HOWTO : nVidia and HashCat on Kali Linux 2018.4

CPU : Intel i7-8750H (6-core with HyperThreading and Graphic Display)
Extra Graphic Display : nVidia GTX 1060 (laptop)

There are two display graphic cards on the same system, namely Optimus on laptop. The installation of nVidia display driver on Kali Linux 2018.4 is difference to Ubuntu 18.04.1 on the same system. You can refer to the link here for Ubuntu 18.04.1 even they are using the same version of nVidia display driver - Version 390.87 at the time of this writing.

Step 1 :

apt updaate
apt install nvidia-kernel-dkms primus bumblebee bbswitch-dkms nvidia-smi

Step 2 :

Reboot the system.

To confirm the installation.

nvidia-smi

Step 3 :

Install HashCat which does not require CUDA.

apt install hashcat-nvidia

Step 4 (optional) :

To install CUDA.

apt install nvidia-cuda-toolkit

To run program that requires CUDA.

bumblebeed --daemon
optirun [program]

That's all! See you.

HOWTO : nVidia CUDA with Kali Linux 1.1.0

Hardware

CPU : Intel i7-3930K
RAM : 32GB DDR3
Hard Drive : 3TB
Display Card : Two nVidia GeForce GTX 590

Install Kali

Install Kali Linux 1.1.0 on the box as usual. Make sure "secure boot" is disabled in your BIOS before installing. After that, you update the Kali accordingly.

apt-get update
apt-get dist-upgrade

Install nVidia Driver

apt-get install -y linux-headers-$(uname -r)
apt-get install nvidia-kernel-dkms nvidia-driver nvidia-cuda-toolkit nvidia-xconfig

nvidia-xconfig

sed 's/quiet/quiet nouveau.modeset=0/g' -i /etc/default/grub
update-grub
reboot

Please note that Kali official does not recommend to compile applications yourself as they think that it will damage the Kali.

Install cudaHashcat

mkdir hacking
cd hacking

wget http://hashcat.net/files-legacy/cudaHashcat-1.31.7z

7za x cudaHashcat-1.31.7z

(Please noted that the current version 1.32 does not compatible to Kali 1.1.0's nVidia driver 340.x).

Test the cudaHashcat

cd /root/hacking/cudaHashcat-1.31/
./cudaExample0.sh

cd /root/hacking/cudaHashcat-1.31/
./cudaExample400.sh

cd /root/hacking/cudaHashcat-1.31/
./cudaExample500.sh

Install John the Ripper

apt-get install libssl-dev

cd hacking

wget http://www.openwall.com/john/g/john-1.8.0-jumbo-1.tar.gz
tar -xvzf john-1.8.0-jumbo-1.tar.gz
cd john-1.8.0-jumbo-1/src

./configure
make
make

** If your hashes or passwords are longer than 8 characters, you need to change the following before compiling the John.

cd john-1.8.0-jumbo-1/src
nano params.h

Then change from "8" to "18" or "20" and etc.

#define CHARSET_LENGTH 8

Test the John the Ripper

cd /root/hacking/john-1.8.0-jumbo-1/run

./john --device=0,1,2,3 --format=sha512crypt-cuda /etc/shadow

* since I have 4 GPUs, so the --device should be 4.

*** When you changed the CHARSET_LENGTH, you need to generate a new charset. Do it once only.

wget http://downloads.skullsecurity.org/passwords/rockyou.txt.bz2
bunzip2 -d rockyou.txt.bz2
cp rockyou.txt /root/hacking/john-1.8.0-jumbo-1/run

cd /root/hacking/john-1.8.0-jumbo-1/run

cat rockyou.txt | sed 's/^/:/' > rockyou.pot

mv all.chr all.chr-original
mv alnum.chr alnum.chr-original
mv alpha.chr alpha.chr-original
mv digits.chr digits.chr-original
mv lanman.chr lanman.chr-original

./john --pot=rockyou.pot --make-charset=all.chr
./john --pot=rockyou.pot --make-charset=alnum.chr --external=filter_alnum
./john --pot=rockyou.pot --make-charset=alpha.chr --external=filter_alpha
./john --pot=rockyou.pot --make-charset=digits.chr --external=filter_digits
./john --pot=rockyou.pot --make-charset=lanman.chr --external=filter_lanman

Then your cracking command will be :

./john --pot=rockyou.pot --device=0,1,2,3 --format=sha512crypt-cuda /etc/shadow

Install and Test Cryptohaze

cd hacking
wget http://sourceforge.net/projects/cryptohaze/files/Cryptohaze-Linux_x64_1_31a.tar.bz2/download -O Cryptohaze-Linux_x64_1_31a.tar.bz2

tar xjvf Cryptohaze-Linux_x64_1_31a.tar.bz2

cd /root/hacking/Cryptohaze-Linux
./Cryptohaze-Multiforcer -h NTLM -c charsets/charsetall -f test_hashes/Hashes-NTLM-Full.txt

That's all! See you.

HOWTO : CUDA with Kali Linux 1.0.9

The guide has been updated on FEB 4, 2015 as Kali Linux 1.0.9a includes the nVidia driver 340.x and CUDA 5.5.x.

Hardware

CPU : Intel i7-3930K
RAM : 32GB DDR3
Hard Drive : 3TB
Display Card : Two nVidia GeForce GTX 590

Install Kali

Install Kali Linux 1.0.9 on the box as usual. Make sure "secure boot" is disabled in your BIOS before installing. After that, you update the Kali accordingly.

apt-get update
apt-get dist-upgrade

Install nVidia Driver

apt-get install -y linux-headers-$(uname -r)
apt-get install nvidia-kernel-dkms nvidia-driver nvidia-cuda-toolkit nvidia-xconfig

nvidia-xconfig

sed 's/quiet/quiet nouveau.modeset=0/g' -i /etc/default/grub
update-grub
reboot

Fix the nvidia_uvm error

After the reboot :

cd /usr/src/nvidia-current-331.67
make

cp Module.symvers uvm/
make -C uvm

cp uvm/nvidia-uvm.ko /lib/modules/`uname -r`/updates/dkms

Updated on Jan 8, 2015

Remark : If you use backports version, the nvidia_uvm problem is fixed and the cudaHashcat 1.31 can be running without any problem. The backports version of nVidia driver is 340.65 and the version of CUDA driver is 5.5.22 at this time of writing.

echo "deb http://ftp.debian.org/debian wheezy-backports main contrib non-free" >> /etc/apt/sources.list

apt-get update

apt-get install -t wheezy-backports nvidia-kernel-dkms nvidia-cuda-toolkit nvidia-driver nvidia-xconfig

If you have done the following steps, you are not required to re-do it again.

nvidia-xconfig

sed 's/quiet/quiet nouveau.modeset=0/g' -i /etc/default/grub
update-grub
reboot

Install cudaHashcat

mkdir hacking
cd hacking

wget http://hashcat.net/files/cudaHashcat-1.30.7z

7za x cudaHashcat-1.30.7z

wget http://hashcat.net/files-legacy/cudaHashcat-1.31.7z

7za x cudaHashcat-1.31.7z

(Please noted that the current version 1.32 does not compatible to nVidia driver 340.x).

Test the cudaHashcat

cd /root/hacking/cudaHashcat-1.30/
./cudaExample0.sh

cd /root/hacking/cudaHashcat-1.30/
./cudaExample400.sh

cd /root/hacking/cudaHashcat-1.30/
./cudaExample500.sh

Install John the Ripper

(Please note that the current version of john is john-1.80-jumbo-1.tar.gz)

apt-get install libssl-dev

cd hacking

wget http://www.openwall.com/john/g/john-1.7.9-jumbo-7.tar.gz
tar -xvzf john-1.7.9-jumbo-7.tar.gz
cd john-1.7.9-jumbo-7/src

./configure
make
make clean linux-x86-64-cuda

** If your hashes or passwords are longer than 8 characters, you need to change the following before compiling the John.

cd john-1.7.9-jumbo-7/src
nano params.h

Then change from "8" to "18" or "20" and etc.

#define CHARSET_LENGTH 8

Test the John the Ripper

cd /root/hacking/john-1.7.9-jumbo-7/run

./john --device=0,1,2,3 --format=sha512crypt-cuda /etc/shadow

* since I have 4 GPUs, so the --device should be 4.

*** When you changed the CHARSET_LENGTH, you need to generate a new charset. Do it once only.

wget http://downloads.skullsecurity.org/passwords/rockyou.txt.bz2
bunzip2 -d rockyou.txt.bz2
cp rockyou.txt /root/hacking/john-1.7.9-jumbo-7/run

cd /root/hacking/john-1.7.9-jumbo-7/run

cat rockyou.txt | sed 's/^/:/' > rockyou.pot

mv all.chr all.chr-original
mv alnum.chr alnum.chr-original
mv alpha.chr alpha.chr-original
mv digits.chr digits.chr-original
mv lanman.chr lanman.chr-original

./john --pot=rockyou.pot --make-charset=all.chr
./john --pot=rockyou.pot --make-charset=alnum.chr --external=filter_alnum
./john --pot=rockyou.pot --make-charset=alpha.chr --external=filter_alpha
./john --pot=rockyou.pot --make-charset=digits.chr --external=filter_digits
./john --pot=rockyou.pot --make-charset=lanman.chr --external=filter_lanman

Then your cracking command will be :

./john --pot=rockyou.pot --device=0,1,2,3 --format=sha512crypt-cuda /etc/shadow

Install and Test Cryptohaze

cd hacking
wget http://sourceforge.net/projects/cryptohaze/files/Cryptohaze-Linux_x64_1_31a.tar.bz2/download -O Cryptohaze-Linux_x64_1_31a.tar.bz2

tar xjvf Cryptohaze-Linux_x64_1_31a.tar.bz2

cd /root/hacking/Cryptohaze-Linux
./Cryptohaze-Multiforcer -h NTLM -c charsets/charsetall -f test_hashes/Hashes-NTLM-Full.txt

That's all! See you.

HOWTO : Kali Linux 1.0.6 for All Purpose

This article is also suit for Kali Linux 1.0.9a

Kali Linux is designed for penetration testing. I am going to make it for daily use operating system as well as for penetration testing.

Installation

Make sure you select full disk encryption when install the Kali Linux on your computer. Your root password should be as strong as possible.

(A) Sudoer

Basic user of Kali Linux is root. For daily usage, a sudoer is much better.

Login as root. Create a new user, e.g. "Samiux" at Applications -- System Tools -- Preferences -- System Settings -- User Accounts. Make sure the new user password is strong enough.

adduser samiux sudo

* where samiux is the new user name.

Then, you need to logout and re-login to make the setting effective. Now, you can use command with "sudo" with your user's password.

(B) Apparmor

It is not effective to use "NoScript" Add-ons on Iceweasel as almost all web pages are using javascript. To protect your browser from being compromised, an alternative way is to implement the Apparmor. Apparmor for Iceweasel can be used in penetration testing and daily use.

sudo apt-get install apparmor apparmor-docs apparmor-notify apparmor-profiles apparmor-utils dh-apparmor python-libapparmor

Edit the /etc/default/grub to make apparmor to active after boot.

sudo nano /etc/default/grub

Locate the following string :

GRUB_CMDLINE_LINUX_DEFAULT="quiet"

To make it looks like :

GRUB_CMDLINE_LINUX_DEFAULT="quiet apparmor=1 security=apparmor"

Then run the following command :

sudo update-grub

After that, create a file namely usr.lib.iceweasel.iceweasel at /etc/apparmor.d/ :

sudo nano /etc/apparmor.d/usr.lib.iceweasel.iceweasel

Copy the following content to the file and save it.



Then change the mode of iceweasel apparmor to enforce by using the following command :

sudo aa-enforce /etc/apparmor.d/usr.lib.iceweasel.iceweasel

To update the rule of apparmor, just run the following command and ask some questions. Most likely, you just need to answer "Allow".

sudo aa-logprof

(C) Iceweasel Add-ons

You may need to install "FoxyProxy" Add-ons to Iceweasel.

sudo apt-get install xul-ext-foxyproxy-standard

You can install any available Add-ons by searching the database :

sudo apt-cache search xul-ext

(D) Power Saving for Laptop

Applying the following setting, your battery life of your laptop will be extended a bit, for example 2 hours battery life more. I have tested this setting on Lenovo ThinkPad X201s and Apple MacBook Air (Mid 2013) with Live USB as well as a Zotac small PC with nVidia display.

Although the i915 is for Intel display, but it is no harm to add them to your box.

nano /etc/modprobe.d/i915.conf

Append the following :

options i915 i915_enable_rc6=1
options i915 i915_enable_fbc=1
options i915 lvds_downclock=1

update-initramfs -u

This file "99macbookair6" is for USB 3.0 power saving. Download this file, "99macbookair6", make it executable and place it at /etc/pm/power.d/99macbookair6



nano /etc/rc.local

Insert the following before "exit 0".

/etc/pm/power.d/99macbookair6 true

Then install the tlp.

nano /etc/apt/sources.list

Append the following :

deb http://ppa.launchpad.net/linrunner/tlp/ubuntu lucid main

Save and exit. Then run the following :

apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 02D65EFF

apt-get update
apt-get install tlp tlp-rdw

nano /etc/default/tlp

Change the following values.

DISK_IDLE_SECS_ON_AC=0
DISK_IDLE_SECS_ON_BAT=2
MAX_LOST_WORK_SECS_ON_BAT=60
CPU_SCALING_GOVERNOR_ON_BAT=powersave
DISK_APM_LEVEL_ON_BAT="1 1"
RUNTIME_PM_ALL=1
RESTORE_DEVICE_STATE_ON_STARTUP=1

* Or, leave the /etc/default/tlp settings untouch

To examine the power saving condition, you can install and run "powertop" or/and run "tlp-stat".

sudo apt-get install powertop

sudo nano /etc/default/grub

Locate the following string :

GRUB_CMDLINE_LINUX_DEFAULT="quiet apparmor=1 security=apparmor"

And make it looks like :

GRUB_CMDLINE_LINUX_DEFAULT="quiet pcie_aspm=force apparmor=1 security=apparmor radeon.dpm=1 acpi_backlight=vendor"

Then run the following command :

sudo update-grub

No matter your display card is Intel, nVidia or AMD Radeon, you can apply the captioned setting. Meanwhile, you can alter the settings at the /etc/default/tlp for your display card (any) even the settings labelled as "radeon".

If your laptop is Lenovo ThinkPad, you need to install the following too. After that, restart the tlp or reboot.

sudo apt-get install tp-smapi-dkms acpi-call-tools

(E) Changing Repositories Mirror

If your Kali Linux update/upgrade is slow due to slow mirror, you can hard code the repositories mirror in order to improve the update/upgrade performance.

There is a mirror list of Kali Linux. You can change the mirror at /etc/apt/sources.list by refering to this link.

(F) nVidia CUDA

If you have an nVidia card and wanted to use CUDA to do password cracking, you can refer to this link for the installation.

(G) Some Useful Applications

There are some useful applications that you may want to install to the Kali Linux. You can refer to this link for the installation.

Apparmor for Hexchat (/etc/apparmor.d/usr.bin.hexchat) :



Apparmor for Radiotray (/etc/apparmor.d/usr.bin.radiotray) :



Apparmor for VirtualBox (/etc/apparmor.d/usr.bin.VBox) :



(H) Lenovo ThinkPad TrackPoint

nano /usr/share/X11/xorg.conf.d/20-thinkpad.conf

Copy the following to the 20-thinkpad.conf :



(I) Kali Linux GRUB Background Reborn

After the installation, the GRUB background of the Kali Linux will be blue on black. However, it should be a Kali Linux background. We are going to get it back.

sudo apt-get update
sudo apt-get remove grub-pc
sudo apt-get install grub-pc

After that, you can reboot your computer.

That's all! See you.

HOWTO : CUDA on Kali Linux 1.0.6

Step 1 :

apt-get install libcudart4 linux-headers-$(uname -r) nvidia-cuda-toolkit

Step 2 :

mkdir /etc/X11/xorg.conf.d

echo -e 'Section "Device"\n\tIdentifier "nVidia GPU"\n\tDriver "nvidia"\n\tOption "NoLogo" "1"\n\tOption "RenderAccel" "1"\n\tOption "TripleBuffr" "true"\n\tOption "MigrationHeuristic" "greedy"\nEndSection' > /etc/X11/xorg.conf.d/20-nvidia.conf

OR

apt-get install nvidia-xconfig
nvidia-xconfig

Step 3 :

Update the boot loader to disable the open source nvidia display driver.

sed 's/quiet/quiet nouveau.modeset=0/g' -i /etc/default/grub
update-grub
reboot

Step 4 (Optional) :

To test the CUDA with multiforcer.

# multiforcer for nvidia (example)
cd /usr/share/multiforcer/
multiforcer -h NTLM -c charsets/charsetall -f test_hashes/Hashes-NTLM-Full.txt --noopencl --nocpu

Step 5 (Optional) :

John the Ripper for CUDA.

# 64-bit
wget http://www.openwall.com/john/g/john-1.7.9-jumbo-7.tar.gz
tar -xvzf john-1.7.9-jumbo-7.tar.gz
cd john-1.7.9-jumbo-7/src
make
make clean linux-x86-64-gpu

cd ../run
./john --help

That's all! See you.

HOWTO : CUDA on Kali Linux 1.0.5

Step 1 :

Download the CUDA driver from nVidia Official Site.

# 64-bit
wget http://developer.download.nvidia.com/compute/cuda/5_5/rel/installers/cuda_5.5.22_linux_64.run

# 32-bit
wget http://developer.download.nvidia.com/compute/cuda/5_5/rel/installers/cuda_5.5.22_linux_32.run

Step 2 :

Install the CUDA driver. Accept the default values and select to install nVidia display driver also.

# 64-bit
chmod +x cuda_5.5.22_linux_64.run
./cuda_5.5.22_linux_64.run

# 32-bit
chmod +x cuda_5.5.22_linux_32.run
./cuda_5.5.22_linux_32.run

Step 3 :

Create a .bash_profile.

nano /root/.bash_profile

# 64-bit
export PATH=/usr/local/cuda-5.5/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-5.5/lib64:$LD_LIBRARY_PATH

# 32-bit
export PATH=/usr/local/cuda-5.5/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-5.5/lib:$LD_LIBRARY_PATH

Step 4 :

Update the boot loader to disable the open source nvidia display driver.

sed 's/quiet/quiet nouveau.modeset=0/g' -i /etc/default/grub
update-grub
reboot

Step 5 (Optional) :

To test the CUDA with multiforcer.

# multiforcer for nvidia (example)
cd /usr/share/multiforcer/
multiforcer -h NTLM -c charsets/charsetall -f test_hashes/Hashes-NTLM-Full.txt --noopencl

Step 6 (Optional) :

John the Ripper for CUDA.

# 64-bit
wget http://www.openwall.com/john/g/john-1.7.9-jumbo-7.tar.gz
tar -xvzf john-1.7.9-jumbo-7.tar.gz
cd john-1.7.9-jumbo-7/src
make
make clean linux-x86-64-gpu

cd ../run
./john --help

That's all! See you.

HOWTO : Cryptohaze on Ubuntu Desktop 12.04 LTS

Cryptohaze is a CUDA & OpenCL accelerated rainbow table implementation from the ground up, and a CUDA hash brute forcing tool with support for many hash types including MD5, SHA1, LM, NTLM, and lots more!

Cryptohaze is for 64-bit system only.

Step 1 :

sudo -sH
cd /opt

wget "http://downloads.sourceforge.net/project/cryptohaze/Cryptohaze-Linux_x64_1_31a.tar.bz2?r=http%3A%2F%2Fsourceforge.net%2Fprojects%2Fcryptohaze%2F%3Fsource%3Ddlp&ts=1368806028&use_mirror=nchc" -O Cryptohaze-Linux_x64_1_31a.tar.bz2

tar -xjvf Cryptohaze-Linux_x64_1_31a.tar.bz2
rm Cryptohaze-Linux_x64_1_31a.tar.bz2
cd /opt/Cryptohaze-Linux

Step 2 :

To run it.

sudo -sH
cd /opt/Cryptohaze-Linux

Create "single_charset" for the operation.

nano single_charset

Append the following :

ABCEDFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz1234567890~!@#$%^&*()_+|}{":?><`-=\][';/.,

Cracking the sample SHA1 hashes :

./Cryptohaze-Multiforcer -h SHA1 -f test_hashes/Hashes-SHA1-Full.txt -c single_charset --threads 512 --blocks 512 -m 500

That's all! See you.

HOWTO : CUDA on Ubuntu Desktop 12.04 LTS

When install Ubuntu Desktop 12.04 LTS, select "nomodeset" by pressing F6 on the purple screen with boot up menu. The boot up menu can be reached by pressing "Enter" or "Spacebar" when seeing a keybroad and a human figure on the bottom of the screen during the boot up.

After the installation, the nvidia display driver is installed automatically.

Step 1 :

sudo add-apt-repository ppa:ginggs/backports
sudo apt-get update
sudo apt-get install nvidia-cuda-toolkit

That's all! See you.

HOWTO : Troubleshooting CUDA on Pentoo 2013.0 RC1.1

As Pentoo 2013.0 RC1.1 is using hardened kernel, some application may not working properly. You may need to inspect and change the pax settings of the application in order to make it to work properly.

Use paxctl to inspect and change the pax settings.

paxctl -h
paxctl -v [application name]

Since the current Pentoo 2013.0 RC1.1 (as updated to April 29, 2013), the CUDA do not work properly by default. You are required to do something on it. This bug may be fixed in the next update or RC version.

First of all, make sure the libraries of CUDA are loading properly by making sure the following lines are at the file /etc/env.d/99cuda :

cat /etc/env.d/99cuda

PATH=/opt/cuda/bin:/opt/cuda/libnvvp
ROOTPATH=/opt/cuda/bin
LD_LIBRARY_PATH=/opt/cuda/lib64:/opt/cuda/lib

Finally, make sure some of the applications are set to proper pax settings. For example, cudaHashcat-plus64.bin and Cryptohaze-Multiforcer which are running with CUDA but they are not setting with pax flags properly at the current version.

Make sure the pax settings should be shown as the following :



Known Issue

The current version/update as on April 29, 2013, the pyrit does not work properly with CUDA. Since pyrit is written in Python, the paxctl does not work at all. According to one of the developers, the pyrit will be removed from the distribution.

That's all! See you.

HOWTO : Setup My Back|Track 5r3 Personal Supercomputer

My Hardware

CPU : Intel i7-3930K (6 cores, 12 cores with Hyper-Threading, Socket 2011)
Motherboard : ASUS SaberTooth X79
RAM : Corsair Vengeance DDR3 1600 32GB (4GB x 8)
Display Card : Inno3D nVidia GeForce GTX 590 384bit 3072MB DDR5 x 2
Hard Drive : WD SATA III 3TB
Power Supply : Seasonic X-series 1250W
Cooling : Water cooling system with EK products
Case : Lian Li PC-z70 (modified)

My Operating System

Back|Track 5r3 64-bit system as the host operating system for the captioned hardware.

My Problem

When boot up the Back|Track 5r3 and started "startx", the screen of the monitor will be black out. It is because I have nVidia display card in the system.

The only way to solve it is when booting up to the Back|Track 5r3, press "Tab" in the boot option menu. Then enter the following at the end of "text splash vga=791".

text splash vga=791 nomodeset

After that, the Back|Track 5r3 will boot up after entering the command "startx". Install the system as usual to your hard drive.

After the installation is completed, do not reboot the system. Edit the following file instead after mounted the partitions of the hard drive.

nano /etc/default/grub

Locate 'GRUB_CMDLINE_LINUX_DEFAULT="text splash vga=791"' and append the following :

text splash vga=791 nomodeset

and it will be looking like this :

GRUB_CMDLINE_LINUX_DEFAULT="text splash vga=791 nomodeset"

Then execute the following commands :

update-grub
fix-splash

Reboot the system.

My nVidia and CUDA drivers

Install the nVidia current driver from the repos of Back|Track :

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

After the nVidia driver is installed, execute the following command :

nvidia-xconfig

Now, it is high time to install the CUDA driver. Go to the CUDA Developer site and download the driver. Make sure you selected Ubuntu 10.04 version.

64-bit version :

wget http://developer.download.nvidia.com/compute/cuda/5_0/rel-update-1/installers/cuda_5.0.35_linux_64_ubuntu10.04-1.run

32-bit version :

wget http://developer.download.nvidia.com/compute/cuda/5_0/rel-update-1/installers/cuda_5.0.35_linux_32_ubuntu10.04-1.run

After the download, make it the be executable.

For example :

chmod +x cuda_5.0.35_linux_64_ubuntu10.04-1.run

Then, install it and follow the instruction on screen. Accept the default settings.

cuda_5.0.35_linux_64_ubuntu10.04-1.run

The last step for the installation is to set up the path of the executable files and libraries.

nano /root/.bashrc

Append the following line at the end of the file.

PATH=$PATH:/usr/local/cuda-5.0/bin

nano /etc/ld.so.conf.d/cuda.conf

Add the following lines to the file.

/usr/local/cuda-5.0/lib
/usr/local/cuda-5.0/lib64

Then execute the following command and reboot afterward.

ldconfig

My Hash Cracking Power

We use oclhashcat+ to test the performance of the cracking power of this hardware.

cd /pentest/passwod/oclhastcat+
./cudaExample0.sh
./cudaExample400.sh
./cudaExample500.sh

If you can see the hashes are cracked, the CUDA is setting up properly.

My Addtional Softwares

This host is for hashes and passwords cracking. The penentration testing work will be doing on virtual machines.

I will install virtualbox, sysinfo, shutter, synaptic, gtk-recordmydesktop, and sensors-applet to enhance the function of this host.

By the way, I need to fix the minor bugs of the Back|Track 5r3.

Bug #1 :

There is no sound since Back|Track 5.

mkdir /root/.config/autostart
nano /root/.config/autostart/pulseaudio.desktop

Add the following lines to the file.

[Desktop Entry]
Type=Application
Exec=/usr/bin/pulseaudio
Hidden=false
NoDisplay=false
X-GNOME-Autostart-enabled=true
Name=Pulseaudio
Comment=Start Pulseaudio

Bug #2 :

Wicd cannot connect to D-Bus since Back|Track 5.

dpkg-reconfigure wicd
update-rc.d wicd defaults

That's all! See you.

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 : 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 : Cryptohaze Multiforcer on 2 nVidia GeForce GTX 590 and Intel i7-3930K

The Cryptohaze Multiforcer is a high performance CUDA password cracker that is designed to target large lists of hashes. Performance holds very solid with large lists, such that on a suitable server, cracking a list of 1 000 000 passwords is not significantly slower than cracking a list of 10. For anyone who deals with large lists of passwords, this is a very useful tool! Algorithm support includes MD5, NTLM, LM, SHA1, and many others. The official website of Cryptohaze Multiforcer is here.

Download Cryptohaze-Linux_x64_1_30.tar.bz2

tar -xjvf Cryptohaze-Linux_x64_1_30.tar.bz2

cd Cryptohaze-Linux

nano single_charset

Append the following :

ABCEDFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz1234567890~!@#$%^&*()_+|}{":?><`-=\][';/.,

Cracking the sample SHA1 hashes on my two nVidia GeForce GTX 590 system :

./Cryptohaze-Multiforcer -h SHA1 -f test_hashes/Hashes-SHA1-Full.txt -c single_charset --threads 512 --blocks 512 -m 500

Hardware Configuration :

CPU : Intel i7-3930K (12 cores with Hyper-Threading, Socket 2011)
Motherboard : ASUS SaberTooth X79
RAM : Corsair Vengeance DDR3 1600 32GB (4GB x 8)
Display Card : Inno3D nVidia GeForce GTX 590 384bit 3072MB DDR5 x 2
Hard Drive : Seagate SATA II 1TB x 2
Power Supply : Seasonic X-series 1250W
CPU Heat Sink : Corsair H100 Liquid CPU Cooler
Case : Corsair Graphite Series 600T Black

Remarks :

Installation of CUDA on Back|Track 5 R1

That's all! See you.

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 : nVidia CUDA Toolkit 4.0 on Ubuntu 11.04 Server

The CUDA Toolkit 4.0 is released on May 2011. If you have nVidia display card that have several CUDAs on it, you will interested in this tutorial. This time, I would like to show you how to install CUDA Toolkit 4.0 on Ubuntu 11.04 Server.

You will experience a more faster server after the installation of CUDA Toolkit 4.0.

This HOWTO does not require to install X.

Step 1 :

Add the CUDA 4.0 PPA.
sudo add-apt-repository ppa:aaron-haviland/cuda-4.0

Thanks for the developer of CUDA 4.0 PPA - Aaron Haviland of his contribution to make CUDA Toolkit to be installed easily.

Step 2 :

sudo apt-get update
sudo apt-get upgrade

64-bit :
sudo apt-get install nvidia-cuda-gdb nvidia-cuda-toolkit nvidia-compute-profiler libnpp4 nvidia-cuda-doc libcudart4 libcublas4 libcufft4 libcusparse4 libcurand4 nvidia-current nvidia-opencl-dev nvidia-current-dev nvidia-cuda-dev opencl-headers

32-bit :
sudo apt-get install nvidia-cuda-gdb nvidia-cuda-toolkit nvidia-compute-profiler lib32npp4 nvidia-cuda-doc lib32cudart4 lib32cublas4 lib32cufft4 lib32cusparse4 lib32curand4 nvidia-current nvidia-opencl-dev nvidia-current-dev nvidia-cuda-dev opencl-headers

Step 3 :

sudo nano /etc/init.d/nvidia_cuda

Append the following lines.

============= Copy from here ================
#!/bin/bash

PATH=/sbin:/bin:/usr/bin:$PATH

/sbin/modprobe nvidia

if [ "$?" -eq 0 ]; then

   # Count the number of NVIDIA controllers found.
   N3D=`/usr/bin/lspci | grep -i NVIDIA | grep "3D controller" | wc -l`
   NVGA=`/usr/bin/lspci | grep -i NVIDIA | grep "VGA compatible controller" | wc -l`

   N=`expr $N3D + $NVGA - 1`
   for i in `seq 0 $N`; do
      /bin/mknod -m 666 /dev/nvidia$i c 195 $i;
   done

   /bin/mknod -m 666 /dev/nvidiactl c 195 255

else
   exit 1
fi

=========== Copy to here =================

Step 4 :

sudo chmod +x /etc/init.d/nvidia_cuda
sudo update-rc.d nvidia_cuda defaults

Step 5 :

Reboot your system.

Remarks

I do not have nVidia display cards server in hand at the moment, I am not sure the captioned startup script working properly or not.

That's all! See you.

HOWTO : nVidia CUDA Toolkit 4.0 on Ubuntu 11.04 Desktop

The CUDA Toolkit 4.0 is released on May 2011. If you have nVidia display card that have several CUDAs on it, you will interested in this tutorial. This time, I would like to show you how to install CUDA Toolkit 4.0 on Ubuntu 11.04 Desktop.

You will experience a more faster desktop after the installation of CUDA Toolkit 4.0. Meanwhile, if you installed SMPlayer, you can playback 1080p videos with the help of vdpau.

Step 1 :

Add the CUDA 4.0 PPA.
sudo add-apt-repository ppa:aaron-haviland/cuda-4.0

Thanks for the developer of CUDA 4.0 PPA - Aaron Haviland of his contribution to make CUDA Toolkit to be installed easily.

Step 2 :

sudo apt-get update
sudo apt-get upgrade

64-bit :
sudo apt-get install nvidia-cuda-gdb nvidia-cuda-toolkit nvidia-compute-profiler libnpp4 nvidia-cuda-doc libcudart4 libcublas4 libcufft4 libcusparse4 libcurand4 nvidia-current nvidia-opencl-dev nvidia-current-dev nvidia-cuda-dev opencl-headers

32-bit :
sudo apt-get install nvidia-cuda-gdb nvidia-cuda-toolkit nvidia-compute-profiler lib32npp4 nvidia-cuda-doc lib32cudart4 lib32cublas4 lib32cufft4 lib32cusparse4 lib32curand4 nvidia-current nvidia-opencl-dev nvidia-current-dev nvidia-cuda-dev opencl-headers

Step 2a (Optional) :

If you do not have any nVidia driver installed before or you encounter any problem of booting up your system, you need to do the following command. Otherwise, this step is not required at all.

sudo nvidia-xconfig

**This step may not be required.

Step 3 :

Reboot your system.

Step 4 (Optional) :

To install SMPlayer.

sudo apt-get install smplayer smplayer-translations smplayer-themes

Then set it to use "vdpau" at "Output Driver" at "Preference".

Step 5 (Optional) :

Once installed the CUDA Toolkit and nVidia drivers, you can download the sample codes for testing.

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

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

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

Accept the default settings.

cd NVIDIA_GPU_computing_SDK/C
make

** Please ignore the warning messages for unsupported gcc version. That is no harm at all.

Run the sample codes.

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

That's all! See you.

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.

HOWTO : nVidia CUDA 4.0 RC on Ubuntu 11.04 Server

If you have nVidia display card that have several CUDAs on it, you will interested in this tutorial. This time, I would like to show you how to install CUDA 4.0 RC on Ubuntu 11.04 Server.

You will experience a faster server after the installation of CUDA 4.0.

This HOWTO does not require to install X.

Step 1 :

Add the CUDA 4.0 PPA.
sudo add-apt-repository ppa:aaron-haviland/cuda-4.0

Step 2 :

sudo apt-get update
sudo apt-get upgrade

64-bit :
sudo apt-get install nvidia-cuda-gdb nvidia-cuda-toolkit nvidia-compute-profiler libnpp4 nvidia-cuda-doc libcudart4 libcublas4 libcufft4 libcusparse4 libcurand4 nvidia-current nvidia-opencl-dev nvidia-current-dev nvidia-cuda-dev opencl-headers

32-bit :
sudo apt-get install nvidia-cuda-gdb nvidia-cuda-toolkit nvidia-compute-profiler lib32npp4 nvidia-cuda-doc lib32cudart4 lib32cublas4 lib32cufft4 lib32cusparse4 lib32curand4 nvidia-current nvidia-opencl-dev nvidia-current-dev nvidia-cuda-dev opencl-headers

Step 3 :

sudo nano /etc/init.d/nvidia_cuda

Append the following lines.

============= Copy from here ================
#!/bin/bash

PATH=/sbin:/bin:/usr/bin:$PATH

/sbin/modprobe nvidia

if [ "$?" -eq 0 ]; then

   # Count the number of NVIDIA controllers found.
   N3D=`/usr/bin/lspci | grep -i NVIDIA | grep "3D controller" | wc -l`
   NVGA=`/usr/bin/lspci | grep -i NVIDIA | grep "VGA compatible controller" | wc -l`

   N=`expr $N3D + $NVGA - 1`
   for i in `seq 0 $N`; do
      /bin/mknod -m 666 /dev/nvidia$i c 195 $i;
   done

   /bin/mknod -m 666 /dev/nvidiactl c 195 255

else
   exit 1
fi

=========== Copy to here =================

Step 4 :

sudo chmod +x /etc/init.d/nvidia_cuda
sudo update-rc.d nvidia_cuda defaults

Step 5 :

Reboot your system.

Remarks

I do not have nVidia display cards server in hand at the moment, I am not sure the captioned startup script working properly or not.

That's all! See you.

HOWTO : nVidia CUDA 4.0 RC on Ubuntu 11.04 Desktop

If you have nVidia display card that have several CUDAs on it, you will interested in this tutorial. This time, I would like to show you how to install CUDA 4.0 RC on Ubuntu 11.04 Desktop.

You will experience a faster desktop after the installation of CUDA 4.0. Meanwhile, if you installed SMPlayer, you can playback 1080p videos with the help of vdpau.

Step 1 :

Add the CUDA 4.0 PPA.
sudo add-apt-repository ppa:aaron-haviland/cuda-4.0

Step 2 :

sudo apt-get update
sudo apt-get upgrade

64-bit :
sudo apt-get install nvidia-cuda-gdb nvidia-cuda-toolkit nvidia-compute-profiler libnpp4 nvidia-cuda-doc libcudart4 libcublas4 libcufft4 libcusparse4 libcurand4 nvidia-current nvidia-opencl-dev nvidia-current-dev nvidia-cuda-dev opencl-headers

32-bit :
sudo apt-get install nvidia-cuda-gdb nvidia-cuda-toolkit nvidia-compute-profiler lib32npp4 nvidia-cuda-doc lib32cudart4 lib32cublas4 lib32cufft4 lib32cusparse4 lib32curand4 nvidia-current nvidia-opencl-dev nvidia-current-dev nvidia-cuda-dev opencl-headers

Step 2a :

If you do not have any nVidia driver installed before, you need to do the following command. Otherwise, this step is not required at all.

sudo nvidia-xconfig

Step 3 :

Reboot your system.

Step 4 (Optional) :

To install SMPlayer.

sudo apt-get install smplayer smplayer-translations smplayer-themes

Then set it to use "vdpau" at "Output Driver" at "Preference".

Known issue

Sample codes cannot be compiled successful due to newer C compiler. However, you can download the sample programs which are compiled with C compiler of Ubuntu 10.10. The compiled sample programs are in 64-bit.

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

tar -xvzf CUDA_4.0_samples_x64.tar.gz
cd CUDA_4.0_samples_x64
./nbody

That's all! See you.