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