- 1 Old Notes
- 2 New Notes
- 3 Github Repositories
- 4 Projects
- 5 Flags
There are a couple of different ways to do wireless attacks with Python.
The One Man Band Approach The first way is sort of painful, or can overload your system: trying to find every wireless network, parsing out clients and access points, listening, identifying and counting packets and unique devices, and managing all of this information. Lots of moving parts. Very painful. Complicated. But you have fine-grained control over every detail.
You end up feeling like a one man band.
For scripts, see the Nosecleaner project on Github: https://github.com/charlesreid1/nosecleaner
Joe Pesci Approach: Besside-ng
This way is painful: besside-ng. besside-ng is like the Joe Pesci of the wireless attack world. Joe Pesci speaks softly and carries a big stick. You give Joe Pesci a MAC number, and just sit back while Joe Pesci gets things done.
Scapy Approach: Mellow Out
The Python way: make things a lot easier for yourself, and let the Scapy Python library do all the parsing of information. Run airodump or similar in the background to make the wireless card channel hop. Run Scapy to parse out all the information that's being collected. (Details?) You still have to scan to find nearby devices/routers, but it makes information management a whole lot easier.
Interesting Python package: https://pypi.python.org/pypi/wireless-radar/0.2
wireless-radar comes with a few tools:
- wprox a scanner for detecting/fingerprinting active 802.11 devices
- mrssi a simple RSSI sensor locking onto a MAC for physically locating the device
- wscan a direction-finder using a directional antenna mounted on a usb rocket launcher
- bprox a Bluetooth device discoverer
- rfdiff to diff the outputs of wprox scans
Nosecleaner Github Repo
Multiple useful scripts in this repository, for each step of the wireless toolchain. Should be revisited with more thought paid to the toolchain objectives and different use cases, however.
Wifi Data Github Repo
Random assortment of scripts. Figure out what's what. Make an attic.
New Wifi Data Github Repo
New Github repository for the UGR project. Initially, it will mainly be a way of sharing files with them. Read-only.
Main page: UGR Project
The scope of the UGR project is to run Linux and Python on Raspberry Pi computers, and capture data from them.
Right now, the plan is to capture wireless data on a C2 server. Not sure what else to do.
If we were to use other data as a model : pollution, dust, light, sound, temperature, humidity
Raspberry Pi could measure pollution, dust, light, sound, temperature, humidity, and cameras and wifi to analyze traffic
Weather timelapse: superimposed weather sensor data with timelapse movie: http://datacanvas.org/project/datacanvas-weather-timelapse/
Pi Data Acquisition
Script/scripts for doing data acquisition of time series from Raspberry Pi.
Similar quantities to what a smartphone time series data set might contain - CPU usage, memory usage, programs, network names, etc.
Pythona powerful programming language
Machine learning libraries: Sklearn
Web and Networking Python:
IPython and Jupyter: Jupyter
Drawing, Geometry, and Shapes:
Shapely (for drawing shapes): Shapely
Geography library: Geos
General Useful Python Utilities:
Python Remote Objects: Pyro
Logging (create multi-channel log messages): Logging
Keyboard (control keyboard from Python): Keyboard
Black Hat Python:
Network scanning: Python/Scanner
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Wirelessall things wireless.
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aircrack-nga suite of tools for wireless cracking.
Many Ways to Crack a Wifi: Cracking Wifi
Aircrack Benchmarking: Aircrack/Benchmarking
WEP Attacks with Aircrack: Aircrack/WEP Cracking
WPA Attacks with Aircrack: Aircrack/WPA Cracking
Aircrack Hardware: Aircrack/Packet Injection Testing
Basic Usage of Airodump
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