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

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Suspicious Log Entries\n",
    "Detects suspicious log entries in Linux log files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rule Content\n",
    "```\n",
    "- title: Suspicious Log Entries\n",
    "  id: f64b6e9a-5d9d-48a5-8289-e1dd2b3876e1\n",
    "  description: Detects suspicious log entries in Linux log files\n",
    "  author: Florian Roth\n",
    "  logsource:\n",
    "    product: linux\n",
    "    service: null\n",
    "    category: null\n",
    "  detection:\n",
    "    keywords:\n",
    "    - entered promiscuous mode\n",
    "    - Deactivating service\n",
    "    - Oversized packet received from\n",
    "    - imuxsock begins to drop messages\n",
    "    condition: keywords\n",
    "  falsepositives:\n",
    "  - Unknown\n",
    "  level: medium\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:(*entered\\ promiscuous\\ mode* OR *Deactivating\\ service* OR *Oversized\\ packet\\ received\\ from* OR *imuxsock\\ begins\\ to\\ drop\\ messages*)')\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
}