{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updated ../amitt_red_framework.md\n",
      "updated ../amitt_red_framework_clickable.html\n",
      "updated ../amitt_blue_framework.md\n",
      "updated ../amitt_blue_framework_clickable.html\n",
      "updated ../phases_index.md\n",
      "updated ../tactics_index.md\n",
      "Updating ../tactics/TA06.md\n",
      "Updating ../tactics/TA12.md\n",
      "updated ../techniques_index.md\n",
      "Updating ../techniques/T0025.md\n",
      "Updating ../techniques/T0062.md\n",
      "Updating ../techniques/T0063.md\n",
      "Updating ../techniques/T0064.md\n",
      "updated ../tasks_index.md\n",
      "Updating ../tasks/.md\n",
      "updated ../incidents_index.md\n",
      "updated ../counters_index.md\n",
      "updated ../metatechniques_index.md\n",
      "Updating ../metatechniques/M001.md\n",
      "updated ../actors_index.md\n",
      "updated ../responsetype_index.md\n",
      "updated ../detections_index.md\n",
      "updated ../tactics_by_responsetype_table.md\n",
      "updated ../metatechniques_by_responsetype_table.md\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from generate_amitt_ttps import Amitt\n",
    "amitt = Amitt()\n",
    "amitt.generate_and_write_datafiles()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['df_phases', 'df_techniques', 'df_tasks', 'df_incidents', 'df_counters', 'df_detections', 'df_actors', 'df_resources', 'df_responsetypes', 'df_metatechniques', 'it', 'df_tactics', 'df_techniques_per_tactic', 'df_counters_per_tactic', 'phases', 'tactics', 'techniques', 'counters', 'metatechniques', 'actors', 'resources', 'num_tactics', 'cross_counterid_techniqueid', 'cross_counterid_resourceid', 'cross_counterid_actorid'])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'TA01': 'Strategic Planning',\n",
       " 'TA02': 'Objective Planning',\n",
       " 'TA03': 'Develop People',\n",
       " 'TA04': 'Develop Networks',\n",
       " 'TA05': 'Microtargeting',\n",
       " 'TA06': 'Develop Content',\n",
       " 'TA07': 'Channel Selection',\n",
       " 'TA08': 'Pump Priming',\n",
       " 'TA09': 'Exposure',\n",
       " 'TA10': 'Go Physical',\n",
       " 'TA11': 'Persistence',\n",
       " 'TA12': 'Measure Effectiveness'}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Check which amitt variables we can see from here\n",
    "print('{}'.format(vars(amitt).keys()))\n",
    "vars(amitt)['tactics']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TEST AREA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from generate_amitt_ttps import Amitt\n",
    "amitt = Amitt()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updated ../amitt_red_framework.md\n",
      "updated ../amitt_red_framework_clickable.html\n",
      "updated ../amitt_blue_framework.md\n",
      "updated ../amitt_blue_framework_clickable.html\n"
     ]
    }
   ],
   "source": [
    "amitt.write_amitt_frameworks()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "updated ../amitt_blue_framework.md\n",
      "updated ../amitt_blue_framework_clickable.html\n"
     ]
    }
   ],
   "source": [
    "amitt.write_amitt_blue_framework_file(outfile = '../amitt_blue_framework.md')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "max(amitt.df_tactics['technique_ids'].apply(len))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0                          [T0001, T0002, T0003, T0004]\n",
       "1                                        [T0005, T0006]\n",
       "2                                 [T0007, T0008, T0009]\n",
       "3            [T0010, T0011, T0012, T0013, T0014, T0015]\n",
       "4                                 [T0016, T0017, T0018]\n",
       "5     [T0019, T0020, T0021, T0022, T0023, T0024, T00...\n",
       "6     [T0029, T0030, T0031, T0032, T0033, T0034, T00...\n",
       "7     [T0039, T0040, T0041, T0042, T0043, T0044, T00...\n",
       "8     [T0047, T0048, T0049, T0050, T0051, T0052, T00...\n",
       "9                                        [T0057, T0061]\n",
       "10                                [T0058, T0059, T0060]\n",
       "11                                                     \n",
       "Name: technique_ids, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amitt.df_tactics['technique_ids']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(amitt.padded_techniques_tactics_table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amitt.max_num_techniques_per_tactic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'xx'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.8.3"
  }
 },
 "nbformat": 4,
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}