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

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ursnif Malware Download URL Pattern\n",
    "Detects download of Ursnif malware done by dropper documents."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rule Content\n",
    "```\n",
    "- title: Ursnif Malware Download URL Pattern\n",
    "  id: a36ce77e-30db-4ea0-8795-644d7af5dfb4\n",
    "  status: stable\n",
    "  description: Detects download of Ursnif malware done by dropper documents.\n",
    "  author: Thomas Patzke\n",
    "  logsource:\n",
    "    category: proxy\n",
    "    product: null\n",
    "    service: null\n",
    "  detection:\n",
    "    selection:\n",
    "      c-uri: '*/*.php?l=*.cab'\n",
    "      sc-status: 200\n",
    "    condition: selection\n",
    "  fields:\n",
    "  - c-ip\n",
    "  - c-uri\n",
    "  - sc-bytes\n",
    "  - c-ua\n",
    "  falsepositives:\n",
    "  - Unknown\n",
    "  level: critical\n",
    "- title: Ursnif Malware C2 URL Pattern\n",
    "  id: 932ac737-33ca-4afd-9869-0d48b391fcc9\n",
    "  status: stable\n",
    "  description: Detects Ursnif C2 traffic.\n",
    "  references:\n",
    "  - https://www.fortinet.com/blog/threat-research/ursnif-variant-spreading-word-document.html\n",
    "  author: Thomas Patzke\n",
    "  logsource:\n",
    "    category: proxy\n",
    "  detection:\n",
    "    b64encoding:\n",
    "      c-uri:\n",
    "      - '*_2f*'\n",
    "      - '*_2b*'\n",
    "    urlpatterns:\n",
    "      c-uri|all:\n",
    "      - '*.avi'\n",
    "      - '*/images/*'\n",
    "    condition: b64encoding and urlpatterns\n",
    "  fields:\n",
    "  - c-ip\n",
    "  - c-uri\n",
    "  - sc-bytes\n",
    "  - c-ua\n",
    "  falsepositives:\n",
    "  - Unknown\n",
    "  level: critical\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='(c-uri.keyword:*\\/*.php?l\\=*.cab AND sc-status:\"200\")')\n",
    "response = s.execute()\n",
    "if response.success():\n",
    "    df = pd.DataFrame((d.to_dict() for d in s.scan()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = searchContext.query('query_string', query='(c-uri.keyword:(*_2f* OR *_2b*) AND c-uri.keyword:*.avi AND c-uri.keyword:*\\/images\\/*)')\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
}