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

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python SQL Exceptions\n",
    "Generic rule for SQL exceptions in Python according to PEP 249"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rule Content\n",
    "```\n",
    "- title: Python SQL Exceptions\n",
    "  id: 19aefed0-ffd4-47dc-a7fc-f8b1425e84f9\n",
    "  description: Generic rule for SQL exceptions in Python according to PEP 249\n",
    "  author: Thomas Patzke\n",
    "  references:\n",
    "  - https://www.python.org/dev/peps/pep-0249/#exceptions\n",
    "  logsource:\n",
    "    category: application\n",
    "    product: python\n",
    "    service: null\n",
    "  detection:\n",
    "    exceptions:\n",
    "    - DataError\n",
    "    - IntegrityError\n",
    "    - ProgrammingError\n",
    "    - OperationalError\n",
    "    condition: exceptions\n",
    "  falsepositives:\n",
    "  - Application bugs\n",
    "  - Penetration testing\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:(*DataError* OR *IntegrityError* OR *ProgrammingError* OR *OperationalError*)')\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
}