mirror of https://github.com/infosecn1nja/HELK.git
133 lines
3.0 KiB
Plaintext
133 lines
3.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Executable in ADS\n",
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"Detects the creation of an ADS data stream that contains an executable (non-empty imphash)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Rule Content\n",
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"```\n",
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"- title: Executable in ADS\n",
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" id: b69888d4-380c-45ce-9cf9-d9ce46e67821\n",
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" status: experimental\n",
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" description: Detects the creation of an ADS data stream that contains an executable\n",
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" (non-empty imphash)\n",
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" references:\n",
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" - https://twitter.com/0xrawsec/status/1002478725605273600?s=21\n",
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" tags:\n",
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" - attack.defense_evasion\n",
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" - attack.t1027\n",
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" - attack.s0139\n",
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" author: Florian Roth, @0xrawsec\n",
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" date: 2018/06/03\n",
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" logsource:\n",
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" product: windows\n",
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" service: sysmon\n",
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" definition: 'Requirements: Sysmon config with Imphash logging activated'\n",
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" category: null\n",
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" detection:\n",
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" selection:\n",
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" EventID: 15\n",
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" filter:\n",
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" Imphash: '00000000000000000000000000000000'\n",
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" condition: selection and not filter\n",
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" fields:\n",
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" - TargetFilename\n",
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" - Image\n",
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" falsepositives:\n",
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" - unknown\n",
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" level: critical\n",
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"\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Querying Elasticsearch"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Import Libraries"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from elasticsearch import Elasticsearch\n",
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"from elasticsearch_dsl import Search\n",
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"import pandas as pd"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Initialize Elasticsearch client"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"es = Elasticsearch(['http://helk-elasticsearch:9200'])\n",
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"searchContext = Search(using=es, index='logs-endpoint-winevent-sysmon-*', doc_type='doc')"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Run Elasticsearch Query"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"s = searchContext.query('query_string', query='(event_id:\"15\" AND (NOT (hash_imphash:\"00000000000000000000000000000000\")))')\n",
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"response = s.execute()\n",
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"if response.success():\n",
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" df = pd.DataFrame((d.to_dict() for d in s.scan()))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### Show Results"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"df.head()"
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]
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}
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],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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