.T.squeeze(), cmap='coolwarm', dropzero=True, yearascending=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "southern-staff",
   "metadata": {},
   "source": [
    "# CVSS 3 Breakdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "legal-wisdom",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nvd_2020['BaseScore'] = pd.to_numeric(nvd_2020['BaseScore']);\n",
    "nvd_2020['BaseScore'] = nvd_2020['BaseScore'].replace(0, np.NaN);\n",
    "nvd_2020['BaseScore'].plot(kind=\"hist\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "surprised-recipe",
   "metadata": {},
   "source": [
    "Average CVSS Score:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "married-carol",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.111513687600644"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nvd_2020['BaseScore'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "female-roman",
   "metadata": {},
   "source": [
    "# 2011 Q1 CVE Data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ethical-chamber",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Build Base DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "municipal-resistance",
   "metadata": {},
   "source": [
    "This code builds a Panda dataframe from the JSON files we downloaded, removing all CVE's marked rejected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "boxed-salvation",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CVEs from NVD: 716\n",
      "CVEs Published Per Day: 8.0\n"
     ]
    }
   ],
   "source": [
    "row_accumulator = []\n",
    "for filename in glob.glob('nvdcve-1.1-2011.json'):\n",
    "    with open(filename, 'r', encoding='utf-8') as f:\n",
    "        nvd_data = json.load(f)\n",
    "        for entry in nvd_data['CVE_Items']:\n",
    "            cve = entry['cve']['CVE_data_meta']['ID']\n",
    "            try:\n",
    "                published_date = entry['publishedDate']\n",
    "            except KeyError:\n",
    "                published_date = 'Missing_Data_JG'\n",
    "            try:\n",
    "                attack_vector = entry['impact']['baseMetricV3']['cvssV3']['attackVector']\n",
    "            except KeyError:\n",
    "                attack_vector = 'Missing_Data_JG'\n",
    "            try:\n",
    "                attack_complexity = entry['impact']['baseMetricV3']['cvssV3']['attackComplexity']\n",
    "            except KeyError:\n",
    "                attack_complexity = 'Missing_Data_JG'\n",
    "            try:\n",
    "                privileges_required = entry['impact']['baseMetricV3']['cvssV3']['privilegesRequired']\n",
    "            except KeyError:\n",
    "                privileges_required = 'Missing_Data_JG'\n",
    "            try:\n",
    "                user_interaction = entry['impact']['baseMetricV3']['cvssV3']['userInteraction']\n",
    "            except KeyError:\n",
    "                user_interaction = 'Missing_Data_JG'\n",
    "            try:\n",
    "                scope = entry['impact']['baseMetricV3']['cvssV3']['scope']\n",
    "            except KeyError:\n",
    "                scope = 'Missing_Data_JG'\n",
    "            try:\n",
    "                confidentiality_impact = entry['impact']['baseMetricV3']['cvssV3']['confidentialityImpact']\n",
    "            except KeyError:\n",
    "                confidentiality_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                integrity_impact = entry['impact']['baseMetricV3']['cvssV3']['integrityImpact']\n",
    "            except KeyError:\n",
    "                integrity_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                availability_impact = entry['impact']['baseMetricV3']['cvssV3']['availabilityImpact']\n",
    "            except KeyError:\n",
    "                availability_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                base_score = entry['impact']['baseMetricV3']['cvssV3']['baseScore']\n",
    "            except KeyError:\n",
    "                base_score = '0.0'\n",
    "            try:\n",
    "                base_severity = entry['impact']['baseMetricV3']['cvssV3']['baseSeverity']\n",
    "            except KeyError:\n",
    "                base_severity = 'Missing_Data_JG'\n",
    "            try:\n",
    "                exploitability_score = entry['impact']['baseMetricV3']['exploitabilityScore']\n",
    "            except KeyError:\n",
    "                exploitability_score = 'Missing_Data_JG'\n",
    "            try:\n",
    "                impact_score = entry['impact']['baseMetricV3']['impactScore']\n",
    "            except KeyError:\n",
    "                impact_score = 'Missing_Data_JG'\n",
    "            try:\n",
    "                cwe = entry['cve']['problemtype']['problemtype_data'][0]['description'][0]['value']\n",
    "            except IndexError:\n",
    "                cwe = 'Missing_Data_JG'\n",
    "            try:\n",
    "                description = entry['cve']['description']['description_data'][0]['value']\n",
    "            except IndexError:\n",
    "                description = ''\n",
    "            new_row = { \n",
    "                'CVE': cve, \n",
    "                'Published': published_date,\n",
    "                'AttackVector': attack_vector,\n",
    "                'AttackComplexity': attack_complexity,\n",
    "                'PrivilegesRequired': privileges_required,\n",
    "                'UserInteraction': user_interaction,\n",
    "                'Scope': scope,\n",
    "                'ConfidentialityImpact': confidentiality_impact,\n",
    "                'IntegrityImpact': integrity_impact,\n",
    "                'AvailabilityImpact': availability_impact,\n",
    "                'BaseScore': base_score,\n",
    "                'BaseSeverity': base_severity,\n",
    "                'ExploitabilityScore': exploitability_score,\n",
    "                'ImpactScore': impact_score,\n",
    "                'CWE': cwe,\n",
    "                'Description': description\n",
    "            }\n",
    "            if not description.startswith('** REJECT **'): # disputed, rejected and other non issues start with '**'\n",
    "                row_accumulator.append(new_row)\n",
    "    nvd_2011 = pd.DataFrame(row_accumulator)\n",
    "    \n",
    "\n",
    "\n",
    "nvd_2011 = nvd_2011[(nvd_2011['Published'] > '2011-01-01') & (nvd_2011['Published'] < '2011-04-01')]\n",
    "nvd_2011['Published'] = pd.to_datetime(nvd_2011['Published']).apply(lambda x: x.date())\n",
    "print ('CVEs from NVD:', nvd_2011['CVE'].count())\n",
    "nvdcount = nvd_2011['Published'].count()\n",
    "Q1Days = 90\n",
    "per_day = nvdcount/Q1Days\n",
    "per_day = round(per_day, 0)\n",
    "print('CVEs Published Per Day:', per_day)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "vietnamese-jungle",
   "metadata": {},
   "source": [
    "### CVEs Per Day Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "significant-canberra",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nvd_data_2011 = nvd_2011['Published'].value_counts()\n",
    "cg = nvd_data_2011.plot(colormap='jet', marker='.', figsize=(16, 8), markersize=2, title='CVEs Per Day')\n",
    "plt.grid()\n",
    "cg.set_ylabel(\"New CVEs\");\n",
    "cg.set_xlabel(\"Date\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ignored-cartridge",
   "metadata": {},
   "source": [
    "### Most CVEs Per Day "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "cognitive-canal",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2011-02-10    76\n",
       "2011-03-03    62\n",
       "2011-03-11    40\n",
       "2011-02-25    36\n",
       "2011-03-01    27\n",
       "2011-01-20    26\n",
       "2011-03-23    20\n",
       "2011-02-04    19\n",
       "2011-02-08    19\n",
       "2011-03-08    19\n",
       "Name: Published, dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nvd_2011['Published'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "norman-tattoo",
   "metadata": {
    "tags": []
   },
   "source": [
    "### CVE Heat Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "facial-booking",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x122.4 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dfs_2011 = nvd_2011['Published'].apply(lambda x: pd.to_datetime(x, errors='coerce', format='%Y/%m/%d'))\n",
    "df_2011 = dfs_2011.value_counts()\n",
    "df_2011 = df_2011.to_frame()\n",
    "df_2011.index = df_2011.index.strftime('%m/%d/%Y')\n",
    "df_2011.index = pd.to_datetime(df_2011.index, format='%m/%d/%Y')\n",
    "df_2011 = df_2011.T.squeeze()\n",
    "calplot.calplot(df_2011.T.squeeze(), cmap='coolwarm', dropzero=True, yearascending=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "touched-coordinator",
   "metadata": {},
   "source": [
    "# CVSS 3 Breakdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "demographic-delhi",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nvd_2011['BaseScore'] = pd.to_numeric(nvd_2011['BaseScore']);\n",
    "nvd_2011['BaseScore'] = nvd_2011['BaseScore'].replace(0, np.NaN);\n",
    "nvd_2011['BaseScore'].plot(kind=\"hist\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "attached-helmet",
   "metadata": {},
   "source": [
    "Average CVSS Score:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "covered-restoration",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.5"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nvd_2011['BaseScore'].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unusual-motel",
   "metadata": {},
   "source": [
    "# Combined Q1 Data 2000-2021"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "reserved-schedule",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Build Base DataFrame"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "lasting-coalition",
   "metadata": {},
   "source": [
    "This code builds a Panda dataframe from the JSON files we downloaded, removing all CVE's marked rejected."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "lyric-intake",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CVEs from NVD: 37372\n",
      "CVEs Published Per Day: 415.0\n"
     ]
    }
   ],
   "source": [
    "row_accumulator = []\n",
    "for filename in glob.glob('nvdcve-1.1-*.json'):\n",
    "    with open(filename, 'r', encoding='utf-8') as f:\n",
    "        nvd_data = json.load(f)\n",
    "        for entry in nvd_data['CVE_Items']:\n",
    "            cve = entry['cve']['CVE_data_meta']['ID']\n",
    "            try:\n",
    "                published_date = entry['publishedDate']\n",
    "            except KeyError:\n",
    "                published_date = 'Missing_Data_JG'\n",
    "            try:\n",
    "                attack_vector = entry['impact']['baseMetricV3']['cvssV3']['attackVector']\n",
    "            except KeyError:\n",
    "                attack_vector = 'Missing_Data_JG'\n",
    "            try:\n",
    "                attack_complexity = entry['impact']['baseMetricV3']['cvssV3']['attackComplexity']\n",
    "            except KeyError:\n",
    "                attack_complexity = 'Missing_Data_JG'\n",
    "            try:\n",
    "                privileges_required = entry['impact']['baseMetricV3']['cvssV3']['privilegesRequired']\n",
    "            except KeyError:\n",
    "                privileges_required = 'Missing_Data_JG'\n",
    "            try:\n",
    "                user_interaction = entry['impact']['baseMetricV3']['cvssV3']['userInteraction']\n",
    "            except KeyError:\n",
    "                user_interaction = 'Missing_Data_JG'\n",
    "            try:\n",
    "                scope = entry['impact']['baseMetricV3']['cvssV3']['scope']\n",
    "            except KeyError:\n",
    "                scope = 'Missing_Data_JG'\n",
    "            try:\n",
    "                confidentiality_impact = entry['impact']['baseMetricV3']['cvssV3']['confidentialityImpact']\n",
    "            except KeyError:\n",
    "                confidentiality_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                integrity_impact = entry['impact']['baseMetricV3']['cvssV3']['integrityImpact']\n",
    "            except KeyError:\n",
    "                integrity_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                availability_impact = entry['impact']['baseMetricV3']['cvssV3']['availabilityImpact']\n",
    "            except KeyError:\n",
    "                availability_impact = 'Missing_Data_JG'\n",
    "            try:\n",
    "                base_score = entry['impact']['baseMetricV3']['cvssV3']['baseScore']\n",
    "            except KeyError:\n",
    "                base_score = '0'\n",
    "            try:\n",
    "                base_severity = entry['impact']['baseMetricV3']['cvssV3']['baseSeverity']\n",
    "            except KeyError:\n",
    "                base_severity = 'Missing_Data_JG'\n",
    "            try:\n",
    "                exploitability_score = entry['impact']['baseMetricV3']['exploitabilityScore']\n",
    "            except KeyError:\n",
    "                exploitability_score = 'Missing_Data_JG'\n",
    "            try:\n",
    "                impact_score = entry['impact']['baseMetricV3']['impactScore']\n",
    "            except KeyError:\n",
    "                impact_score = 'Missing_Data_JG'\n",
    "            try:\n",
    "                cwe = entry['cve']['problemtype']['problemtype_data'][0]['description'][0]['value']\n",
    "            except IndexError:\n",
    "                cwe = 'Missing_Data_JG'\n",
    "            try:\n",
    "                description = entry['cve']['description']['description_data'][0]['value']\n",
    "            except IndexError:\n",
    "                description = ''\n",
    "            new_row = { \n",
    "                'CVE': cve, \n",
    "                'Published': published_date,\n",
    "                'AttackVector': attack_vector,\n",
    "                'AttackComplexity': attack_complexity,\n",
    "                'PrivilegesRequired': privileges_required,\n",
    "                'UserInteraction': user_interaction,\n",
    "                'Scope': scope,\n",
    "                'ConfidentialityImpact': confidentiality_impact,\n",
    "                'IntegrityImpact': integrity_impact,\n",
    "                'AvailabilityImpact': availability_impact,\n",
    "                'BaseScore': base_score,\n",
    "                'BaseSeverity': base_severity,\n",
    "                'ExploitabilityScore': exploitability_score,\n",
    "                'ImpactScore': impact_score,\n",
    "                'CWE': cwe,\n",
    "                'Description': description\n",
    "            }\n",
    "            if not description.startswith('** REJECT **'): # disputed, rejected and other non issues start with '**'\n",
    "                row_accumulator.append(new_row)\n",
    "    nvd_all = pd.DataFrame(row_accumulator)\n",
    "    \n",
    "\n",
    "nvd_all['Published'] = pd.to_datetime(nvd_all['Published'], infer_datetime_format=True)\n",
    "nvd_all['MM-DD'] = nvd_all['Published'].dt.strftime('%m-%d')\n",
    "nvd_all = nvd_all[(nvd_all['MM-DD'] > '01-01') & (nvd_all['MM-DD'] < '04-01')]\n",
    "nvd_all['Published'] = pd.to_datetime(nvd_all['Published']).apply(lambda x: x.date())\n",
    "print ('CVEs from NVD:', nvd_all['CVE'].count())\n",
    "nvdcount = nvd_all['Published'].count()\n",
    "Q1Days = 90\n",
    "per_day = nvdcount/Q1Days\n",
    "per_day = round(per_day, 0)\n",
    "print('CVEs Published Per Day:', per_day)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "duplicate-barcelona",
   "metadata": {},
   "source": [
    "### CVEs Per Day Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "revolutionary-picture",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1152x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "df_sample_grouped = nvd_all.groupby(['MM-DD']).size()\n",
    "n_unique_dates = len(df_sample_grouped.index.unique())\n",
    "\n",
    "fig = plt.figure(figsize=(n_unique_dates/5, n_unique_dates/10))\n",
    "\n",
    "ax = df_sample_grouped.plot(colormap='jet', marker='.', figsize=(16, 8), markersize=2, title='CVEs Per Day')\n",
    "# ax.set_xticklabels(labels=df_sample_grouped.index, rotation=70, rotation_mode=\"anchor\", ha=\"right\");\n",
    "ax.legend(labels=['CVEs']);\n",
    "ax.set_ylabel(\"New CVEs\")\n",
    "ax.set_xlabel(\"Date\")\n",
    "\n",
    "plt.tight_layout()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "precise-information",
   "metadata": {},
   "source": [
    "### Most CVEs Per Day "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "governmental-range",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "01-15    772\n",
       "02-15    712\n",
       "03-12    709\n",
       "01-18    700\n",
       "01-21    660\n",
       "01-09    657\n",
       "01-12    600\n",
       "01-27    600\n",
       "03-24    591\n",
       "01-10    590\n",
       "Name: MM-DD, dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nvd_all['MM-DD'].value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "particular-thousand",
   "metadata": {
    "tags": []
   },
   "source": [
    "### CVE Heat Map"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "seventh-response",
   "metadata": {},
   "source": [
    "# CVSS 3 Breakdown"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "japanese-equation",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "nvd_all['BaseScore'] = pd.to_numeric(nvd_all['BaseScore']);\n",
    "nvd_all['BaseScore'] = nvd_all['BaseScore'].replace(0, np.NaN)\n",
    "nvd_all['BaseScore'].plot(kind=\"hist\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "innocent-question",
   "metadata": {},
   "source": [
    "Average CVSS Score:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "separate-newsletter",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.196985117618819"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nvd_all['BaseScore'].mean()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}