| Filename | BackTrack - Penetration Testing Distribution Setting Part III |
| Permission | rw-r--r-- |
| Author | WhySoSeriousssssssssssss |
| Date and Time | 02:03 |
| Label | hack |
| Action |
Tested and working cards
We were able to test the following cards. Note that "passed" means "passed an aireplay -9" injection test. We will be expanding on this list as more feedback domes form the community. From our testing we found that most major chipsets were supported, as well as the most common cards.
- AWUS036H (rtl8187, r8187) - both mac80211 and IEEE drivers - passed
- AWUS036NH (Ralink RT2870/3070) - using the mac80211 rt2x00usb drivers - passed
- BCM4312 802.11b/g LP-PHY (rev 01) - using the mac80211 b43, works well - passed
- Rockland N3 - (Ralink RT2870/3070) - using the mac80211 rt2x00usb drivers - passed
- Edimax EW-7318USG USB - (Ralink RT2501/RT2573) - using the mac80211 rt2500usb/rt73usb drivers - passed
- ASUSTek Computer, Inc. RT2573 - using the mac80211 rt2500usb/rt73usb drivers- passed
- Linksys WUSB54GC ver 3 - using the mac80211 rt2800usb drivers - passed
- Ubiquiti SRC - using the mac80211 ath9k drivers- passed
- Internal Intel Corporation PRO/Wireless 3945ABG - using the mac80211 iwl3945 drivers- passed
- Dlink WNA-2330 PCMCIA - using the mac80211 ath5k drivers- passed
- Atheros Communications Inc. AR9285 Wireless Network Adapter (PCI-Express) (rev 01) - using the mac80211 ath9k drivers- passed
- Netgear wg111v2 - using the mac80211 rtl8187 drivers- passed
- ZyXEL AG-225H v2 - using the mac80211 zd1211 drivers - passed
- Intel 4956/5xxx - using the iwlagn drivers - passed
Working, without injection
- Broadcom Corporation BCM4321 802.11a/b/g/n (rev 03)
- Broadcom Corporation BCM4322 802.11a/b/g/n Wireless LAN Controller (rev 01)
NON working cards
- D-Link DWL-122 - using the mac80211 prism2_usb drivers - fail
- Linksys WUSB600N v2 - using the mac80211 rt2800usb drivers - fail
- AWUS051NH - fail
Advanced Corner
Getting Cuda working on Backtrack 4
BackTrack includes many tools which utilize the power of graphics cards to greatly improve perfor- mance. This section will help you get your environment set up to use these tools and also to set up a development environment to make your own tools.
Check http://en.wikipedia.org/wiki/CUDA to see if your video card is capable of running CUDA applications
Installing the Nvidia Drivers
Installing the driver is now easier than ever. We use the installer from the nvidia web site and do not alter the install in any way. This means no matter which kernel version you are running on backtrack the nvidia-driver package should work. Note: Be sure to log out of X before installing the driver or it will fail
root@bt:~# apt-get install nvidia-driver
Simply follow the prompts and choose the defaults and you should be fine. Since every system is different there are 2 ways to get your xorg.conf working on backtrack.
Method 1: The installer attempts to do this method but in some cases its needed to do it manually. Log out of the X server.
root@bt:~# Xorg -configure
root@bt:~# cp /root/xorg.conf.new /etc/X11/xorg.conf
root@bt:~# startx
Method 2: Nvidia bundles a config tool with their install which may work better for you that the Xorg tools. Log out of the X server
root@bt:~# nvidia-xconfig
root@bt:~# startx
Installing the CUDA Toolkit
The toolkit contains the nvcc compiler and all the libraries needed to build any GPU based app- lications from source. The toolkit is also needed if you are planning on developing any of your own applications.
root@bt:~# apt-get install cuda-toolkit
The default install is /opt/cuda. Note: The toolkit is designed to be installed as root. If you want to install it as another user you will need to add the following lines to the users .bashrc file.
PATH=$PATH:/usr/local/cuda/bin
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib
export PATH
export LD_LIBRARY_PATH
Installing the Nvidia SDK
You no longer package the cuda code samples in our repositories due to the size the package has become. The code samples are extremely useful though if you are interested in cuda development. Getting it installed on backtrack is fairly simple.
root@bt:~# wget http://developer.download.nvidia.com/compute/cuda/3_1/sdk/gpu-computingsdk_3.1_linux.run
root@bt:~# chmod 755 gpucomputingsdk_3.1_linux.run
root@bt:~# ./gpucomputingsdk_3.1_linux.run
The only thing I change aside from the default choices is the place where the NVIDIA_SDK is installed. On backtrack you install to /opt. you have to instruct the installer to install to /opt/cuda/ so that my code samples are inside my cuda directory.
Getting up and running with Pyrit
Pyrit is included in the backtrack iso but in order to use it with cuda you will need to install the cuda kernel module. This is part of the cpyrit package. Installation is fairly straight forward:
root@bt:~# apt-get install cpyrit-cuda
You can check if your GPU is being recognized with the following command:
root@bt:~# pyrit list_cores
Pyrit 0.3.1-dev (svn r279) (C) 2008-2010 Lukas Lueg http://pyrit.googlecode.com. This code is distributed under the GNU General Public License v3+.
The following cores seem available...
#1: 'CUDA-Device #1 'GeForce GTX 295
#2: 'CUDA-Device #2 'GeForce GTX 295
#3: 'CUDA-Device #3 'GeForce GTX 295
#4: 'CUDA-Device #4 'GeForce GTX 295
#5: 'CUDA-Device #5 'GeForce GTX 295
#6: 'CUDA-Device #6 'GeForce GTX 295
#8: 'CUDA-Device #8 'GeForce GTX 295
You can then run a benchmark to see how many keys per second your system in capable of:
root@bt:~# pyrit benchmark
Pyrit 0.3.1-dev (svn r279) (C) 2008-2010 Lukas Lueg http://pyrit.googlecode.com. This code is distributed under the GNU General Public License v3+. Running benchmark (97384.8 PMKs/s)... |
Computed 97384.83 PMKs/s total.
#1: 'CUDA-Device #1 'GeForce GTX 295: 11520.5 PMKs/s (RTT 2.9)
#2: 'CUDA-Device #2 'GeForce GTX 295: 11274.3 PMKs/s (RTT 2.9)
#3: 'CUDA-Device #3 'GeForce GTX 295: 10439.3 PMKs/s (RTT 2.9)
#4: 'CUDA-Device #4 'GeForce GTX 295: 11095.7 PMKs/s (RTT 2.9)
#5: 'CUDA-Device #5 'GeForce GTX 295: 10564.8 PMKs/s (RTT 2.6)
#6: 'CUDA-Device #6 'GeForce GTX 295: 10533.7 PMKs/s (RTT 2.9)
#7: 'CUDA-Device #7 'GeForce GTX 295: 10414.8 PMKs/s (RTT 2.6)
#8: 'CUDA-Device #8 'GeForce GTX 295: 11333.7 PMKs/s (RTT 2.9)
Add CUDA syntax highlighting to Vim
Here is how to add CUDA syntax highlighting to Backtrack. First you need to install vim-full:
root@bt:~# apt-get install vim-full
Then grab the syntax file:
root@bt:~# cd /usr/share/vim/vim71/syntax/
root@bt:/usr/share/vim/vim71/syntax# wget http://www.backtrack-linux.org/patches/cu.vim.txt
root@bt:/usr/share/vim/vim71/syntax# mv cu.vim.txt cu.vim
Next change into your root directory (or whichever user you are using):
root@bt:~# touch .vimrc
root@bt:~# vi .vimrc
Add the following lines:
au BufNewFile,BufRead *.cu set ft=cu
syntax on
Now your vi should be set up for CUDA syntax highlighting.
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