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How To Hack Your Neighbor’s WIFI/Wireless With Your Graphics Card

Necessary Materials:

I will be operating under the assumption that you have created a bootable USB version of Backtrack 4 R1 as is outlined in the tutorial here. You will also need a computer with either a Nvidia (8000 series or higher) or an ATI (4000 series or higher) graphics card for this to work. An internet connection is also required to download the necessary packages.

As far as wireless cards go, an Atheros based card is recommended, but some Intel based cards will also work.

thumbs wrt54router How To Hack Your Neighbors WIFI/Wireless With Your Graphics Card

Getting Things Started:

Now that you have all of your materials together, we need to do a little bit of prep work to get our flash drive up to snuff for this hack. To get things started boot into Backtrack from your flash drive.

Step 1:

If you followed the previous tutorial then networking should already be enabled. Run the following command to update the repositories.

apt-get update

It’s usually a good idea to update your packages to the latest version. To do that run:

apt-get upgrade

Now that we have the latest package list we can get down to installing the proper graphics drivers and the modules we will need.

Step 2:

(Easy Way)

The Backtrack repositories come with a pre-compiled binary of pyrit. Unfortunately the required display drivers in the repository are not always kept up to date. You may get lucky and just have it work for you, I was not so fortunate when I learned the first time around. The easy way is if you want a quick and dirty way of doing it. If you want the most performance out of your setup, the hard way has more steps that detail the process.

For ATI Graphics Cards:

apt-get install atidriver atistream cpyrit-stream

For Nvidia Graphics Cards:

apt-get install nvidia-driver cpyrit-cuda

In order to make sure everything is working you need to boot into an X session. Done by running:

startx

Once the desktop has loaded you will need to launch a command prompt and then run the command:

pyrit list_cores

If you see your graphics card in list, then congratulations, you’re ready for the next step. If it didn’t work for you then it may have crashed the X session. You will need to uninstall the drivers and packages that we just installed.

For ATI Graphics Cards:

apt-get remove cpyrit-stream atidriver atistream

For Nvidia Graphics Cards:

apt-get remove cpyrit-cuda nvidia-driver

(The Hard Way)

So you weren’t lucky enough to just have it work, huh? Not to fret, this section is for you. Whether the above method didn’t work for you or you want to create a flash drive that will work across multiple kinds of systems with different graphics cards in each, this section will walk you through the steps necessary to accomplish it. We will be compiling code from source in order to make this work, but fear not, we are here to hold your hand the whole way through.

The default VESA driver that BackTrack comes with should be enough to allow you to start an X session and download the necessary files. If it’s not, then you can download the files from another computer and transfer it over.

For ATI Graphics Cards:

Since we are going to be compiling from source anyways, we may as well get the most bang for our buck. Pyrit has an additional module for CAL++ support. It has a bit better performance than the pre-compiled stream module that is in the BackTrack repository.

Grab the latest ATI display driver from their driver page here. You need to make sure you select Linux x86 and not x86_x64, as BackTrack is a 32 bit distro. You will then need to grab the latest ATI Stream SDK from here (it’s all the way at the bottom of the page). Finally you will need to grab the CAL++ libraries from here.

Now that we have all of the files downloaded, we can start putting everything into place. Next extract the ATI Stream SDK. Enter the following commands in a command prompt window where /path/to/sdk/ is the actual path to the SDK folder that you just extracted.

export ATISTREAMSDKROOT=/path/to/sdk/

export ATISTREAMSDKSAMPLESROOT=/path/to/sdk/

export LD_LIBRARY_PATH=$ATISTREAMSDKROOT/lib/x86:$LD_LIBRARY_PATH

The next step is to extract the CAL++ library. Copy the contents of the “include” folder into the “include” folder located in /usr/local/include.

Now that all of the files are in place we can download the pyrit source code and begin compiling. Open a command prompt to the location that you want to save the folder that contains the pyrit source. Run the following command:

svn checkout http://pyrit.googlecode.com/svn/trunk/ pyrit_svn

Navigate to the folder called pyrit inside of the pyrit_svn folder. Once inside the folder, run the commands:

python setup.py build

python setup.py install

Next, navigate to the folder called cpyrit_calpp, inside of the pyrit_svn folder. Run the commands:

python setup.py build

python setup.py install

For the next part you need to make sure you are NOT in an X session (i.e. no GUI). Once you are out of the X session and at the command prompt, navigate to the folder where you saved the ATI display driver. Run the following commands:

chmod 777 <name of the display driver>

./<name of the display driver>

Follow the prompts of the installer until it finishes. Afterward, start X again and open a command prompt. To make sure that we’re ready to move on to the actual hacking part, run the command:

pyrit list_cores

You should see it list a CAL++ device along with the number of cores your CPU has minus 1. As a final test, run the command:

pyrit selftest

If the command checks out fine, you are ready to proceed on to the next section. If it doesn’t work for you, post your problem in either the comments or forums and we will try and help as best we can.

For Nvidia Graphics Cards:

First thing we need to do is grab the latest display driver from Nvidia’s site. You can find it here. You will  want the one labeled Linux x86, NOT the one labeled x86_64. Next you will need to grab the CUDA Toolkit. It can be found here. You will want the 32 bit version of the one labeled “CUDA Toolkit for Ubuntu Linux”.

For the next part you will not want to be in a X session. Once you have logged out of X and are at a command prompt, navigate to the folder where you saved the toolkit and display driver. Run the commands:

chmod 777 <name of the display driver>

chmod 777 <name of the toolkit>

./<name of display driver>

./<name of the toolkit>

You can now go back in to an X session. Now that all of the files are in place we can download the pyrit source code and begin compiling. Open a command prompt to the location that you want to save the folder that contains the pyrit source. Run the following command:

svn checkout http://pyrit.googlecode.com/svn/trunk/ pyrit_svn

Navigate to the folder called pyrit inside of the pyrit_svn folder. Once inside the folder, run the commands:

python setup.py build

python setup.py install

Next, navigate to the folder called cpyrit_cuda, inside of the pyrit_svn folder. Run the commands:

python setup.py build

python setup.py install

To make sure that we’re ready to move on to the actual hacking part, run the command:

pyrit list_cores

You should see it list a Cuda device along with the number of cores your CPU has minus 1. As a final test, run the command:

pyrit selftest

If the command checks out fine, you are ready to proceed on to the next section. If it doesn’t work for you, post your problem in either the comments or forums and we will try and help as best we can.

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8 Comments... What's your say?

  1. What would be even more useful is to run a generic cluster using GPUs and boot CDs/USB drives. Imagine being able to throw a problem like generating rainbow files, simulating weather, rendering 3D scenes, playing chess (Grin) or whatever you want so long as the algorithm is suitable to clusters.

    I wonder if anyone makes motherboards with several PCI-E slots for rackmount render farms… It would be an economical solution for some people who need to do huge batch rendering jobs. Come to think of it, the same reasoning applies to recoding videos.

  2. how to hack wifi near 100m by dell laptop.

  3. please sent me wifi
    master key

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