Scapy/Wifi Database - Revision history

Admin: /* Wifi Capture Script Breakdown */

2017-04-06T05:11:40Z

Wifi Capture Script Breakdown

← Older revision		Revision as of 05:11, 6 April 2017
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	and notes here: [[Pymongo]]		and notes here: [[Pymongo]]

			<!--

	=Wifi Capture Script Breakdown=		=Wifi Capture Script Breakdown=
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	sniff(iface=mon_iface, store=0, prn=cb)		sniff(iface=mon_iface, store=0, prn=cb)
	</pre>		</pre>

			-->

	=Flags=		=Flags=

Admin: /* Database Creation Script Breakdown */

2017-04-06T05:11:27Z

Database Creation Script Breakdown

← Older revision		Revision as of 05:11, 6 April 2017
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	-->		-->

	=Database Creation ~~Script Breakdown~~=		=Database Creation Process=

	==Overview==		==Overview==

Admin: /* Full Script */

2017-04-06T05:10:36Z

Full Script

← Older revision		Revision as of 05:10, 6 April 2017
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	* Scapy script to process wifi packets, parse information from them, send data to database		* Scapy script to process wifi packets, parse information from them, send data to database
	* Database script to create/connect to database, listen for data		* Database script to create/connect to database, listen for data

			<!--

	=Full Script=		=Full Script=
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	</pre>		</pre>
	}}		}}
			-->

	=Database Creation Script Breakdown=		=Database Creation Script Breakdown=

Admin: /* Importing Libraries */

2017-04-06T05:09:56Z

Importing Libraries

← Older revision		Revision as of 05:09, 6 April 2017
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	<pre>		<pre>
	import logging		import logging
	logging.getLogger("scapy.runtime").setLevel(logging.ERROR) ~~# Shut up Scapy~~		logging.getLogger("scapy.runtime").setLevel(logging.ERROR)
	from scapy.all import *		from scapy.all import *
	conf.verb = 0 ~~# Scapy I thought I told you to shut up~~		conf.verb = 0
	import os		import os
	import sys		import sys

Admin: /* Preparing MongoDB */

2017-03-30T07:36:23Z

Preparing MongoDB

← Older revision		Revision as of 07:36, 30 March 2017
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	<pre>		<pre>
	apt-get install mongodb		# don't do apt-get install mongo-db
			# see https://docs.mongodb.com/manual/tutorial/install-mongodb-on-ubuntu/
	pip install pymodm		pip install pymodm
	</pre>		</pre>

Admin: /* Pymongo */

2016-08-31T23:57:24Z

Pymongo

@@ Line 506: / Line 506: @@
 More info on pymongo here: [http://api.mongodb.com/python/current/tutorial.html]
-In this section we show how to set up a connection to the MongoDB.
+and notes here: [[Pymongo]]
 =Wifi Capture Script Breakdown=

Admin: /* Database Schema */

2016-08-31T23:18:35Z

Database Schema

@@ Line 501: / Line 501: @@
+}
 </pre>
 =Wifi Capture Script Breakdown=

Admin: /* Database Schema */

2016-08-31T22:46:57Z

Database Schema

← Older revision		Revision as of 22:46, 31 August 2016
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	More on DB cross-references: [https://docs.mongodb.com/manual/reference/database-references/]		More on DB cross-references: [https://docs.mongodb.com/manual/reference/database-references/]

			===Data===

			The AP data we're putting into the database depends on what type of packet is received. The type of packets we might receive from an AP that we would keep are:
			* Beacon frames

			The data available about an AP in a beacon frame is:
			* BSSID
			* Channel
			* SSID
			* Signal strength
			* Encryption type

			Thus, typical behavior for the Wifi Database program is as follows: Begin listening for packets. When a beacon packet is received, extract BSSID, channel, SSID, signal strength, and encryption information. Create a dictionary following the schema below; this will become the MongoDB document. Insert the MongoDB document into the collection.

			<pre>
			{
			'bssid' : 'aa:bb:cc:dd:ee:ff:00:11',
			'channel' : 5,
			'ssid' : 'Nacho Wifi',
			'strength' : -20,
			'encryption' : 'WPA'
			}
			</pre>

			The data available for clients is:
			* Client MAC
			* Gateway/destination MAC
			* Signal strength
			* Channel
			* Associated SSIDs

			<pre>
			{
			'bssid' : 'aa:bb:cc:dd:ee:ff:00:11',
			'channel' : 5,
			'ssid' : 'Nacho Wifi',
			'strength' : -20,
			'encryption' : 'WPA'
			}
			</pre>

	=Wifi Capture Script Breakdown=		=Wifi Capture Script Breakdown=

Admin: /* NoSQL Verbiage */

2016-08-31T22:27:15Z

NoSQL Verbiage

← Older revision		Revision as of 22:27, 31 August 2016
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	Before we talk about putting data into MongoDB, let's clarify how MongoDB refers to different concepts in code.		Before we talk about putting data into MongoDB, let's clarify how MongoDB refers to different concepts in code.

	Concepts:		Nosql/Mongodb Concepts:
	* Document - a document is a chunk of related data that represents a single observation or a single record. Equivalent to SQL record.		* Document - a document is a chunk of related data that represents a single observation or a single record. Equivalent to SQL record.
	* Collection - a collection is an assembled group of documents that are all related somehow. Equivalent to SQL table.		* Collection - a collection is an assembled group of documents that are all related somehow. Equivalent to SQL table.
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	NOTE: The key idea behind NoSQL is that Collections do not impose any requirements on Documents. This makes NoSQL much more flexible than SQL.		NOTE: The key idea behind NoSQL is that Collections do not impose any requirements on Documents. This makes NoSQL much more flexible than SQL.

	Implementation:		Mongodb Implementation:
	* Data Model - this refers to the actual nuts-and-bolts schema of how data is structured in the code.		* Data Model - this refers to the actual nuts-and-bolts schema of how data is structured in the code.
	* Normalized Data Model - a data model where certain pieces of data in a database that refer to other pieces of data use cross-references, rather than copying and embedding the data directly.		* Normalized Data Model - a data model where certain pieces of data in a database that refer to other pieces of data use cross-references, rather than copying and embedding the data directly.

Admin: /* NoSQL Verbiage */

2016-08-31T22:26:41Z

NoSQL Verbiage

← Older revision		Revision as of 22:26, 31 August 2016
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	* Embedded Data Model - a data model where any data that is cross-referenced is copied and embedded directly.		* Embedded Data Model - a data model where any data that is cross-referenced is copied and embedded directly.

	~~Note: you~~ should consider embedding for performance reasons if you have a collection with a large number of small documents. If you can group these small documents by some logical relationship and you frequently retrieve the documents by this grouping, you might consider “rolling-up” the small documents into larger documents that contain an array of embedded documents. [https://docs.mongodb.com/manual/core/data-model-operations/]		"You should consider embedding for performance reasons if you have a collection with a large number of small documents. If you can group these small documents by some logical relationship and you frequently retrieve the documents by this grouping, you might consider “rolling-up” the small documents into larger documents that contain an array of embedded documents." [https://docs.mongodb.com/manual/core/data-model-operations/]

	Nice guide to example data patterns. [https://docs.mongodb.com/manual/applications/data-models/]		Nice guide to example data patterns. [https://docs.mongodb.com/manual/applications/data-models/]