{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CISA KVE EPSS Data Analyis "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-13T00:23:15.992149Z",
     "iopub.status.busy": "2022-10-13T00:23:15.991789Z",
     "iopub.status.idle": "2022-10-13T00:23:16.394390Z",
     "shell.execute_reply": "2022-10-13T00:23:16.392392Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import json\n",
    "import requests\n",
    "import os\n",
    "import glob\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-13T00:23:16.399743Z",
     "iopub.status.busy": "2022-10-13T00:23:16.399312Z",
     "iopub.status.idle": "2022-10-13T00:23:16.666590Z",
     "shell.execute_reply": "2022-10-13T00:23:16.665504Z"
    }
   },
   "outputs": [],
   "source": [
    "cisa_df = pd.read_csv(\"https://www.cisa.gov/sites/default/files/csv/known_exploited_vulnerabilities.csv\")\n",
    "cisa_df = cisa_df\n",
    "cisa_df.columns = cisa_df.columns.str.strip(\"\\u200b\")\n",
    "cisa_df = cisa_df.rename(columns={\"cveID\": \"CVE\", \"shortDescription\" : \"Description\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-13T00:23:16.671532Z",
     "iopub.status.busy": "2022-10-13T00:23:16.671225Z",
     "iopub.status.idle": "2022-10-13T00:23:16.817962Z",
     "shell.execute_reply": "2022-10-13T00:23:16.816529Z"
    }
   },
   "outputs": [],
   "source": [
    "epss = pd.read_csv('epss_scores-current.csv', skiprows=1)\n",
    "epss = epss.rename(columns={\"cve\": \"CVE\", \"epss\" : \"EPSS\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-13T00:23:16.822780Z",
     "iopub.status.busy": "2022-10-13T00:23:16.822462Z",
     "iopub.status.idle": "2022-10-13T00:23:57.984884Z",
     "shell.execute_reply": "2022-10-13T00:23:57.981175Z"
    }
   },
   "outputs": [],
   "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",
    "                base_score = entry['impact']['baseMetricV3']['cvssV3']['baseScore']\n",
    "            except KeyError:\n",
    "                base_score = '0.0'\n",
    "            new_row = { \n",
    "                'CVE': cve, \n",
    "                'CVSS3': base_score,\n",
    "            }\n",
    "            row_accumulator.append(new_row)\n",
    "        nvd = pd.DataFrame(row_accumulator)\n",
    "        \n",
    "nvd['CVSS3'] = pd.to_numeric(nvd['CVSS3']);\n",
    "nvd['CVSS3'] = nvd['CVSS3'].replace(0, np.NaN);       "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-13T00:23:57.990722Z",
     "iopub.status.busy": "2022-10-13T00:23:57.989962Z",
     "iopub.status.idle": "2022-10-13T00:23:58.252534Z",
     "shell.execute_reply": "2022-10-13T00:23:58.251492Z"
    }
   },
   "outputs": [],
   "source": [
    "epss_kev = pd.merge(cisa_df, epss, left_on='CVE', right_on='CVE')\n",
    "epss_kev_nvd =  pd.merge(epss_kev, nvd, left_on='CVE', right_on='CVE')\n",
    "epss_kev_nvd =  epss_kev_nvd[[\"CVE\", \"CVSS3\", \"EPSS\", \"Description\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## CISA KEV Score Scatter Plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-13T00:23:58.257886Z",
     "iopub.status.busy": "2022-10-13T00:23:58.257511Z",
     "iopub.status.idle": "2022-10-13T00:23:59.551992Z",
     "shell.execute_reply": "2022-10-13T00:23:59.551169Z"
    }
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2000x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = epss_kev_nvd.plot.scatter(x='CVSS3',\n",
    "                     y='EPSS',\n",
    "                     colormap='jet',\n",
    "                     figsize=(20, 10),\n",
    "                     title='CISA Known Exploited Vulnerabilities');\n",
    "ax.set_xlabel(\"CVSS 3 Base Score\");\n",
    "ax.set_ylabel(\"EPSS Score\");\n",
    "ax.figure.savefig('epss_kev_nvd.png');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Export to CVS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2022-10-13T00:23:59.606619Z",
     "iopub.status.busy": "2022-10-13T00:23:59.606075Z",
     "iopub.status.idle": "2022-10-13T00:23:59.628721Z",
     "shell.execute_reply": "2022-10-13T00:23:59.627904Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CVE</th>\n",
       "      <th>CVSS3</th>\n",
       "      <th>EPSS</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>CVE-2021-27104</td>\n",
       "      <td>9.8</td>\n",
       "      <td>0.01440</td>\n",
       "      <td>Accellion FTA 9_12_370 and earlier is affected...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CVE-2021-27102</td>\n",
       "      <td>7.8</td>\n",
       "      <td>0.01005</td>\n",
       "      <td>Accellion FTA 9_12_411 and earlier is affected...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>CVE-2021-27101</td>\n",
       "      <td>9.8</td>\n",
       "      <td>0.00885</td>\n",
       "      <td>Accellion FTA 9_12_370 and earlier is affected...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CVE-2021-27103</td>\n",
       "      <td>9.8</td>\n",
       "      <td>0.00885</td>\n",
       "      <td>Accellion FTA 9_12_411 and earlier is affected...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>CVE-2021-21017</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.31326</td>\n",
       "      <td>Acrobat Reader DC versions versions 2020.013.2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>CVE-2021-28550</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.01282</td>\n",
       "      <td>Acrobat Reader DC versions versions 2021.001.2...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>CVE-2018-4939</td>\n",
       "      <td>9.8</td>\n",
       "      <td>0.04874</td>\n",
       "      <td>Adobe ColdFusion Update 5 and earlier versions...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>CVE-2018-15961</td>\n",
       "      <td>9.8</td>\n",
       "      <td>0.95996</td>\n",
       "      <td>Adobe ColdFusion versions July 12 release (201...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>CVE-2018-4878</td>\n",
       "      <td>9.8</td>\n",
       "      <td>0.75301</td>\n",
       "      <td>A use-after-free vulnerability was discovered ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>CVE-2020-5735</td>\n",
       "      <td>8.8</td>\n",
       "      <td>0.04891</td>\n",
       "      <td>Amcrest cameras and NVR are vulnerable to a st...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              CVE  CVSS3     EPSS  \\\n",
       "0  CVE-2021-27104    9.8  0.01440   \n",
       "1  CVE-2021-27102    7.8  0.01005   \n",
       "2  CVE-2021-27101    9.8  0.00885   \n",
       "3  CVE-2021-27103    9.8  0.00885   \n",
       "4  CVE-2021-21017    8.8  0.31326   \n",
       "5  CVE-2021-28550    8.8  0.01282   \n",
       "6   CVE-2018-4939    9.8  0.04874   \n",
       "7  CVE-2018-15961    9.8  0.95996   \n",
       "8   CVE-2018-4878    9.8  0.75301   \n",
       "9   CVE-2020-5735    8.8  0.04891   \n",
       "\n",
       "                                         Description  \n",
       "0  Accellion FTA 9_12_370 and earlier is affected...  \n",
       "1  Accellion FTA 9_12_411 and earlier is affected...  \n",
       "2  Accellion FTA 9_12_370 and earlier is affected...  \n",
       "3  Accellion FTA 9_12_411 and earlier is affected...  \n",
       "4  Acrobat Reader DC versions versions 2020.013.2...  \n",
       "5  Acrobat Reader DC versions versions 2021.001.2...  \n",
       "6  Adobe ColdFusion Update 5 and earlier versions...  \n",
       "7  Adobe ColdFusion versions July 12 release (201...  \n",
       "8  A use-after-free vulnerability was discovered ...  \n",
       "9  Amcrest cameras and NVR are vulnerable to a st...  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "epss_kev_nvd.to_csv(\"epss_kev_nvd.csv\", index=False)\n",
    "epss_kev_nvd.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.10.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}