{ "metadata": { "name": "", "signature": "sha256:68d702d5c3abbbc96762808f68f327f6d51d8681d28d26959cce998dfc012611" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "# PCAP to Pandas Dataframe\n", "This notebook demonstrates a particularily kewl feature of workbench. Quickly and efficiently going from raw data to a Pandas Dataframe. \n", "\n", "Here we're using the workbench server to look at a specific case captured by [ThreatGlass](http://www.threatglass.com/). The exploited website for this exercise is gold-xxx.net [ThreatGlass_Info](http://www.threatglass.com/malicious_urls/141deabbc8741175d9f51559cf4ef3dd?process_date=2014-05-29).\n", "\n", "**Tools in this Notebook:**\n", "\n", "- Workbench: Open Source Security Framework [Workbench GitHub](https://github.com/SuperCowPowers/workbench)\n", "- Bro Network Security Monitor (http://www.bro.org)\n", "- Pandas: Python Data Analysis Library (http://pandas.pydata.org)\n", "\n", "**More Info:** \n", "\n", "- See [PCAP_to_Graph](http://nbviewer.ipython.org/github/SuperCowPowers/workbench/blob/master/workbench/notebooks/PCAP_to_Graph.ipynb) for a short notebook on turning this PCAP into a Neo4j graph.\n", "
\n", "- See [Workbench Demo Notebook](http://nbviewer.ipython.org/github/SuperCowPowers/workbench/blob/master/workbench/notebooks/Workbench_Demo.ipynb) for a lot more info on using workbench.\n", "

\n", "\n", "## Lets start up the workbench server...\n", "Run the workbench server (from somewhere, for the demo we're just going to start a local one)\n", "
\n",
      "$ workbench_server\n",
      "
" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Lets start to interact with workbench, please note there is NO specific client to workbench,\n", "# Just use the ZeroRPC Python, Node.js, or CLI interfaces.\n", "import zerorpc\n", "c = zerorpc.Client(timeout=120)\n", "c.connect(\"tcp://127.0.0.1:4242\")" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 5, "text": [ "[None]" ] } ], "prompt_number": 5 }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "# Read in the Data\n", " The data is pulled from [ThreatGlass](http://www.threatglass.com/), the exploited website for this exercise is gold-xxx.net [ThreatGlass_Info](http://www.threatglass.com/malicious_urls/141deabbc8741175d9f51559cf4ef3dd?process_date=2014-05-29).\n", "" ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Load in the PCAP file\n", "with open('../data/pcap/gold_xxx.pcap','rb') as f:\n", " pcap_md5 = c.store_sample(f.read(), 'gold_xxx', 'pcap')" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 6 }, { "cell_type": "code", "collapsed": false, "input": [ "# We can also ask workbench for a python dictionary of all the info from this PCAP,\n", "# because sometimes visualization are useful and sometimes organized data is useful.\n", "output = c.work_request('view_pcap_details', pcap_md5)['view_pcap_details']\n", "output" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 10, "text": [ "{'bro_logs': {'conn_log': 'e6b210abca2299821a31e4448260f5da',\n", " 'dhcp_log': 'cf081f397ae93aaeada91cb68ac86168',\n", " 'dns_log': '3af86fbc1bd125c83160d1f5d0cafa39',\n", " 'files_log': '468dca88929d2ed54b26ff81fe1b1700',\n", " 'http_log': 'b76384cf1c5179bccf64f8320882af94',\n", " 'packet_filter_log': '87676f840e783c2dc537efe51acfc075',\n", " 'weird_log': 'a8d45ed8b0ddb0b9e115d05fe9f65dea'},\n", " 'extracted_files': [{'entropy': 6.845206689967475,\n", " 'file_size': 219136,\n", " 'file_type': 'PE32 executable (GUI) Intel 80386, for MS Windows',\n", " 'md5': '17d786f9a3ac2b54cf29122cd58bdabe',\n", " 'sha256': 'cc5bd99f15d2b2c3153ca132245b2780fac08e66c8ed0dc096919b81beb886b5',\n", " 'ssdeep': '3072:ddZuptT5MSMLp30xUiteu55Cva5xmSnaCOnQe+kAiE7jtMH4jIT9m26zD2FzXunl:dneTSjaxjeu50va5xm2jtcUQR2'},\n", " {'entropy': 6.845206689967475,\n", " 'file_size': 219136,\n", " 'file_type': 'PE32 executable (GUI) Intel 80386, for MS Windows',\n", " 'md5': '17d786f9a3ac2b54cf29122cd58bdabe',\n", " 'sha256': 'cc5bd99f15d2b2c3153ca132245b2780fac08e66c8ed0dc096919b81beb886b5',\n", " 'ssdeep': '3072:ddZuptT5MSMLp30xUiteu55Cva5xmSnaCOnQe+kAiE7jtMH4jIT9m26zD2FzXunl:dneTSjaxjeu50va5xm2jtcUQR2'},\n", " {'entropy': 6.672123050634468,\n", " 'file_size': 149,\n", " 'file_type': 'data',\n", " 'md5': '016d482b6cf4fda57240b539e1468794',\n", " 'sha256': 'b5b1c65f25374362658c6c8ffbdf15fa61f7c09890eb30bd9e835906b2fdd9c6',\n", " 'ssdeep': '3:WH9TISb/x9doI+YBU4eqezcW73YOJKVsv/dXN5bgZMlR/73bU4ZEMGOB9:6ISbvV+2bHYn/d95bg2zbDEI7'},\n", " {'entropy': 3.7725899061892,\n", " 'file_size': 1150,\n", " 'file_type': 'MS Windows icon resource - 1 icon',\n", " 'md5': '8f8e6f2edc6d89b9632d7fa73ee4f5ea',\n", " 'sha256': 'af0db6b81e131069926379a610d770973d24b2be92a99cb5c1a30b5fc4b13e5e',\n", " 'ssdeep': '12:jG28R+X1Zxr94pUfHudkLaJaJaJaJaaJaJaJgEhKqEYax5adqwtmUUlR55n:i28AxrVfHsZUUUXUUVhz1l8UUj'},\n", " {'entropy': 6.672123050634468,\n", " 'file_size': 149,\n", " 'file_type': 'data',\n", " 'md5': '016d482b6cf4fda57240b539e1468794',\n", " 'sha256': 'b5b1c65f25374362658c6c8ffbdf15fa61f7c09890eb30bd9e835906b2fdd9c6',\n", " 'ssdeep': '3:WH9TISb/x9doI+YBU4eqezcW73YOJKVsv/dXN5bgZMlR/73bU4ZEMGOB9:6ISbvV+2bHYn/d95bg2zbDEI7'},\n", " {'entropy': 6.845206689967475,\n", " 'file_size': 219136,\n", " 'file_type': 'PE32 executable (GUI) Intel 80386, for MS Windows',\n", " 'md5': '17d786f9a3ac2b54cf29122cd58bdabe',\n", " 'sha256': 'cc5bd99f15d2b2c3153ca132245b2780fac08e66c8ed0dc096919b81beb886b5',\n", " 'ssdeep': '3072:ddZuptT5MSMLp30xUiteu55Cva5xmSnaCOnQe+kAiE7jtMH4jIT9m26zD2FzXunl:dneTSjaxjeu50va5xm2jtcUQR2'},\n", " {'entropy': 6.845206689967475,\n", " 'file_size': 219136,\n", " 'file_type': 'PE32 executable (GUI) Intel 80386, for MS Windows',\n", " 'md5': '17d786f9a3ac2b54cf29122cd58bdabe',\n", " 'sha256': 'cc5bd99f15d2b2c3153ca132245b2780fac08e66c8ed0dc096919b81beb886b5',\n", " 'ssdeep': '3072:ddZuptT5MSMLp30xUiteu55Cva5xmSnaCOnQe+kAiE7jtMH4jIT9m26zD2FzXunl:dneTSjaxjeu50va5xm2jtcUQR2'},\n", " {'entropy': 6.845206689967475,\n", " 'file_size': 219136,\n", " 'file_type': 'PE32 executable (GUI) Intel 80386, for MS Windows',\n", " 'md5': '17d786f9a3ac2b54cf29122cd58bdabe',\n", " 'sha256': 'cc5bd99f15d2b2c3153ca132245b2780fac08e66c8ed0dc096919b81beb886b5',\n", " 'ssdeep': '3072:ddZuptT5MSMLp30xUiteu55Cva5xmSnaCOnQe+kAiE7jtMH4jIT9m26zD2FzXunl:dneTSjaxjeu50va5xm2jtcUQR2'},\n", " {'entropy': 7.306977991950132,\n", " 'file_size': 12761,\n", " 'file_type': 'PDF document, version 1.6',\n", " 'md5': 'b85cb7cee9e145ac4dfb7e8f1870e360',\n", " 'sha256': 'af1f3785ea4a2be08cb13c6b32a3cf71bbe24f50530b591ddb3be9d363d2e6a3',\n", " 'ssdeep': '384:SW3+jGeEBnZgazaw0eUqfgij6aUi0f+xOfESUxDnDKT:fW+h0eho5YxOIFKT'},\n", " {'entropy': 7.855433934299751,\n", " 'file_size': 10629,\n", " 'file_type': 'Java Jar file data (zip)',\n", " 'md5': 'd4c56b4d0ba9fbbd1028b83401eec133',\n", " 'sha256': '155527017e6dbeec01c1b0a99f9db9dcf7a0b4ea902fb6586b463b2836e481bc',\n", " 'ssdeep': '192:rh3cJzBpxUybGZXwnYzG2/HCtLVl+Wg/+czIPKGgGmnzmIlbA:t3KLFbGdqU6tCWdc8PKUwmf'},\n", " {'entropy': 6.845206689967475,\n", " 'file_size': 219136,\n", " 'file_type': 'PE32 executable (GUI) Intel 80386, for MS Windows',\n", " 'md5': '17d786f9a3ac2b54cf29122cd58bdabe',\n", " 'sha256': 'cc5bd99f15d2b2c3153ca132245b2780fac08e66c8ed0dc096919b81beb886b5',\n", " 'ssdeep': '3072:ddZuptT5MSMLp30xUiteu55Cva5xmSnaCOnQe+kAiE7jtMH4jIT9m26zD2FzXunl:dneTSjaxjeu50va5xm2jtcUQR2'},\n", " {'entropy': 4.869185904780487,\n", " 'file_size': 7692,\n", " 'file_type': 'assembler source, ASCII text',\n", " 'md5': '739993fe99fcb74d283f7faa1617984b',\n", " 'sha256': '2882a10573b80d8c6cfe2137160f993523082dd20948cbbfcb2458128d0a3043',\n", " 'ssdeep': '192:/2TFrmh1FVFlrfVWIXXoJAaF7Fe7cFJeS1NM8M8D2f:uTFryFVFlr9WcaF7FeoF0mHm'},\n", " {'entropy': 6.570728034441538,\n", " 'file_size': 156160,\n", " 'file_type': 'PE32 executable (GUI) Intel 80386, for MS Windows',\n", " 'md5': 'c37f0a7b0249c91a43e749ad3660fb55',\n", " 'sha256': 'e0124e97a99c40b6f48760ab90d2ed009f9b4c661f3e98c86c848b876588c47d',\n", " 'ssdeep': '3072:Dd/1aVzIF8P3h3cJUitGoDp+XSB5mKAKYOnQe+FSDHslun81L:DraVzTP3GJjGoDYXSB5mkHet'},\n", " {'entropy': 7.855433934299751,\n", " 'file_size': 10629,\n", " 'file_type': 'Java Jar file data (zip)',\n", " 'md5': 'd4c56b4d0ba9fbbd1028b83401eec133',\n", " 'sha256': '155527017e6dbeec01c1b0a99f9db9dcf7a0b4ea902fb6586b463b2836e481bc',\n", " 'ssdeep': '192:rh3cJzBpxUybGZXwnYzG2/HCtLVl+Wg/+czIPKGgGmnzmIlbA:t3KLFbGdqU6tCWdc8PKUwmf'},\n", " {'entropy': 6.570728034441538,\n", " 'file_size': 156160,\n", " 'file_type': 'PE32 executable (GUI) Intel 80386, for MS Windows',\n", " 'md5': 'c37f0a7b0249c91a43e749ad3660fb55',\n", " 'sha256': 'e0124e97a99c40b6f48760ab90d2ed009f9b4c661f3e98c86c848b876588c47d',\n", " 'ssdeep': '3072:Dd/1aVzIF8P3h3cJUitGoDp+XSB5mKAKYOnQe+FSDHslun81L:DraVzTP3GJjGoDYXSB5mkHet'},\n", " {'entropy': 7.855433934299751,\n", " 'file_size': 10629,\n", " 'file_type': 'Java Jar file data (zip)',\n", " 'md5': 'd4c56b4d0ba9fbbd1028b83401eec133',\n", " 'sha256': '155527017e6dbeec01c1b0a99f9db9dcf7a0b4ea902fb6586b463b2836e481bc',\n", " 'ssdeep': '192:rh3cJzBpxUybGZXwnYzG2/HCtLVl+Wg/+czIPKGgGmnzmIlbA:t3KLFbGdqU6tCWdc8PKUwmf'}],\n", " 'md5': 'c8e58ff22b9a8e48838373fbb1692bdd'}" ] } ], "prompt_number": 10 }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "## If the next line of code doesn't blow your mind, you aren't paying attention!\n", "#### Thanks to ZeroRPC all of the bro logs are streamed from server to client with NETWORK STREAMING GENERATORS, those highly efficient generators are zero-copy and stream data directly into Pandas Dataframes.\n", "\n", "#### For more on client/server generators and client-contructed/server-executed generator pipelines see our super spiffy [Generator Pipelines](http://nbviewer.ipython.org/url/raw.github.com/SuperCowPowers/workbench/master/workbench/notebooks/Generator_Pipelines.ipynb) notebook." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Critical Code: Transition from Bro logs to Pandas Dataframes\n", "# This one line of code populates dataframes from the Bro logs, \n", "# streaming client/server generators, zero-copy, efficient, awesome...\n", "import pandas as pd\n", "dataframes = {name:pd.DataFrame(c.stream_sample(bro_log, None)) for name, bro_log in output['bro_logs'].iteritems()}" ], "language": "python", "metadata": {}, "outputs": [], "prompt_number": 11 }, { "cell_type": "markdown", "metadata": {}, "source": [ "
\n", "# Lets look at the Data\n", "We're going to use some nice functionality in the Pandas dataframe to look at our network data, specifically we're going to group by host, host-ip, mime_type and uri. The last column represents the aggregated sum of response_body_len.\n", "

\n", "This type of operation is really just scratching the surface when it comes to dataframes, so quickly and efficiently populating a dataframe is super awesome." ] }, { "cell_type": "code", "collapsed": false, "input": [ "# Look at DNS logs\n", "dataframes['dns_log'][['query','answers','qtype_name']].head(10)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
queryanswersqtype_name
0 gold-xxx.net 178.208.85.60 A
1 counter.yadro.ru 88.212.196.105,88.212.196.122,88.212.196.123,8... A
2 picsee.net 62.75.207.72 A
3 counter.rambler.ru 81.19.88.95,81.19.88.96,81.19.88.102,81.19.88.... A
4 freeroomhostelz.com 91.194.254.195 A
5 57d9bf9co3qbc.paroonic.ru 80.72.37.112 A
6 323210841-1.paroonic.ru 80.72.37.112 A
7 domainsfullkolls.biz 94.242.216.61 A
8 update.microsoft.com update.microsoft.com.nsatc.net,157.56.96.60,15... A
9 update.microsoft.com update.microsoft.com.nsatc.net,65.55.138.114,1... A
\n", "

10 rows \u00d7 3 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 20, "text": [ " query \\\n", "0 gold-xxx.net \n", "1 counter.yadro.ru \n", "2 picsee.net \n", "3 counter.rambler.ru \n", "4 freeroomhostelz.com \n", "5 57d9bf9co3qbc.paroonic.ru \n", "6 323210841-1.paroonic.ru \n", "7 domainsfullkolls.biz \n", "8 update.microsoft.com \n", "9 update.microsoft.com \n", "\n", " answers qtype_name \n", "0 178.208.85.60 A \n", "1 88.212.196.105,88.212.196.122,88.212.196.123,8... A \n", "2 62.75.207.72 A \n", "3 81.19.88.95,81.19.88.96,81.19.88.102,81.19.88.... A \n", "4 91.194.254.195 A \n", "5 80.72.37.112 A \n", "6 80.72.37.112 A \n", "7 94.242.216.61 A \n", "8 update.microsoft.com.nsatc.net,157.56.96.60,15... A \n", "9 update.microsoft.com.nsatc.net,65.55.138.114,1... A \n", "\n", "[10 rows x 3 columns]" ] } ], "prompt_number": 20 }, { "cell_type": "code", "collapsed": false, "input": [ "# Look at Conn logs\n", "dataframes['conn_log'].head(10)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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conn_statedurationhistoryid.orig_hid.orig_pid.resp_hid.resp_plocal_origmissed_bytesorig_bytesorig_ip_bytesorig_pktsprotoresp_bytesresp_ip_bytesresp_pktsservicetstunnel_parentsuid
0 RSTO 0.631127 ShADadR 192.168.39.10 1036 178.208.85.60 80 - 0 587 955 9 tcp 6459 6743 7 http 1.401401e+09 (empty) CBdyLA2FydtnrvzeBi
1 RSTO 0.150052 ShR 192.168.39.10 1037 178.208.85.60 80 - 0 0 88 2 tcp 0 44 1 - 1.401401e+09 (empty) C0gD932Pau36gzSy93
2 RSTO 0.151529 ShR 192.168.39.10 1040 178.208.85.60 80 - 0 0 88 2 tcp 0 44 1 - 1.401401e+09 (empty) CXTGqY2XNUSXRynhFg
3 RSTO 0.152817 ShR 192.168.39.10 1039 178.208.85.60 80 - 0 0 88 2 tcp 0 44 1 - 1.401401e+09 (empty) CNLjfJ1CSChTSRPRO1
4 RSTO 0.154018 ShR 192.168.39.10 1038 178.208.85.60 80 - 0 0 88 2 tcp 0 44 1 - 1.401401e+09 (empty) CWUpVH2eZ0g3HgXe1k
5 RSTO 0.15395 ShR 192.168.39.10 1041 178.208.85.60 80 - 0 0 88 2 tcp 0 44 1 - 1.401401e+09 (empty) C7WF992bGceJEID9k5
6 SF 0.802815 ShADdfFa 192.168.39.10 1051 88.212.196.105 80 - 0 653 901 6 tcp 1621 1829 5 http 1.401401e+09 (empty) C05Lh44T4Od4nxKuPc
7 SF 0.009575 Dd 192.168.39.10 1048 4.2.2.3 53 - 0 28 56 1 udp 44 72 1 dns 1.401401e+09 (empty) CoK5EL2wWO4GXS26D7
8 RSTO 6.797592 ShADadfR 192.168.39.10 1055 91.194.254.195 80 - 0 326 574 6 tcp 801 969 4 http 1.401401e+09 (empty) CiDYwq4jpcz4IGmX0g
9 RSTO 8.367047 ShADdfR 192.168.39.10 1054 81.19.88.95 80 - 0 799 1287 12 tcp 7618 7946 8 http 1.401401e+09 (empty) CDR6w61LKf7XpsHC36
\n", "

10 rows \u00d7 20 columns

\n", "
" ], "metadata": {}, "output_type": "pyout", "prompt_number": 21, "text": [ " conn_state duration history id.orig_h id.orig_p id.resp_h \\\n", "0 RSTO 0.631127 ShADadR 192.168.39.10 1036 178.208.85.60 \n", "1 RSTO 0.150052 ShR 192.168.39.10 1037 178.208.85.60 \n", "2 RSTO 0.151529 ShR 192.168.39.10 1040 178.208.85.60 \n", "3 RSTO 0.152817 ShR 192.168.39.10 1039 178.208.85.60 \n", "4 RSTO 0.154018 ShR 192.168.39.10 1038 178.208.85.60 \n", "5 RSTO 0.15395 ShR 192.168.39.10 1041 178.208.85.60 \n", "6 SF 0.802815 ShADdfFa 192.168.39.10 1051 88.212.196.105 \n", "7 SF 0.009575 Dd 192.168.39.10 1048 4.2.2.3 \n", "8 RSTO 6.797592 ShADadfR 192.168.39.10 1055 91.194.254.195 \n", "9 RSTO 8.367047 ShADdfR 192.168.39.10 1054 81.19.88.95 \n", "\n", " id.resp_p local_orig missed_bytes orig_bytes orig_ip_bytes orig_pkts \\\n", "0 80 - 0 587 955 9 \n", "1 80 - 0 0 88 2 \n", "2 80 - 0 0 88 2 \n", "3 80 - 0 0 88 2 \n", "4 80 - 0 0 88 2 \n", "5 80 - 0 0 88 2 \n", "6 80 - 0 653 901 6 \n", "7 53 - 0 28 56 1 \n", "8 80 - 0 326 574 6 \n", "9 80 - 0 799 1287 12 \n", "\n", " proto resp_bytes resp_ip_bytes resp_pkts service ts \\\n", "0 tcp 6459 6743 7 http 1.401401e+09 \n", "1 tcp 0 44 1 - 1.401401e+09 \n", "2 tcp 0 44 1 - 1.401401e+09 \n", "3 tcp 0 44 1 - 1.401401e+09 \n", "4 tcp 0 44 1 - 1.401401e+09 \n", "5 tcp 0 44 1 - 1.401401e+09 \n", "6 tcp 1621 1829 5 http 1.401401e+09 \n", "7 udp 44 72 1 dns 1.401401e+09 \n", "8 tcp 801 969 4 http 1.401401e+09 \n", "9 tcp 7618 7946 8 http 1.401401e+09 \n", "\n", " tunnel_parents uid \n", "0 (empty) CBdyLA2FydtnrvzeBi \n", "1 (empty) C0gD932Pau36gzSy93 \n", "2 (empty) CXTGqY2XNUSXRynhFg \n", "3 (empty) CNLjfJ1CSChTSRPRO1 \n", "4 (empty) CWUpVH2eZ0g3HgXe1k \n", "5 (empty) C7WF992bGceJEID9k5 \n", "6 (empty) C05Lh44T4Od4nxKuPc \n", "7 (empty) CoK5EL2wWO4GXS26D7 \n", "8 (empty) CiDYwq4jpcz4IGmX0g \n", "9 (empty) CDR6w61LKf7XpsHC36 \n", "\n", "[10 rows x 20 columns]" ] } ], "prompt_number": 21 }, { "cell_type": "code", "collapsed": false, "input": [ "# Simple Stats with Pandas Dataframe\n", "dataframes['conn_log'][['missed_bytes','orig_ip_bytes','resp_ip_bytes','resp_pkts']].describe()" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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missed_bytesorig_ip_bytesresp_ip_bytesresp_pkts
count 65 65.000000 65.000000 65.000000
mean 0 1221.769231 39791.953846 17.107692
std 0 1685.608669 74050.375527 27.989464
min 0 48.000000 0.000000 0.000000
25% 0 63.000000 79.000000 1.000000
50% 0 464.000000 365.000000 4.000000
75% 0 1600.000000 51482.000000 18.000000
max 0 5312.000000 223664.000000 106.000000
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8 rows \u00d7 4 columns

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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 24, "text": [ " missed_bytes orig_ip_bytes resp_ip_bytes resp_pkts\n", "count 65 65.000000 65.000000 65.000000\n", "mean 0 1221.769231 39791.953846 17.107692\n", "std 0 1685.608669 74050.375527 27.989464\n", "min 0 48.000000 0.000000 0.000000\n", "25% 0 63.000000 79.000000 1.000000\n", "50% 0 464.000000 365.000000 4.000000\n", "75% 0 1600.000000 51482.000000 18.000000\n", "max 0 5312.000000 223664.000000 106.000000\n", "\n", "[8 rows x 4 columns]" ] } ], "prompt_number": 24 }, { "cell_type": "code", "collapsed": false, "input": [ "# Simple Filtering with Pandas Dataframe\n", "not_80_df = dataframes['conn_log'][dataframes['conn_log']['id.resp_p'] != 80]\n", "not_80_df.head(10)" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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conn_statedurationhistoryid.orig_hid.orig_pid.resp_hid.resp_plocal_origmissed_bytesorig_bytesorig_ip_bytesorig_pktsprotoresp_bytesresp_ip_bytesresp_pktsservicetstunnel_parentsuid
7 SF 0.009575 Dd 192.168.39.10 1048 4.2.2.3 53 - 0 28 56 1 udp 44 72 1 dns 1.401401e+09 (empty) CoK5EL2wWO4GXS26D7...
11 SF 11.55683 Dd 192.168.39.10 1035 4.2.2.3 53 - 0 221 389 6 udp 669 837 6 dns 1.401401e+09 (empty) CBWgV42cYiaGqu9Z25...
12 S0 0.000911 D 0.0.0.0 68 255.255.255.255 67 - 0 626 682 2 udp 0 0 0 dhcp 1.401401e+09 (empty) CKYJGa15i6s1Rpq0Y...
13 SF 2.110374 dD 192.168.39.10 68 192.168.39.1 67 - 0 314 342 1 udp 900 984 3 dhcp 1.401401e+09 (empty) C6zKAr3iKNDLKufq4h...
15 SF 0.027165 Dd 192.168.39.10 1035 4.2.2.3 53 - 0 38 66 1 udp 54 82 1 dns 1.401401e+09 (empty) C50uAqkg2gpAF0eH5...
26 S0 6.024315 D 192.168.39.10 1058 239.255.255.250 1900 - 0 399 483 3 udp 0 0 0 - 1.401401e+09 (empty) CAirC04eZatVhqLFvc...
41 SF 0.008703 Dd 192.168.39.10 1035 4.2.2.3 53 - 0 38 66 1 udp 114 142 1 dns 1.401401e+09 (empty) Cjnp9B3tRdimStImlc...
42 SF 0.009521 Dd 192.168.39.10 1048 4.2.2.3 53 - 0 38 66 1 udp 114 142 1 dns 1.401401e+09 (empty) Cl5qe21lfeB8wXEZg4...
43 SF 0.021553 Dd 192.168.39.10 1066 8.8.4.4 53 - 0 35 63 1 udp 51 79 1 dns 1.401401e+09 (empty) Cn9DTl3yp91dxD8hFl...
44 SF 0.001862 Dd 192.168.39.10 1068 8.8.4.4 53 - 0 35 63 1 udp 51 79 1 dns 1.401401e+09 (empty) Cy7sm63NXzJ1XuxTpj...
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10 rows \u00d7 21 columns

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" ], "metadata": {}, "output_type": "pyout", "prompt_number": 64, "text": [ " conn_state duration history id.orig_h id.orig_p id.resp_h \\\n", "7 SF 0.009575 Dd 192.168.39.10 1048 4.2.2.3 \n", "11 SF 11.55683 Dd 192.168.39.10 1035 4.2.2.3 \n", "12 S0 0.000911 D 0.0.0.0 68 255.255.255.255 \n", "13 SF 2.110374 dD 192.168.39.10 68 192.168.39.1 \n", "15 SF 0.027165 Dd 192.168.39.10 1035 4.2.2.3 \n", "26 S0 6.024315 D 192.168.39.10 1058 239.255.255.250 \n", "41 SF 0.008703 Dd 192.168.39.10 1035 4.2.2.3 \n", "42 SF 0.009521 Dd 192.168.39.10 1048 4.2.2.3 \n", "43 SF 0.021553 Dd 192.168.39.10 1066 8.8.4.4 \n", "44 SF 0.001862 Dd 192.168.39.10 1068 8.8.4.4 \n", "\n", " id.resp_p local_orig missed_bytes orig_bytes orig_ip_bytes orig_pkts \\\n", "7 53 - 0 28 56 1 \n", "11 53 - 0 221 389 6 \n", "12 67 - 0 626 682 2 \n", "13 67 - 0 314 342 1 \n", "15 53 - 0 38 66 1 \n", "26 1900 - 0 399 483 3 \n", "41 53 - 0 38 66 1 \n", "42 53 - 0 38 66 1 \n", "43 53 - 0 35 63 1 \n", "44 53 - 0 35 63 1 \n", "\n", " proto resp_bytes resp_ip_bytes resp_pkts service ts \\\n", "7 udp 44 72 1 dns 1.401401e+09 \n", "11 udp 669 837 6 dns 1.401401e+09 \n", "12 udp 0 0 0 dhcp 1.401401e+09 \n", "13 udp 900 984 3 dhcp 1.401401e+09 \n", "15 udp 54 82 1 dns 1.401401e+09 \n", "26 udp 0 0 0 - 1.401401e+09 \n", "41 udp 114 142 1 dns 1.401401e+09 \n", "42 udp 114 142 1 dns 1.401401e+09 \n", "43 udp 51 79 1 dns 1.401401e+09 \n", "44 udp 51 79 1 dns 1.401401e+09 \n", "\n", " tunnel_parents uid \n", "7 (empty) CoK5EL2wWO4GXS26D7 ... \n", "11 (empty) CBWgV42cYiaGqu9Z25 ... \n", "12 (empty) CKYJGa15i6s1Rpq0Y ... \n", "13 (empty) C6zKAr3iKNDLKufq4h ... \n", "15 (empty) C50uAqkg2gpAF0eH5 ... \n", "26 (empty) CAirC04eZatVhqLFvc ... \n", "41 (empty) Cjnp9B3tRdimStImlc ... \n", "42 (empty) Cl5qe21lfeB8wXEZg4 ... \n", "43 (empty) Cn9DTl3yp91dxD8hFl ... \n", "44 (empty) Cy7sm63NXzJ1XuxTpj ... \n", "\n", "[10 rows x 21 columns]" ] } ], "prompt_number": 64 }, { "cell_type": "code", "collapsed": false, "input": [ "# Now we group by host and show the different response mime types for each host\n", "group_host = dataframes['http_log'].groupby(['host','id.resp_h','resp_mime_types','uri'])[['response_body_len']].sum()\n", "group_host" ], "language": "python", "metadata": {}, "outputs": [ { "html": [ "
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[], "prompt_number": 75 }, { "cell_type": "code", "collapsed": false, "input": [ "# Plot hosts and mime-types\n", "plot_df = dataframes['http_log'].groupby(['host','resp_mime_types'])[['response_body_len']].sum().unstack()\n", "plot_df['response_body_len'].plot(kind='bar', stacked=True)\n", "plt.xlabel('Domain')\n", "plt.ylabel('Response Bytes')\n", "plt.xticks(rotation=45, ha='right')" ], "language": "python", "metadata": {}, "outputs": [ { "metadata": {}, "output_type": "pyout", "prompt_number": 82, "text": [ "(array([ 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5,\n", " 9.5, 10.5]), )" ] }, { "metadata": {}, "output_type": "display_data", "png": 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qVezZs4fDhw8zaNAgfvvtN4tzZ4+DiIiIiEhZpOm4pYiDkwPp49OL9Xr5YWtr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\nrLm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"text": [ "" ] } ], "prompt_number": 82 }, { "cell_type": "markdown", "metadata": {}, "source": [ "#Wrap Up\n", "Well for this short notebook we used 6-7 lines of python to go from PCAP file to a Pandas Dataframe and then we did a bunch of kewl stuff using the Dataframe. We hope this exercise showed some neato functionality using [Workbench](https://github.com/SuperCowPowers/workbench), we encourage you to check out the GitHub repository and our other notebooks:\n", "- [PCAP_to_Graph](http://nbviewer.ipython.org/github/SuperCowPowers/workbench/blob/master/workbench/notebooks/PCAP_to_Graph.ipynb) for a short notebook on turning this PCAP into a Neo4j graph.\n", "- [Workbench Demo](http://nbviewer.ipython.org/url/raw.github.com/SuperCowPowers/workbench/master/workbench/notebooks/Workbench_Demo.ipynb) general introduction to Workbench.\n", "- [PCAP_DriveBy](http://nbviewer.ipython.org/url/raw.github.com/SuperCowPowers/workbench/master/workbench/notebooks/PCAP_DriveBy.ipynb) a detail look at a Web DriveBy from the [ThreatGlass](http://www.threatglass.com) repository.\n", "- [PE File Sim Graph](http://nbviewer.ipython.org/url/raw.github.com/SuperCowPowers/workbench/master/workbench/notebooks/PE_SimGraph.ipynb) using Neo4j to generate a similarity graph using PE File features.\n", "- [Generator Pipelines](http://nbviewer.ipython.org/url/raw.github.com/SuperCowPowers/workbench/master/workbench/notebooks/Generator_Pipelines.ipynb) using the client/server streaming generators to demonstrate 'chaining' generators." ] } ], "metadata": {} } ] }