HELK/docker/helk-jupyter/notebooks/sigma/web_webshell_keyword.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Webshell Detection by Keyword\n",
    "Detects webshells that use GET requests by keyword searches in URL strings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rule Content\n",
    "```\n",
    "- title: Webshell Detection by Keyword\n",
    "  id: 7ff9db12-1b94-4a79-ba68-a2402c5d6729\n",
    "  description: Detects webshells that use GET requests by keyword searches in URL\n",
    "    strings\n",
    "  author: Florian Roth\n",
    "  logsource:\n",
    "    category: webserver\n",
    "    product: null\n",
    "    service: null\n",
    "  detection:\n",
    "    keywords:\n",
    "    - =whoami\n",
    "    - =net%20user\n",
    "    - =cmd%20/c%20\n",
    "    condition: keywords\n",
    "  fields:\n",
    "  - client_ip\n",
    "  - vhost\n",
    "  - url\n",
    "  - response\n",
    "  falsepositives:\n",
    "  - Web sites like wikis with articles on os commands and pages that include the os\n",
    "    commands in the URLs\n",
    "  - User searches in search boxes of the respective website\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='\\*.keyword:(*\\=whoami* OR *\\=net%20user* OR *\\=cmd%20\\/c%20*)')\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
}