Method 1.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Actor determination method 1: Skimming threat reports\n",
    "This notebook depicts the first methodology for actor determination as described in the corresponding master thesis. Threat reports are used as a basis for determining active threats and actors over a period in time.\n",
    "The results of skimming the reports are denoted in a spreadsheet, which is scanned and used to count the precise occurences of these threats and actors across the reports. This data is then further enriched using public data sources. A graphical representation is depicted in the image below.\n",
    "\n",
    "The enriched data can then be filtered on the sector and the actors and TTPs will be ranked using the ranking functions. These ranked TTPs are then mapped to controls in order to obtain a prioritization of security controls.\n",
    "\n",
    "![Diagram representation of method 1](./docs/images/Method1.png)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Determine relevant threats  and actors\n",
    "### 1.0 Set parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "SECTOR = \"Government\"\n",
    "YEAR = 2021\n",
    "CONTROLS = \"NIST_SP_800_53\"\n",
    "file = \"Threat reports.xlsx\"\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.1. Scan spreadsheet with skimming results \n",
    "#### 1.1.1. Build actor and threat list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34 Threats:\n",
      " ['ransomware', 'crypto malware', 'scams', 'adware', 'fleeceware', 'phishing', 'coinminers', 'information stealers', 'remote access trojan', 'technical support cams', 'rootkits', 'supply chain attack', 'remote code execution', 'business email compromise', 'brand abuse', 'data exposure on code repositories', 'targeted threats on remote work', 'DDoS', 'proxy shell', 'account compromise', 'system compromise', 'botnet', 'server access', 'credential harvesting', 'misconfiguration', 'malicious insider', 'vulnerability exploitation', 'brute force', 'password spraying', 'banking trojan', 'network pivot', 'network infrastructure compromise', 'local code execution', 'use of stolen credentials']\n",
      "80 Threat actors:\n",
      " ['LuckyMouse', 'Mustang Panda', 'Gamaredon', 'Promethium', 'HAFNIUM', 'Wizard Spider', 'Bitwise Spider', 'Carbon Spider', 'Pinchy Spider', 'Pioneer Kitten', 'Deus', 'BlackShadow', 'Moses Staff', 'Nemesis Kitten', 'Wicked Panda', 'Doppel Spider', 'Aquatic Panda', 'Fancy Bear', 'Cozy Bear', 'nei', 'barf', 'inthematrix1', 'UNC2452', 'Astro Locker Team', 'MuddyWater', 'ITG23', 'LemonDuck', 'Tortoiseshell', 'Charming Kitten', 'Fox Kitten Parasite', 'ControlX', 'APT40', 'APT5', 'APT15', 'APT31', 'Sea Turtle', 'Kimsuky', 'Konni', 'Lazarus', 'APT32', 'Energetic Bear', 'APT28', 'Nobelium', 'Nickel', 'Thallium', 'Phosphorus', 'Cerium', 'Gadolinium', 'Strontium', 'Bromine', 'TeamTNT', 'Water Pamola', 'Earth Wendigo', 'Earth Vetala', 'Iron Tiger', 'PlugX', 'Sandworm', 'APT41', 'Ghostwriter', 'Black Shadow', 'REvil', 'Cl0p', 'NetWalker', 'LockerGoga', ' MegaCortex', 'BlackCat', 'Conti', 'DEV-0537', 'Karakurt', 'DeathStalker', 'Candiru', 'Anonymous', 'TeamOneFirst', 'GhostSec', 'Against The West', 'NB65', 'Belarusian Cyber Partisans', 'KILLNET', 'XakNet', 'The Red Bandits']\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "reports = pd.read_excel(file,sheet_name=\"Threat reports\")\n",
    "\n",
    "# Function to transform a list to unique (case insensitive) values\n",
    "def unique(lst):\n",
    "    result=[]\n",
    "    marker = set()\n",
    "\n",
    "    for l in lst:\n",
    "        ll = l.lower()\n",
    "        if ll not in marker:   # test presence\n",
    "            marker.add(ll)\n",
    "            result.append(l)   # preserve order\n",
    "\n",
    "    return result\n",
    "\n",
    "# Build the lists\n",
    "\n",
    "# Filter on one year\n",
    "reports=reports[reports['reported year'] == YEAR]\n",
    "\n",
    "report_threats = reports['threats'].dropna().apply(lambda x: x.split(\", \"))\n",
    "threats_mentions = pd.Series([t for l in report_threats for t in l if t != \"\"])\n",
    "threatlist = unique(threats_mentions)\n",
    "\n",
    "report_actors = reports['actors'].dropna().apply(lambda x: x.split(\", \"))\n",
    "actor_mentions = pd.Series([t for l in report_actors for t in l if t != \"\"])\n",
    "actorlist = unique(actor_mentions)\n",
    "\n",
    "print(len(threatlist),\"Threats:\\n\",threatlist)\n",
    "print(len(actorlist),\"Threat actors:\\n\",actorlist)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.1.2. Visualize quarterly time coverage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Convert a 2d list to 1d\n",
    "def to_1D(series):\n",
    " return pd.Series([x for _list in series for x in _list if len(x) > 1]) # Convert column of lists to one list and remove single character values\n",
    "\n",
    "quarters = to_1D(reports['quarter'].dropna().apply(lambda x: x.split(\", \"))).value_counts().sort_index()\n",
    "fig = quarters.plot(kind='bar',rot=0, title='Time coverage of reports on {} per quarter'.format(YEAR),ylabel=\"Number of threat reports\")\n",
    "plt.savefig(\"results/figures/method1/reports_timecoverage.pdf\",format=\"pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observations\n",
    "It can be seen that not all reports report on a full calendar year. Some reports do not start in Q1, but start in Q3 and report on the following 4 quarters, like the ENISA threat landscape. In other cases, the report does not report on 4 quarters. For example, Bugcrowd reports up and until Q3, since the report is released before the end of the year."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2. Scan PDFs on threats and actors\n",
    "Scan the PDFs on the actors and threats from the spreadsheet and count the number of occurences."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2.1. Initialize dictionaries and functions\n",
    "Initialize dictionaries and define a preprocessing function whichs converts to lowercase and removes punctuations. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import re\n",
    "\n",
    "report_folder = \"reports\\\\{}\".format(YEAR)\n",
    "report_list = [file for file in os.listdir(report_folder) if file.endswith(\".pdf\")]\n",
    "\n",
    "## Init threat dictionary to count occurences of threats per report\n",
    "report_threats = {}  \n",
    "report_actors = {}\n",
    "\n",
    "for i in report_list:\n",
    "    threat_dict = {}\n",
    "    for j in threatlist:\n",
    "        threat_dict[j] = 0    \n",
    "    report_threats[i] = threat_dict\n",
    "\n",
    "for i in report_list:\n",
    "    actor_dict = {}\n",
    "    for k in actorlist:\n",
    "        actor_dict[k] = 0\n",
    "    report_actors[i] = actor_dict\n",
    "\n",
    "def preprocess(text):\n",
    "    text_lower = re.sub(r\"[^a-zA-Z0-9 ]\",\"\",text.lower())\n",
    "    return text_lower"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2.2. Build dictionary with contents of PDFs\n",
    "The text of the PDFs is saved as both the original as well as the preprocessed text."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing:  Blackberry.pdf\n",
      "Processing:  Bugcrowd.pdf\n",
      "Processing:  Crowdstrike.pdf\n",
      "Processing:  Deepwatch.pdf\n",
      "Processing:  ENISA.pdf\n",
      "Processing:  Fortinet-2021H1.pdf\n",
      "Processing:  Fortinet-2021H2.pdf\n",
      "Processing:  IBM.pdf\n",
      "Processing:  Microsoft.pdf\n",
      "Processing:  PaloAltoNetworks.pdf\n",
      "Processing:  Rapid7.pdf\n",
      "Processing:  Verizon.pdf\n"
     ]
    }
   ],
   "source": [
    "import PyPDF2\n",
    "\n",
    "text_dict = {}\n",
    "\n",
    "for file in report_list:\n",
    "    print(\"Processing: \",file)\n",
    "\n",
    "    reader = PyPDF2.PdfFileReader(report_folder+\"\\\\\"+file,strict=False)\n",
    "    raw_text = \"\"\n",
    "    for page_number in range(0, reader.numPages):\n",
    "        page = reader.getPage(page_number)\n",
    "        raw_text += page.extractText()\n",
    "    text_dict[file] = {\"raw\": raw_text, \"processed\": preprocess(raw_text)}"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2.3. Convert reports to .txt for later testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "txt_filepath = Path(\"reports_txt/\"+str(YEAR))\n",
    "\n",
    "for file,values in text_dict.items():\n",
    "    text = values[\"raw\"]\n",
    "    filenm = file.replace(\".pdf\",\".txt\")\n",
    "    to_write = txt_filepath / filenm\n",
    "    with open(to_write,'w',encoding='utf-8') as f:\n",
    "        f.write(text)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.2.4. Count occurences of terms in reports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Count occurences of terms in reports\n",
    "for file,values in text_dict.items():\n",
    "    text = values[\"processed\"]\n",
    "    for threat in threatlist:\n",
    "        report_threats[file][threat] = text.count(threat.lower())\n",
    "    for actor in actorlist:\n",
    "        report_actors[file][actor] = text.count(actor.lower()) \n",
    "\n",
    "threats_df = pd.DataFrame(report_threats)\n",
    "actors_df = pd.DataFrame(report_actors)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3. Process data and first enrichment\n",
    "#### 1.3.1. Gather data from public sources\n",
    "Since actors are known by a variety of names, it is important to be aware of their synonyms. Therefore the results of the same actors are summed by combining the synonyms. This information is retrieved from the [ETDA Threat Actor Encyclopedia](https://apt.etda.or.th/cgi-bin/aptgroups.cgi)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "        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>actor</th>\n",
       "      <th>alternate_names</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Big Panda</td>\n",
       "      <td>[Big Panda]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Boulder Bear</td>\n",
       "      <td>[Boulder Bear]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Clockwork Spider</td>\n",
       "      <td>[Clockwork Spider]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Corsair Jackal</td>\n",
       "      <td>[Corsair Jackal, TunisianCyberArmy]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dextorous Spider</td>\n",
       "      <td>[Dextorous Spider]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>437</th>\n",
       "      <td>UNC1878</td>\n",
       "      <td>[UNC1878]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>438</th>\n",
       "      <td>[Vault 7/8]</td>\n",
       "      <td>[[Vault 7/8]]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>439</th>\n",
       "      <td>Yanbian Gang</td>\n",
       "      <td>[Yanbian Gang]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>440</th>\n",
       "      <td>Yingmob</td>\n",
       "      <td>[Yingmob]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>Zombie Spider</td>\n",
       "      <td>[Zombie Spider]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>442 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                actor                      alternate_names\n",
       "0           Big Panda                          [Big Panda]\n",
       "1        Boulder Bear                       [Boulder Bear]\n",
       "2    Clockwork Spider                   [Clockwork Spider]\n",
       "3      Corsair Jackal  [Corsair Jackal, TunisianCyberArmy]\n",
       "4    Dextorous Spider                   [Dextorous Spider]\n",
       "..                ...                                  ...\n",
       "437           UNC1878                            [UNC1878]\n",
       "438       [Vault 7/8]                        [[Vault 7/8]]\n",
       "439      Yanbian Gang                       [Yanbian Gang]\n",
       "440           Yingmob                            [Yingmob]\n",
       "441     Zombie Spider                      [Zombie Spider]\n",
       "\n",
       "[442 rows x 2 columns]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get synonyms of threat actors from ETDA\n",
    "import pandas as pd\n",
    "import requests\n",
    "\n",
    "# Retrieve data in json format\n",
    "etda_actors = requests.get('https://apt.etda.or.th/cgi-bin/getcard.cgi?g=all&o=j')\n",
    "data = etda_actors.json()\n",
    "\n",
    "actor_list = []\n",
    "\n",
    "for actor in data['values']:\n",
    "    actor_dict = {}\n",
    "    actor_dict['actor'] = actor['actor']\n",
    "    actor_dict['alternate_names'] = [x['name'] for x in actor['names']]\n",
    "    groupnames = [x['name'].replace(' Group','') for x in actor['names'] if ' Group' in x['name']] # For example: Include Lazarus and Lazarus Group\n",
    "    actor_dict['alternate_names'] = actor_dict['alternate_names'] + groupnames\n",
    "    actor_list.append(actor_dict)\n",
    "\n",
    "synonym_df = pd.DataFrame(actor_list)\n",
    "synonym_df"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.3.2. Merge results of synonyms from actors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Transpose dataframe so that the actors are columns\n",
    "actors_df_transposed = actors_df.T\n",
    "\n",
    "# Function to find synonyms of actors and sum the results\n",
    "def sum_synonyms(df, synonyms):\n",
    "    summed_df = df\n",
    "    word_matches = {}\n",
    "    for actor in df.columns:\n",
    "        # lst = []\n",
    "        for _, row in synonyms.iterrows():\n",
    "            keyname = row['actor']\n",
    "            synonym = row['alternate_names']\n",
    "            match = [x for x in synonym if actor == x]\n",
    "            if actor == keyname or match:\n",
    "                match = ' '.join(map(str, match))\n",
    "                try:\n",
    "                    word_matches[keyname].append(match)\n",
    "                except:\n",
    "                    word_matches[keyname] = [match]\n",
    "\n",
    "    # Combine results of alternative names\n",
    "    for keyname, matches in word_matches.items():\n",
    "        summed_df[keyname] = df[matches].sum(axis=1)\n",
    "    \n",
    "    # Return the summed columns\n",
    "    return summed_df[list(word_matches.keys())]\n",
    "\n",
    "actors_df = sum_synonyms(actors_df_transposed,synonym_df).T\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ENISA.pdf               14\n",
       "Crowdstrike.pdf         12\n",
       "Microsoft.pdf           10\n",
       "Verizon.pdf              5\n",
       "IBM.pdf                  2\n",
       "Blackberry.pdf           1\n",
       "Deepwatch.pdf            1\n",
       "Rapid7.pdf               1\n",
       "Bugcrowd.pdf             0\n",
       "Fortinet-2021H1.pdf      0\n",
       "Fortinet-2021H2.pdf      0\n",
       "PaloAltoNetworks.pdf     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actors_per_report = actors_df[actors_df > 0].count()\n",
    "actors_per_report.sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "IBM.pdf                 17\n",
       "ENISA.pdf               16\n",
       "Microsoft.pdf           16\n",
       "Verizon.pdf             12\n",
       "Blackberry.pdf          10\n",
       "PaloAltoNetworks.pdf    10\n",
       "Fortinet-2021H1.pdf      8\n",
       "Fortinet-2021H2.pdf      8\n",
       "Crowdstrike.pdf          7\n",
       "Rapid7.pdf               7\n",
       "Bugcrowd.pdf             2\n",
       "Deepwatch.pdf            2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "threats_per_report = threats_df[threats_df > 0].count()\n",
    "threats_per_report.sort_values(ascending=False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.3.3. Normalize data and plots\n",
    "Since the absolute number of hits cannot be compared between reports, due to differences in report lengths and the number of words, the data is normalized using the minmax normalization. The resulting number depicts how relatively often this threat or actor is mentioned within the report. The assumption is that the more often a threat is mentioned, the more important it is deemed. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "def normalize(df):\n",
    "    return (df-df.min())/(df.max()-df.min())\n",
    "\n",
    "normalized_threats = normalize(threats_df)\n",
    "normalized_actors = normalize(actors_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "plt.figure()\n",
    "sns.heatmap(normalized_threats.loc[~(normalized_threats==0).all(axis=1)], yticklabels=True)\n",
    "\n",
    "plt.figure()\n",
    "sns.heatmap(normalized_actors.loc[~(normalized_actors==0).all(axis=1)], yticklabels=True)\n",
    "plt.savefig(\"results/figures/method1/actors_in_reports.pdf\",format=\"pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observations\n",
    "It can be seen that Ransomware is mentioned in every report. IBM and CTM360 mention a wide variety of threats.\n",
    "\n",
    "Not all reports report on threat actors, 8 out of 13 reports are mentioning threat actors. ENISA and Crowdstrike are doing this the most. APT29, a group attributed to Russia's Foreign Intelligence Service, is mentioned the most."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.3.3. Sum counts\n",
    "The normalized counts per report are summed for the threats and actors, as well as the number of reports the term occurs in. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(33, 2)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        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>total_count</th>\n",
       "      <th>reports_mentioned</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>APT 29, Cozy Bear, The Dukes</th>\n",
       "      <td>5.545455</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wizard Spider, Gold Blackburn</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Promethium, StrongPity</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sandworm Team, Iron Viking, Voodoo Bear</th>\n",
       "      <td>0.833333</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kimsuky, Velvet Chollima</th>\n",
       "      <td>0.833333</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lazarus Group, Hidden Cobra, Labyrinth Chollima</th>\n",
       "      <td>0.733333</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sofacy, APT 28, Fancy Bear, Sednit</th>\n",
       "      <td>0.730303</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEV-0270, Nemesis Kitten</th>\n",
       "      <td>0.727273</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gamaredon Group</th>\n",
       "      <td>0.566667</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Magic Hound, APT 35, Cobalt Illusion, Charming Kitten</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NB65</th>\n",
       "      <td>0.466667</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aquatic Panda</th>\n",
       "      <td>0.448485</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MuddyWater, Seedworm, TEMP.Zagros, Static Kitten</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moses Staff</th>\n",
       "      <td>0.290909</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pinchy Spider, Gold Southfield</th>\n",
       "      <td>0.224242</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Deceptikons, DeathStalker</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Tortoiseshell, Imperial Kitten</th>\n",
       "      <td>0.200000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Doppel Spider</th>\n",
       "      <td>0.181818</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ke3chang, Vixen Panda, APT 15, GREF, Playful Dragon</th>\n",
       "      <td>0.166667</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reaper, APT 37, Ricochet Chollima, ScarCruft</th>\n",
       "      <td>0.133333</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mustang Panda, Bronze President</th>\n",
       "      <td>0.133333</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Energetic Bear, Dragonfly</th>\n",
       "      <td>0.100000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leviathan, APT 40, TEMP.Periscope</th>\n",
       "      <td>0.100000</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parisite, Fox Kitten, Pioneer Kitten</th>\n",
       "      <td>0.090909</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agrius</th>\n",
       "      <td>0.090909</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Winnti Group, Blackfly, Wicked Panda</th>\n",
       "      <td>0.090909</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Carbanak, Anunak</th>\n",
       "      <td>0.090909</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Karakurt</th>\n",
       "      <td>0.066667</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sea Turtle</th>\n",
       "      <td>0.033333</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Earth Wendigo</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nazar</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lapsus$</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emissary Panda, APT 27, LuckyMouse, Bronze Union</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    total_count  \\\n",
       "APT 29, Cozy Bear, The Dukes                           5.545455   \n",
       "Wizard Spider, Gold Blackburn                          2.000000   \n",
       "Promethium, StrongPity                                 1.000000   \n",
       "Sandworm Team, Iron Viking, Voodoo Bear                0.833333   \n",
       "Kimsuky, Velvet Chollima                               0.833333   \n",
       "Lazarus Group, Hidden Cobra, Labyrinth Chollima        0.733333   \n",
       "Sofacy, APT 28, Fancy Bear, Sednit                     0.730303   \n",
       "DEV-0270, Nemesis Kitten                               0.727273   \n",
       "Gamaredon Group                                        0.566667   \n",
       "Magic Hound, APT 35, Cobalt Illusion, Charming ...     0.500000   \n",
       "NB65                                                   0.466667   \n",
       "Aquatic Panda                                          0.448485   \n",
       "MuddyWater, Seedworm, TEMP.Zagros, Static Kitten       0.400000   \n",
       "Moses Staff                                            0.290909   \n",
       "Pinchy Spider, Gold Southfield                         0.224242   \n",
       "Deceptikons, DeathStalker                              0.200000   \n",
       "Tortoiseshell, Imperial Kitten                         0.200000   \n",
       "Doppel Spider                                          0.181818   \n",
       "Ke3chang, Vixen Panda, APT 15, GREF, Playful Dr...     0.166667   \n",
       "Reaper, APT 37, Ricochet Chollima, ScarCruft           0.133333   \n",
       "Mustang Panda, Bronze President                        0.133333   \n",
       "Energetic Bear, Dragonfly                              0.100000   \n",
       "Leviathan, APT 40, TEMP.Periscope                      0.100000   \n",
       "Parisite, Fox Kitten, Pioneer Kitten                   0.090909   \n",
       "Agrius                                                 0.090909   \n",
       "Winnti Group, Blackfly, Wicked Panda                   0.090909   \n",
       "Carbanak, Anunak                                       0.090909   \n",
       "Karakurt                                               0.066667   \n",
       "Sea Turtle                                             0.033333   \n",
       "Earth Wendigo                                          0.000000   \n",
       "Nazar                                                  0.000000   \n",
       "Lapsus$                                                0.000000   \n",
       "Emissary Panda, APT 27, LuckyMouse, Bronze Union       0.000000   \n",
       "\n",
       "                                                    reports_mentioned  \n",
       "APT 29, Cozy Bear, The Dukes                                        6  \n",
       "Wizard Spider, Gold Blackburn                                       2  \n",
       "Promethium, StrongPity                                              1  \n",
       "Sandworm Team, Iron Viking, Voodoo Bear                             2  \n",
       "Kimsuky, Velvet Chollima                                            2  \n",
       "Lazarus Group, Hidden Cobra, Labyrinth Chollima                     3  \n",
       "Sofacy, APT 28, Fancy Bear, Sednit                                  3  \n",
       "DEV-0270, Nemesis Kitten                                            1  \n",
       "Gamaredon Group                                                     2  \n",
       "Magic Hound, APT 35, Cobalt Illusion, Charming ...                  2  \n",
       "NB65                                                                1  \n",
       "Aquatic Panda                                                       2  \n",
       "MuddyWater, Seedworm, TEMP.Zagros, Static Kitten                    1  \n",
       "Moses Staff                                                         2  \n",
       "Pinchy Spider, Gold Southfield                                      2  \n",
       "Deceptikons, DeathStalker                                           1  \n",
       "Tortoiseshell, Imperial Kitten                                      1  \n",
       "Doppel Spider                                                       1  \n",
       "Ke3chang, Vixen Panda, APT 15, GREF, Playful Dr...                  1  \n",
       "Reaper, APT 37, Ricochet Chollima, ScarCruft                        1  \n",
       "Mustang Panda, Bronze President                                     1  \n",
       "Energetic Bear, Dragonfly                                           1  \n",
       "Leviathan, APT 40, TEMP.Periscope                                   1  \n",
       "Parisite, Fox Kitten, Pioneer Kitten                                1  \n",
       "Agrius                                                              1  \n",
       "Winnti Group, Blackfly, Wicked Panda                                1  \n",
       "Carbanak, Anunak                                                    1  \n",
       "Karakurt                                                            1  \n",
       "Sea Turtle                                                          1  \n",
       "Earth Wendigo                                                       0  \n",
       "Nazar                                                               0  \n",
       "Lapsus$                                                             0  \n",
       "Emissary Panda, APT 27, LuckyMouse, Bronze Union                    0  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "total_count = normalized_actors.sum(axis=1)\n",
    "reports_mentioned = normalized_actors.gt(0).sum(axis=1)\n",
    "\n",
    "actors_results = pd.concat([total_count,reports_mentioned],axis=1)\n",
    "actors_results.columns = ['total_count','reports_mentioned']\n",
    "\n",
    "print(actors_results.shape)\n",
    "actors_results.sort_values(by='total_count',ascending=False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observations:\n",
    "From the summed results can be seen that APT29 is mentioned the most by a big margin. There are 8 reports mentioning threat actors, and this actor appears in 6.\n",
    "\n",
    "Some actors are present in the list but have no occurences in the reports. This can be explained by the initial spreadsheet. Some reports are described of which no PDF is present. This is the case for online reports, existing only as a web page."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.4 Enrich data further\n",
    "#### 1.4.1 Add sector and TTP data\n",
    "Perform an outer join with the extracted actors and extra data from ETDA and MITRE. These two have been combined in a dataset byh tropChaud, which will be used for this. See [tropChaud.ipynb](tropChaud.ipynb) for exploration and functions for this data.\n",
    "\n",
    "Since in some cases MITRE had two different group IDs for the same ETDA actor, these TTPs are merged for the same ETDA actor. Within the TTP lists the duplicates are removed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['mitre_attack_id', 'mitre_attack_name', 'mitre_attack_aliases',\n",
      "       'mitre_attack_created', 'mitre_attack_last_modified', 'mitre_url',\n",
      "       'etda_id', 'etda_name', 'etda_aliases', 'etda_first_seen', 'etda_url',\n",
      "       'country', 'motivation', 'victim_industries', 'victim_countries',\n",
      "       'mitre_attack_ttps'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_json('data/Categorized_Adversary_TTPs.json')\n",
    "print(df.columns)\n",
    "\n",
    "enrich_columns = ['etda_name','victim_industries','mitre_attack_ttps']\n",
    "\n",
    "# Define helper functions\n",
    "\n",
    "# Retrieve information on an actor\n",
    "def get_actor_ETDA(actor):\n",
    "   return df.loc[df['etda_name'] == actor]\n",
    "                                      \n",
    "# Retrieve information on a list of actors\n",
    "def get_actor_list_ETDA(actor_list):\n",
    "   return df.loc[df['etda_name'].isin(actor_list)]\n",
    "\n",
    "# Get all industries\n",
    "def get_industries():\n",
    "    return to_1D(df['victim_industries']).value_counts().index.to_list()\n",
    "\n",
    "extracted_actors = actors_results.index.tolist()\n",
    "actors_extradata = get_actor_list_ETDA(extracted_actors)\n",
    "\n",
    "actors_extradata = actors_extradata[enrich_columns]\n",
    "actors_extradata.set_index('etda_name',inplace=True)\n",
    "\n",
    "actors_enriched = pd.merge(actors_results,actors_extradata,how='left',left_index=True,right_index=True)\n",
    "actors_enriched.index.name = 'etda_actor_name'\n",
    "\n",
    "\n",
    "actors_enriched = actors_enriched.groupby(['etda_actor_name']).agg({'total_count': 'first', 'reports_mentioned': 'first', 'victim_industries':'first','mitre_attack_ttps':'sum'}) #apply(lambda df: to_1D(df['mitre_attack_ttps']))\n",
    "actors_enriched['mitre_attack_ttps'] = actors_enriched['mitre_attack_ttps'].apply(lambda x: pd.Series(x).unique())\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1.4.2 Filter on sector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of mentioned actors targeting this sector: 17\n"
     ]
    },
    {
     "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>total_count</th>\n",
       "      <th>reports_mentioned</th>\n",
       "      <th>victim_industries</th>\n",
       "      <th>mitre_attack_ttps</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>etda_actor_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>APT 29, Cozy Bear, The Dukes</th>\n",
       "      <td>5.545455</td>\n",
       "      <td>6</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1078.004, T1001.002, T1087, T1562.004, T1560...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aquatic Panda</th>\n",
       "      <td>0.448485</td>\n",
       "      <td>2</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1595.002, T1027, T1003.001, T1059.003, T1588...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gamaredon Group</th>\n",
       "      <td>0.566667</td>\n",
       "      <td>2</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1559.001, T1036.005, T1218.011, T1608.001, T...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ke3chang, Vixen Panda, APT 15, GREF, Playful Dragon</th>\n",
       "      <td>0.166667</td>\n",
       "      <td>1</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1007, T1071.004, T1082, T1560.001, T1059, T1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kimsuky, Velvet Chollima</th>\n",
       "      <td>0.833333</td>\n",
       "      <td>2</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1059.001, T1594, T1136.001, T1560.001, T1562...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lazarus Group, Hidden Cobra, Labyrinth Chollima</th>\n",
       "      <td>0.733333</td>\n",
       "      <td>3</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1573.001, T1070.003, T1588.002, T1560.002, T...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leviathan, APT 40, TEMP.Periscope</th>\n",
       "      <td>0.100000</td>\n",
       "      <td>1</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1078, T1189, T1003.001, T1572, T1021.001, T1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Magic Hound, APT 35, Cobalt Illusion, Charming Kitten</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>2</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1105, T1053.005, T1059.001, T1586.002, T1564...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Moses Staff</th>\n",
       "      <td>0.290909</td>\n",
       "      <td>2</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1105, T1587.001, T1087.001, T1505.003, T1588...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MuddyWater, Seedworm, TEMP.Zagros, Static Kitten</th>\n",
       "      <td>0.400000</td>\n",
       "      <td>1</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1059.007, T1057, T1087.002, T1555, T1105, T1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mustang Panda, Bronze President</th>\n",
       "      <td>0.133333</td>\n",
       "      <td>1</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1566.002, T1573.001, T1003.003, T1546.003, T...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Parisite, Fox Kitten, Pioneer Kitten</th>\n",
       "      <td>0.090909</td>\n",
       "      <td>1</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1012, T1083, T1505.003, T1046, T1190, T1036....</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Reaper, APT 37, Ricochet Chollima, ScarCruft</th>\n",
       "      <td>0.133333</td>\n",
       "      <td>1</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1055, T1053.005, T1189, T1559.002, T1566.001...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sandworm Team, Iron Viking, Voodoo Bear</th>\n",
       "      <td>0.833333</td>\n",
       "      <td>2</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1491.002, T1070.004, T1027, T1594, T1140, T1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sofacy, APT 28, Fancy Bear, Sednit</th>\n",
       "      <td>0.730303</td>\n",
       "      <td>3</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1036.005, T1218.011, T1566.001, T1211, T1498...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Winnti Group, Blackfly, Wicked Panda</th>\n",
       "      <td>0.090909</td>\n",
       "      <td>1</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1083, T1583.001, T1057, T1553.002, T1105, T1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wizard Spider, Gold Blackburn</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>2</td>\n",
       "      <td>Government</td>\n",
       "      <td>[T1070.004, T1557.001, T1543.003, T1003.002, T...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    total_count  \\\n",
       "etda_actor_name                                                   \n",
       "APT 29, Cozy Bear, The Dukes                           5.545455   \n",
       "Aquatic Panda                                          0.448485   \n",
       "Gamaredon Group                                        0.566667   \n",
       "Ke3chang, Vixen Panda, APT 15, GREF, Playful Dr...     0.166667   \n",
       "Kimsuky, Velvet Chollima                               0.833333   \n",
       "Lazarus Group, Hidden Cobra, Labyrinth Chollima        0.733333   \n",
       "Leviathan, APT 40, TEMP.Periscope                      0.100000   \n",
       "Magic Hound, APT 35, Cobalt Illusion, Charming ...     0.500000   \n",
       "Moses Staff                                            0.290909   \n",
       "MuddyWater, Seedworm, TEMP.Zagros, Static Kitten       0.400000   \n",
       "Mustang Panda, Bronze President                        0.133333   \n",
       "Parisite, Fox Kitten, Pioneer Kitten                   0.090909   \n",
       "Reaper, APT 37, Ricochet Chollima, ScarCruft           0.133333   \n",
       "Sandworm Team, Iron Viking, Voodoo Bear                0.833333   \n",
       "Sofacy, APT 28, Fancy Bear, Sednit                     0.730303   \n",
       "Winnti Group, Blackfly, Wicked Panda                   0.090909   \n",
       "Wizard Spider, Gold Blackburn                          2.000000   \n",
       "\n",
       "                                                    reports_mentioned  \\\n",
       "etda_actor_name                                                         \n",
       "APT 29, Cozy Bear, The Dukes                                        6   \n",
       "Aquatic Panda                                                       2   \n",
       "Gamaredon Group                                                     2   \n",
       "Ke3chang, Vixen Panda, APT 15, GREF, Playful Dr...                  1   \n",
       "Kimsuky, Velvet Chollima                                            2   \n",
       "Lazarus Group, Hidden Cobra, Labyrinth Chollima                     3   \n",
       "Leviathan, APT 40, TEMP.Periscope                                   1   \n",
       "Magic Hound, APT 35, Cobalt Illusion, Charming ...                  2   \n",
       "Moses Staff                                                         2   \n",
       "MuddyWater, Seedworm, TEMP.Zagros, Static Kitten                    1   \n",
       "Mustang Panda, Bronze President                                     1   \n",
       "Parisite, Fox Kitten, Pioneer Kitten                                1   \n",
       "Reaper, APT 37, Ricochet Chollima, ScarCruft                        1   \n",
       "Sandworm Team, Iron Viking, Voodoo Bear                             2   \n",
       "Sofacy, APT 28, Fancy Bear, Sednit                                  3   \n",
       "Winnti Group, Blackfly, Wicked Panda                                1   \n",
       "Wizard Spider, Gold Blackburn                                       2   \n",
       "\n",
       "                                                   victim_industries  \\\n",
       "etda_actor_name                                                        \n",
       "APT 29, Cozy Bear, The Dukes                              Government   \n",
       "Aquatic Panda                                             Government   \n",
       "Gamaredon Group                                           Government   \n",
       "Ke3chang, Vixen Panda, APT 15, GREF, Playful Dr...        Government   \n",
       "Kimsuky, Velvet Chollima                                  Government   \n",
       "Lazarus Group, Hidden Cobra, Labyrinth Chollima           Government   \n",
       "Leviathan, APT 40, TEMP.Periscope                         Government   \n",
       "Magic Hound, APT 35, Cobalt Illusion, Charming ...        Government   \n",
       "Moses Staff                                               Government   \n",
       "MuddyWater, Seedworm, TEMP.Zagros, Static Kitten          Government   \n",
       "Mustang Panda, Bronze President                           Government   \n",
       "Parisite, Fox Kitten, Pioneer Kitten                      Government   \n",
       "Reaper, APT 37, Ricochet Chollima, ScarCruft              Government   \n",
       "Sandworm Team, Iron Viking, Voodoo Bear                   Government   \n",
       "Sofacy, APT 28, Fancy Bear, Sednit                        Government   \n",
       "Winnti Group, Blackfly, Wicked Panda                      Government   \n",
       "Wizard Spider, Gold Blackburn                             Government   \n",
       "\n",
       "                                                                                    mitre_attack_ttps  \n",
       "etda_actor_name                                                                                        \n",
       "APT 29, Cozy Bear, The Dukes                        [T1078.004, T1001.002, T1087, T1562.004, T1560...  \n",
       "Aquatic Panda                                       [T1595.002, T1027, T1003.001, T1059.003, T1588...  \n",
       "Gamaredon Group                                     [T1559.001, T1036.005, T1218.011, T1608.001, T...  \n",
       "Ke3chang, Vixen Panda, APT 15, GREF, Playful Dr...  [T1007, T1071.004, T1082, T1560.001, T1059, T1...  \n",
       "Kimsuky, Velvet Chollima                            [T1059.001, T1594, T1136.001, T1560.001, T1562...  \n",
       "Lazarus Group, Hidden Cobra, Labyrinth Chollima     [T1573.001, T1070.003, T1588.002, T1560.002, T...  \n",
       "Leviathan, APT 40, TEMP.Periscope                   [T1078, T1189, T1003.001, T1572, T1021.001, T1...  \n",
       "Magic Hound, APT 35, Cobalt Illusion, Charming ...  [T1105, T1053.005, T1059.001, T1586.002, T1564...  \n",
       "Moses Staff                                         [T1105, T1587.001, T1087.001, T1505.003, T1588...  \n",
       "MuddyWater, Seedworm, TEMP.Zagros, Static Kitten    [T1059.007, T1057, T1087.002, T1555, T1105, T1...  \n",
       "Mustang Panda, Bronze President                     [T1566.002, T1573.001, T1003.003, T1546.003, T...  \n",
       "Parisite, Fox Kitten, Pioneer Kitten                [T1012, T1083, T1505.003, T1046, T1190, T1036....  \n",
       "Reaper, APT 37, Ricochet Chollima, ScarCruft        [T1055, T1053.005, T1189, T1559.002, T1566.001...  \n",
       "Sandworm Team, Iron Viking, Voodoo Bear             [T1491.002, T1070.004, T1027, T1594, T1140, T1...  \n",
       "Sofacy, APT 28, Fancy Bear, Sednit                  [T1036.005, T1218.011, T1566.001, T1211, T1498...  \n",
       "Winnti Group, Blackfly, Wicked Panda                [T1083, T1583.001, T1057, T1553.002, T1105, T1...  \n",
       "Wizard Spider, Gold Blackburn                       [T1070.004, T1557.001, T1543.003, T1003.002, T...  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def filter_by_sector(df, sector):\n",
    "    actors_sector_exploded = df.explode('victim_industries')\n",
    "    return actors_sector_exploded.loc[actors_sector_exploded['victim_industries'] == sector]\n",
    "\n",
    "actors_filtered = filter_by_sector(actors_enriched,SECTOR)\n",
    "# Remove actors that are not mentioned\n",
    "actors_filtered = actors_filtered[actors_filtered['reports_mentioned']!=0]\n",
    "print(\"Number of mentioned actors targeting this sector:\",len(actors_filtered))\n",
    "actors_filtered"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Rank actors and TTPs\n",
    "### 2.1 Rank actors\n",
    "#### 2.1.1 Create weight and sort"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "T1105        16\n",
       "T1027        16\n",
       "T1059.003    14\n",
       "T1082        13\n",
       "T1059.001    13\n",
       "             ..\n",
       "T1027.006     1\n",
       "T1213.003     1\n",
       "T1591.004     1\n",
       "T1202         1\n",
       "T1135         1\n",
       "Length: 288, dtype: int64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actors_filtered['actor_weight'] = normalize(actors_filtered['total_count'])\n",
    "\n",
    "actors_filtered.sort_values(by='actor_weight',ascending=False)\n",
    "\n",
    "actors_ranked = actors_filtered[['actor_weight','mitre_attack_ttps']]\n",
    "to_1D(actors_ranked['mitre_attack_ttps']).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Top 5 actors targeting Government sector by weight'}, xlabel='Actor Name', ylabel='etda_actor_name'>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "actor_weights = actors_ranked['actor_weight']\n",
    "actor_weights.nlargest(5).plot(kind='barh',xlabel='Actor Name', title=\"Top 5 actors targeting {} sector by weight\".format(SECTOR))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observations\n",
    "Since the Government sector is the most represented in the ETDA dataset, this one is chosen for the tests. 13 of the actors from the reports target this sector. APT 29 is mentioned the most across reports. This is due to their notorious SolarWinds attack in 2020, which is mentioned often. In 2021 they also launched a big spear-phishing campaign. This actor is followed by Wizard Spider, a ransomware actor that is very active.\n",
    "\n",
    "It is mainly these two actors that exceed the others in terms of how often they are mentioned. The other mentioned actors have a weigth just below 1.0."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2. Rank TTPs\n",
    "#### 2.3.1 Explode dataframe per TTP\n",
    "Explode the dataframe per TTP. Now a weighting calculation can be done per TTP, based on the information provided. Information includes the actor results (and kill chain phase).\n",
    "\n",
    "For now: the actor weights are summed per TTP to obtain a ranking per TTP. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "actors_ttp_exploded = actors_ranked.explode('mitre_attack_ttps')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.3.2. Group by TTP and sum actor weights\n",
    "Sum the actor weights."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "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>actor_weight</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mitre_attack_ttps</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>T1027</th>\n",
       "      <td>2.209444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T1059.003</th>\n",
       "      <td>2.171111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T1059.001</th>\n",
       "      <td>2.151111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T1071.001</th>\n",
       "      <td>2.105556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T1588.002</th>\n",
       "      <td>2.105000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T1197</th>\n",
       "      <td>0.001667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T1585</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T1217</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T1555.005</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>T1530</th>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>288 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   actor_weight\n",
       "mitre_attack_ttps              \n",
       "T1027                  2.209444\n",
       "T1059.003              2.171111\n",
       "T1059.001              2.151111\n",
       "T1071.001              2.105556\n",
       "T1588.002              2.105000\n",
       "...                         ...\n",
       "T1197                  0.001667\n",
       "T1585                  0.000000\n",
       "T1217                  0.000000\n",
       "T1555.005              0.000000\n",
       "T1530                  0.000000\n",
       "\n",
       "[288 rows x 1 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "actors_ttp_summed = actors_ttp_exploded.reset_index(drop=True)\n",
    "ttps_ranked = actors_ttp_summed.groupby('mitre_attack_ttps').sum()\n",
    "ttps_ranked.sort_values(by='actor_weight',ascending=False)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.3.3 Enrich TTP information\n",
    "Information from the ATT&CK data is used via the attackcti package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[taxii2client.v20] [WARNING ] [2023-08-15 11:40:38,833] TAXII Server Response did not include 'Content-Range' header - results could be incomplete.\n",
      "[taxii2client.v20] [WARNING ] [2023-08-15 11:40:38,979] TAXII Server Response with different amount of objects! Setting per_request=750\n"
     ]
    }
   ],
   "source": [
    "from attackcti import attack_client\n",
    "from pandas import json_normalize\n",
    "import sys\n",
    "\n",
    "mitre_columns = ['technique_id','technique','kill_chain_phases','id','tactic','technique_detection','impact_type']\n",
    "\n",
    "def get_attck_dataframe(matrix = 'enterprise'):\n",
    "    if  (matrix.lower() == 'enterprise'):\n",
    "        # Instantiating attack_client class\n",
    "        lift = attack_client()\n",
    "        # Getting techniques for windows platform - enterprise matrix\n",
    "        attck = lift.get_enterprise_techniques(stix_format = False)\n",
    "        # Generating a dataframe with information collected\n",
    "        attck = json_normalize(attck)\n",
    "        return attck\n",
    "    else:\n",
    "        sys.exit('ERROR: Only Enterprise available!!')\n",
    "\n",
    "attck = get_attck_dataframe()\n",
    "attck = attck[mitre_columns]\n",
    "\n",
    "ttps_enriched = pd.merge(ttps_ranked,attck,how='left',left_index=True,right_on='technique_id')\n",
    "ttps_enriched.index = ttps_ranked.index\n",
    "ttps_enriched['technique_name_id'] = ttps_enriched['technique'] + \" (\" + ttps_enriched['technique_id'] + \")\""
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2.3.4. Calculate weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "ttps_enriched['ttp_weight'] = normalize(ttps_enriched['actor_weight'])\n",
    "ttps_enriched = ttps_enriched.drop(['actor_weight'],axis=1)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Top 10 techniques for actors targeting Government sector'}, xlabel='TTP Name and ATT&CK ID', ylabel='technique_name_id'>"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ttps_enriched.nlargest(10,columns='ttp_weight').plot.barh(y='ttp_weight',x='technique_name_id',xlabel=\"TTP Name and ATT&CK ID\" ,title=\"Top 10 techniques for actors targeting {} sector\".format(SECTOR))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observations\n",
    "Within the tested Government sector, the top 10 techniques used are shown above. \n",
    "The top technique is '[Obfuscated Files or Information](https://attack.mitre.org/techniques/T1027/)', where adversaries obfuscate the contents of an executable or file by encrypting, encoding, compressing or otherwise obscuring them on the system or in transit. This is common behavior to evade defenses. \n",
    "\n",
    "The second technique is '[Tool]'(https://attack.mitre.org/techniques/T1588/002/), is described as \"Adversaries may buy, steal or download software tools that can be used during targeting.\" This is a very generic technique, since the use of the use of tools is common among hackers and there exists a wide variety of tools, hence why it is listed in such a high position."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Control prioritization"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 Control Mapping\n",
    "Source of the mapping: [Security Control Framework Mappings to ATT&CK](https://github.com/center-for-threat-informed-defense/attack-control-framework-mappings).\n",
    "\n",
    "This maps controls from NIST 800-53 to MITRE ATT&CK. The following versions are considered:\n",
    "- MITRE ATT&CK v10.1\n",
    "- NIST 800-53 Revision 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load ATT&CK to NIST 800-53 mapping\n",
    "def get_nist_sp800_53_attck_mapping():\n",
    "    nist_attck_mapping = pd.read_excel(\"data/mappings/nist800-53-r5-mappings-attckv12.xlsx\")\n",
    "    nist_attck_mapping = nist_attck_mapping.drop([\"Mapping Type\",\"Technique Name\"],axis=1)\n",
    "    return nist_attck_mapping\n",
    "\n",
    "def get_nist_csf_attck_mapping():\n",
    "    nist_attck_mapping = pd.read_excel(\"data/mappings/NIST_CSF_ATTCKv12.xlsx\")\n",
    "    return nist_attck_mapping\n",
    "\n",
    "def get_cis_attck_mapping():\n",
    "    cis_attck_mapping = pd.read_excel(\"data/mappings/CIS_Controls_v8_ATTCKv82_condensed.xlsx\")\n",
    "    cis_attck_mapping = cis_attck_mapping.drop([\"CIS Controls v8\",\"CIS Controls\",\"Asset Type\"],axis=1)\n",
    "    cis_attck_mapping['Technique ID'] = cis_attck_mapping['Technique ID'].str.split(', ')\n",
    "    cis_attck_mapping.drop('Description',axis=1)\n",
    "    return cis_attck_mapping.explode('Technique ID')\n",
    "\n",
    "def get_iso_attck_mapping():\n",
    "    iso_attck_mapping = pd.read_excel(\"data/mappings/ISO_27001_2022_ATTCKv82.xlsx\")\n",
    "    return iso_attck_mapping\n",
    "\n",
    "def get_nist_iso_2013_attck_mapping():\n",
    "    iso_attck_mapping = pd.read_excel(\"data/mappings/ISO_27001_2013_ATTCKv10.1_FROM_NIST.xlsx\")\n",
    "    return iso_attck_mapping\n",
    "\n",
    "def get_cis_iso_2013_attck_mapping():\n",
    "    iso_attck_mapping = pd.read_excel(\"data/mappings/ISO_27001_2013_ATTCKv82.xlsx\")\n",
    "    return iso_attck_mapping\n",
    "\n",
    "def get_cis7_iso_2013_attck_mapping():\n",
    "    iso_attck_mapping = pd.read_excel(\"data/mappings/ISO_27001_2013_ATTCKv82_FROM_CIS7.xlsx\")\n",
    "    return iso_attck_mapping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Taking 100%; 288 entries\n"
     ]
    }
   ],
   "source": [
    "PERCENTAGE = 1\n",
    "\n",
    "def take_percentage(percentage,df):\n",
    "    top_percent = int(len(df) * PERCENTAGE)\n",
    "    print(\"Taking {}%; {} entries\".format(percentage*100,top_percent))\n",
    "    return df.nlargest(top_percent,columns=\"ttp_weight\")\n",
    "\n",
    "def take_threshold(threshold, df):\n",
    "    return df.loc[df['ttp_weight']>threshold]\n",
    "\n",
    "\n",
    "ttps_enriched = take_percentage(PERCENTAGE,ttps_enriched)\n",
    "# ttps_enriched = take_threshold(TTP_THRESHOLD,ttps_enriched)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of TTPS: 196\n",
      "Number of controls: 109\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Control ID</th>\n",
       "      <th>Control Name</th>\n",
       "      <th>Technique ID</th>\n",
       "      <th>technique_id</th>\n",
       "      <th>technique</th>\n",
       "      <th>kill_chain_phases</th>\n",
       "      <th>id</th>\n",
       "      <th>tactic</th>\n",
       "      <th>technique_detection</th>\n",
       "      <th>impact_type</th>\n",
       "      <th>technique_name_id</th>\n",
       "      <th>ttp_weight</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2272</th>\n",
       "      <td>SI-3</td>\n",
       "      <td>Malicious Code Protection</td>\n",
       "      <td>T1027</td>\n",
       "      <td>T1027</td>\n",
       "      <td>Obfuscated Files or Information</td>\n",
       "      <td>[{'kill_chain_name': 'mitre-attack', 'phase_na...</td>\n",
       "      <td>attack-pattern--b3d682b6-98f2-4fb0-aa3b-b4df00...</td>\n",
       "      <td>[defense-evasion]</td>\n",
       "      <td>Detection of file obfuscation is difficult unl...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Obfuscated Files or Information (T1027)</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2273</th>\n",
       "      <td>SI-4</td>\n",
       "      <td>System Monitoring</td>\n",
       "      <td>T1027</td>\n",
       "      <td>T1027</td>\n",
       "      <td>Obfuscated Files or Information</td>\n",
       "      <td>[{'kill_chain_name': 'mitre-attack', 'phase_na...</td>\n",
       "      <td>attack-pattern--b3d682b6-98f2-4fb0-aa3b-b4df00...</td>\n",
       "      <td>[defense-evasion]</td>\n",
       "      <td>Detection of file obfuscation is difficult unl...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Obfuscated Files or Information (T1027)</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2274</th>\n",
       "      <td>SI-7</td>\n",
       "      <td>Software, Firmware, and Information Integrity</td>\n",
       "      <td>T1027</td>\n",
       "      <td>T1027</td>\n",
       "      <td>Obfuscated Files or Information</td>\n",
       "      <td>[{'kill_chain_name': 'mitre-attack', 'phase_na...</td>\n",
       "      <td>attack-pattern--b3d682b6-98f2-4fb0-aa3b-b4df00...</td>\n",
       "      <td>[defense-evasion]</td>\n",
       "      <td>Detection of file obfuscation is difficult unl...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Obfuscated Files or Information (T1027)</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2270</th>\n",
       "      <td>CM-6</td>\n",
       "      <td>Configuration Settings</td>\n",
       "      <td>T1027</td>\n",
       "      <td>T1027</td>\n",
       "      <td>Obfuscated Files or Information</td>\n",
       "      <td>[{'kill_chain_name': 'mitre-attack', 'phase_na...</td>\n",
       "      <td>attack-pattern--b3d682b6-98f2-4fb0-aa3b-b4df00...</td>\n",
       "      <td>[defense-evasion]</td>\n",
       "      <td>Detection of file obfuscation is difficult unl...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Obfuscated Files or Information (T1027)</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2269</th>\n",
       "      <td>CM-2</td>\n",
       "      <td>Baseline Configuration</td>\n",
       "      <td>T1027</td>\n",
       "      <td>T1027</td>\n",
       "      <td>Obfuscated Files or Information</td>\n",
       "      <td>[{'kill_chain_name': 'mitre-attack', 'phase_na...</td>\n",
       "      <td>attack-pattern--b3d682b6-98f2-4fb0-aa3b-b4df00...</td>\n",
       "      <td>[defense-evasion]</td>\n",
       "      <td>Detection of file obfuscation is difficult unl...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Obfuscated Files or Information (T1027)</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>IA-4</td>\n",
       "      <td>Identifier Management</td>\n",
       "      <td>T1530</td>\n",
       "      <td>T1530</td>\n",
       "      <td>Data from Cloud Storage</td>\n",
       "      <td>[{'kill_chain_name': 'mitre-attack', 'phase_na...</td>\n",
       "      <td>attack-pattern--3298ce88-1628-43b1-87d9-0b5336...</td>\n",
       "      <td>[collection]</td>\n",
       "      <td>Monitor for unusual queries to the cloud provi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Data from Cloud Storage (T1530)</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>IA-5</td>\n",
       "      <td>Authenticator Management</td>\n",
       "      <td>T1530</td>\n",
       "      <td>T1530</td>\n",
       "      <td>Data from Cloud Storage</td>\n",
       "      <td>[{'kill_chain_name': 'mitre-attack', 'phase_na...</td>\n",
       "      <td>attack-pattern--3298ce88-1628-43b1-87d9-0b5336...</td>\n",
       "      <td>[collection]</td>\n",
       "      <td>Monitor for unusual queries to the cloud provi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Data from Cloud Storage (T1530)</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>IA-6</td>\n",
       "      <td>Authentication Feedback</td>\n",
       "      <td>T1530</td>\n",
       "      <td>T1530</td>\n",
       "      <td>Data from Cloud Storage</td>\n",
       "      <td>[{'kill_chain_name': 'mitre-attack', 'phase_na...</td>\n",
       "      <td>attack-pattern--3298ce88-1628-43b1-87d9-0b5336...</td>\n",
       "      <td>[collection]</td>\n",
       "      <td>Monitor for unusual queries to the cloud provi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Data from Cloud Storage (T1530)</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>IA-8</td>\n",
       "      <td>Identification and Authentication (non-organiz...</td>\n",
       "      <td>T1530</td>\n",
       "      <td>T1530</td>\n",
       "      <td>Data from Cloud Storage</td>\n",
       "      <td>[{'kill_chain_name': 'mitre-attack', 'phase_na...</td>\n",
       "      <td>attack-pattern--3298ce88-1628-43b1-87d9-0b5336...</td>\n",
       "      <td>[collection]</td>\n",
       "      <td>Monitor for unusual queries to the cloud provi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Data from Cloud Storage (T1530)</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>RA-5</td>\n",
       "      <td>Vulnerability Monitoring and Scanning</td>\n",
       "      <td>T1530</td>\n",
       "      <td>T1530</td>\n",
       "      <td>Data from Cloud Storage</td>\n",
       "      <td>[{'kill_chain_name': 'mitre-attack', 'phase_na...</td>\n",
       "      <td>attack-pattern--3298ce88-1628-43b1-87d9-0b5336...</td>\n",
       "      <td>[collection]</td>\n",
       "      <td>Monitor for unusual queries to the cloud provi...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Data from Cloud Storage (T1530)</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2345 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Control ID                                       Control Name  \\\n",
       "2272       SI-3                          Malicious Code Protection   \n",
       "2273       SI-4                                  System Monitoring   \n",
       "2274       SI-7      Software, Firmware, and Information Integrity   \n",
       "2270       CM-6                             Configuration Settings   \n",
       "2269       CM-2                             Baseline Configuration   \n",
       "...         ...                                                ...   \n",
       "495        IA-4                              Identifier Management   \n",
       "496        IA-5                           Authenticator Management   \n",
       "497        IA-6                            Authentication Feedback   \n",
       "498        IA-8  Identification and Authentication (non-organiz...   \n",
       "499        RA-5              Vulnerability Monitoring and Scanning   \n",
       "\n",
       "     Technique ID technique_id                        technique  \\\n",
       "2272        T1027        T1027  Obfuscated Files or Information   \n",
       "2273        T1027        T1027  Obfuscated Files or Information   \n",
       "2274        T1027        T1027  Obfuscated Files or Information   \n",
       "2270        T1027        T1027  Obfuscated Files or Information   \n",
       "2269        T1027        T1027  Obfuscated Files or Information   \n",
       "...           ...          ...                              ...   \n",
       "495         T1530        T1530          Data from Cloud Storage   \n",
       "496         T1530        T1530          Data from Cloud Storage   \n",
       "497         T1530        T1530          Data from Cloud Storage   \n",
       "498         T1530        T1530          Data from Cloud Storage   \n",
       "499         T1530        T1530          Data from Cloud Storage   \n",
       "\n",
       "                                      kill_chain_phases  \\\n",
       "2272  [{'kill_chain_name': 'mitre-attack', 'phase_na...   \n",
       "2273  [{'kill_chain_name': 'mitre-attack', 'phase_na...   \n",
       "2274  [{'kill_chain_name': 'mitre-attack', 'phase_na...   \n",
       "2270  [{'kill_chain_name': 'mitre-attack', 'phase_na...   \n",
       "2269  [{'kill_chain_name': 'mitre-attack', 'phase_na...   \n",
       "...                                                 ...   \n",
       "495   [{'kill_chain_name': 'mitre-attack', 'phase_na...   \n",
       "496   [{'kill_chain_name': 'mitre-attack', 'phase_na...   \n",
       "497   [{'kill_chain_name': 'mitre-attack', 'phase_na...   \n",
       "498   [{'kill_chain_name': 'mitre-attack', 'phase_na...   \n",
       "499   [{'kill_chain_name': 'mitre-attack', 'phase_na...   \n",
       "\n",
       "                                                     id             tactic  \\\n",
       "2272  attack-pattern--b3d682b6-98f2-4fb0-aa3b-b4df00...  [defense-evasion]   \n",
       "2273  attack-pattern--b3d682b6-98f2-4fb0-aa3b-b4df00...  [defense-evasion]   \n",
       "2274  attack-pattern--b3d682b6-98f2-4fb0-aa3b-b4df00...  [defense-evasion]   \n",
       "2270  attack-pattern--b3d682b6-98f2-4fb0-aa3b-b4df00...  [defense-evasion]   \n",
       "2269  attack-pattern--b3d682b6-98f2-4fb0-aa3b-b4df00...  [defense-evasion]   \n",
       "...                                                 ...                ...   \n",
       "495   attack-pattern--3298ce88-1628-43b1-87d9-0b5336...       [collection]   \n",
       "496   attack-pattern--3298ce88-1628-43b1-87d9-0b5336...       [collection]   \n",
       "497   attack-pattern--3298ce88-1628-43b1-87d9-0b5336...       [collection]   \n",
       "498   attack-pattern--3298ce88-1628-43b1-87d9-0b5336...       [collection]   \n",
       "499   attack-pattern--3298ce88-1628-43b1-87d9-0b5336...       [collection]   \n",
       "\n",
       "                                    technique_detection impact_type  \\\n",
       "2272  Detection of file obfuscation is difficult unl...         NaN   \n",
       "2273  Detection of file obfuscation is difficult unl...         NaN   \n",
       "2274  Detection of file obfuscation is difficult unl...         NaN   \n",
       "2270  Detection of file obfuscation is difficult unl...         NaN   \n",
       "2269  Detection of file obfuscation is difficult unl...         NaN   \n",
       "...                                                 ...         ...   \n",
       "495   Monitor for unusual queries to the cloud provi...         NaN   \n",
       "496   Monitor for unusual queries to the cloud provi...         NaN   \n",
       "497   Monitor for unusual queries to the cloud provi...         NaN   \n",
       "498   Monitor for unusual queries to the cloud provi...         NaN   \n",
       "499   Monitor for unusual queries to the cloud provi...         NaN   \n",
       "\n",
       "                            technique_name_id  ttp_weight  \n",
       "2272  Obfuscated Files or Information (T1027)         1.0  \n",
       "2273  Obfuscated Files or Information (T1027)         1.0  \n",
       "2274  Obfuscated Files or Information (T1027)         1.0  \n",
       "2270  Obfuscated Files or Information (T1027)         1.0  \n",
       "2269  Obfuscated Files or Information (T1027)         1.0  \n",
       "...                                       ...         ...  \n",
       "495           Data from Cloud Storage (T1530)         0.0  \n",
       "496           Data from Cloud Storage (T1530)         0.0  \n",
       "497           Data from Cloud Storage (T1530)         0.0  \n",
       "498           Data from Cloud Storage (T1530)         0.0  \n",
       "499           Data from Cloud Storage (T1530)         0.0  \n",
       "\n",
       "[2345 rows x 12 columns]"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ttp_control_map = get_iso_attck_mapping()\n",
    "if CONTROLS == \"ISO_2013_CIS\":\n",
    "    ttp_control_map = get_cis_iso_2013_attck_mapping()\n",
    "elif CONTROLS == \"ISO_2013_CIS7\":\n",
    "    ttp_control_map = get_cis7_iso_2013_attck_mapping()\n",
    "elif CONTROLS == \"ISO_2013_NIST\":\n",
    "    ttp_control_map = get_nist_iso_2013_attck_mapping()\n",
    "elif CONTROLS == \"ISO_2022\":\n",
    "    ttp_control_map = get_iso_attck_mapping()\n",
    "elif CONTROLS == \"NIST_SP_800_53\":\n",
    "    ttp_control_map = get_nist_sp800_53_attck_mapping()\n",
    "elif CONTROLS == \"NIST_CSF\":\n",
    "    ttp_control_map = get_nist_csf_attck_mapping()\n",
    "elif CONTROLS == \"CIS_v8\":\n",
    "    ttp_control_map = get_cis_attck_mapping()\n",
    "\n",
    "# ttp_control_merge = ttp_control_map.merge(ttps_enriched, left_on=\"Technique ID\", right_on=\"technique_id\",how=\"inner\")\n",
    "ttp_control_merge = ttp_control_map.merge(ttps_enriched, left_on=\"Technique ID\", right_on=\"mitre_attack_ttps\",how=\"inner\")\n",
    "ttp_control_merge = ttp_control_merge.loc[ttp_control_merge[\"Control ID\"] != '/']\n",
    "ttp_control_merge = ttp_control_merge.loc[ttp_control_merge[\"Control ID\"] != 'None']\n",
    "ttp_control_merge = ttp_control_merge.loc[ttp_control_merge[\"Control Name\"] != 'Vervallen']\n",
    "\n",
    "ttp_control_merge.sort_values(by='ttp_weight',inplace=True,ascending=False)\n",
    "print(\"Number of TTPS:\",ttp_control_merge['Technique ID'].value_counts().index.size)\n",
    "print(\"Number of controls:\",ttp_control_merge['Control ID'].value_counts().index.size)\n",
    "ttp_control_merge"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get TTPs incl number of controls that mitigate them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Distribution of TTP weights for actors targeting Government sector'}, ylabel='Frequency'>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ttp_control_merge[['Technique ID','ttp_weight']].drop_duplicates().plot(kind='hist',bins=30,title=\"Distribution of TTP weights for actors targeting {} sector\".format(SECTOR))\n",
    "# ttp_control_merge['ttp_weight'].plot(kind='hist',bins=30,title=\"Distribution of TTP weights for actors targeting {} sector\".format(SECTOR),xlabel=\"TTP weights\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Abe\\AppData\\Local\\Temp\\ipykernel_11780\\2258918078.py:3: FutureWarning: The default value of numeric_only in DataFrameGroupBy.sum is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  ttp_control_ranked = ttp_control_merge.groupby(['Control ID','Control Name']).sum()\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Top controls by number of mitigated TTPs. Top 100% of TTPS'}, ylabel='Control ID,Control Name'>"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# ttp_control_merge[['Control ID','Control Name']].value_counts().nlargest(10).plot(kind='barh',title=\"Number of selected TTPs mitigated per control\")\n",
    "\n",
    "ttp_control_ranked = ttp_control_merge.groupby(['Control ID','Control Name']).sum()\n",
    "ttp_control_ranked.sort_values(by='ttp_weight',ascending=False)\n",
    "\n",
    "# ttp_control_ranked.nlargest(10,columns='ttp_weight').plot(kind='barh',title=\"Top controls by number of mitigated TTPs. No TTP threshold\")\n",
    "ttp_control_ranked.nlargest(10,columns='ttp_weight').plot(kind='barh',title=\"Top controls by number of mitigated TTPs. Top {}% of TTPS\".format(PERCENTAGE*100))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Observations\n",
    "There are some controls that map to a lot of TTPs. This results in a large set of TTP-Control mappings. Since there is no measure of control effectiveness to a TTP in this data, they can currently only be sorted based on the TTPs they control and their respective weights.\n",
    "\n",
    "There are two ways to approach the ranking, either TTP based on Control based:\n",
    "- TTP: Take the most prominent TTPs, which are ranked, and show the controls for this\n",
    "- Control: Rank the controls based on the number of TTPs they control and their respective weights. The downside of this is that controls that map to a large number of TTPs will probably always end up on top. This means that the initial TTP ranking matters less."
   ]
  }
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