{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Antivirus Relevant File Paths Alerts\n",
    "Detects an Antivirus alert in a highly relevant file path or with a relevant file name"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rule Content\n",
    "```\n",
    "- title: Antivirus Relevant File Paths Alerts\n",
    "  id: c9a88268-0047-4824-ba6e-4d81ce0b907c\n",
    "  description: Detects an Antivirus alert in a highly relevant file path or with a\n",
    "    relevant file name\n",
    "  date: 2018/09/09\n",
    "  modified: 2019/10/04\n",
    "  author: Florian Roth\n",
    "  references:\n",
    "  - https://www.nextron-systems.com/2018/09/08/antivirus-event-analysis-cheat-sheet-v1-4/\n",
    "  logsource:\n",
    "    product: antivirus\n",
    "    service: null\n",
    "    category: null\n",
    "  detection:\n",
    "    selection:\n",
    "      FileName:\n",
    "      - C:\\Windows\\Temp\\\\*\n",
    "      - C:\\Temp\\\\*\n",
    "      - '*\\\\Client\\\\*'\n",
    "      - C:\\PerfLogs\\\\*\n",
    "      - C:\\Users\\Public\\\\*\n",
    "      - C:\\Users\\Default\\\\*\n",
    "      - '*.ps1'\n",
    "      - '*.vbs'\n",
    "      - '*.bat'\n",
    "      - '*.chm'\n",
    "      - '*.xml'\n",
    "      - '*.txt'\n",
    "      - '*.jsp'\n",
    "      - '*.jspx'\n",
    "      - '*.asp'\n",
    "      - '*.aspx'\n",
    "      - '*.php'\n",
    "      - '*.war'\n",
    "      - '*.hta'\n",
    "      - '*.lnk'\n",
    "      - '*.scf'\n",
    "      - '*.sct'\n",
    "      - '*.vbe'\n",
    "      - '*.wsf'\n",
    "      - '*.wsh'\n",
    "    condition: selection\n",
    "  fields:\n",
    "  - Signature\n",
    "  - User\n",
    "  falsepositives:\n",
    "  - Unlikely\n",
    "  level: high\n",
    "\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Querying Elasticsearch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Import Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from elasticsearch import Elasticsearch\n",
    "from elasticsearch_dsl import Search\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initialize Elasticsearch client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "es = Elasticsearch(['http://helk-elasticsearch:9200'])\n",
    "searchContext = Search(using=es, index='logs-*', doc_type='doc')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run Elasticsearch Query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = searchContext.query('query_string', query='file_name.keyword:(C\\:\\\\Windows\\\\Temp\\\\* OR C\\:\\\\Temp\\\\* OR *\\\\Client\\\\* OR C\\:\\\\PerfLogs\\\\* OR C\\:\\\\Users\\\\Public\\\\* OR C\\:\\\\Users\\\\Default\\\\* OR *.ps1 OR *.vbs OR *.bat OR *.chm OR *.xml OR *.txt OR *.jsp OR *.jspx OR *.asp OR *.aspx OR *.php OR *.war OR *.hta OR *.lnk OR *.scf OR *.sct OR *.vbe OR *.wsf OR *.wsh)')\n",
    "response = s.execute()\n",
    "if response.success():\n",
    "    df = pd.DataFrame((d.to_dict() for d in s.scan()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Show Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.head()"
   ]
  }
 ],
 "metadata": {},
 "nbformat": 4,
 "nbformat_minor": 4
}