Hello, I'm new using Hashcat and my setup has an old 560ti that gives arround 24000 H/s. And I'm thinking in getting another GPU that could give more H/s, as Im still trying dont wanna spend to much, and around 100€ would be mi limit.
would be a 7970 a good purchase? I could buy it for around 50, and also have the chance of getting a 6990 for 70.
or is just better to buy something newer?
thanks.
Buy something newer and buy an nvidia card. If you're on a budget a used 750TI or 960 might be ok.
(03-17-2019, 12:11 PM)undeath Wrote: [ -> ]Buy something newer and buy an nvidia card. If you're on a budget a used 750TI or 960 might be ok.
Thanks for the reply, based on some GPU Hash benchmarks i see that 7970 provides more H/s than the Nvidia (750ti only 60000) cards that you suggest, could you give me a reason for going for Nvidia instead Radeon?
cheers.
I don't think AMD 7xxx cards still have opencl support, hence won't work with hashcat. Besides. AMD cards quickly overheat/heat throttle and need much more power.
I've managed to assemble and run Hashcat 5.1.0 with Windows 10 and 7x AMD Radeon HD 7970 / AMD Radeon R9 280x (generally the same cards) last month.
But yeah, they are kinda hot and power hungry so you might be better off with some Nvidia card.
Thanks, I've been researching in the forum and I could buy for the same price (60 EUR) a 750ti, a 960 or a 1050. Any suggestion to take the better along those three? 1080 are more than 600 EUR in Spain, the idea is okay around with something cheaper and then in a while but something better off the prices go down.
750TI is definitely the slowest of the three. Not sure about 960 vs 1050.
Have also the chance of a 1060 3gb for just a little more, would it be a good candidate? I didn't found real world H/S for the 1060.
I think the 1060 is definitely your best bet. Here is a benchmark of my GTX 1060 6GB (Driver is currently not uptodate, but it should give you a good idea) :
Code:
hashcat (v5.1.0) starting in benchmark mode...
Benchmarking uses hand-optimized kernel code by default.
You can use it in your cracking session by setting the -O option.
Note: Using optimized kernel code limits the maximum supported password length.
To disable the optimized kernel code in benchmark mode, use the -w option.
* Device #1: WARNING! Kernel exec timeout is not disabled.
This may cause "CL_OUT_OF_RESOURCES" or related errors.
To disable the timeout, see: https://hashcat.net/q/timeoutpatch
OpenCL Platform #1: NVIDIA Corporation
======================================
* Device #1: GeForce GTX 1060 6GB, 1536/6144 MB allocatable, 10MCU
Benchmark relevant options:
===========================
* --optimized-kernel-enable
Hashmode: 0 - MD5
Speed.#1.........: 9655.7 MH/s (68.75ms) @ Accel:1024 Loops:256 Thr:256 Vec:1
Hashmode: 100 - SHA1
Speed.#1.........: 3688.0 MH/s (90.32ms) @ Accel:512 Loops:256 Thr:256 Vec:1
Hashmode: 1400 - SHA2-256
Speed.#1.........: 1351.2 MH/s (61.51ms) @ Accel:256 Loops:128 Thr:256 Vec:1
Hashmode: 1700 - SHA2-512
Speed.#1.........: 470.9 MH/s (88.59ms) @ Accel:256 Loops:64 Thr:256 Vec:1
Hashmode: 2500 - WPA-EAPOL-PBKDF2 (Iterations: 4096)
Speed.#1.........: 175.6 kH/s (57.96ms) @ Accel:256 Loops:64 Thr:256 Vec:1
Hashmode: 1000 - NTLM
Speed.#1.........: 16901.8 MH/s (78.58ms) @ Accel:1024 Loops:512 Thr:256 Vec:1
Hashmode: 3000 - LM
Speed.#1.........: 9599.9 MH/s (69.40ms) @ Accel:256 Loops:1024 Thr:256 Vec:1
Hashmode: 5500 - NetNTLMv1 / NetNTLMv1+ESS
Speed.#1.........: 9692.7 MH/s (68.38ms) @ Accel:1024 Loops:256 Thr:256 Vec:1
Hashmode: 5600 - NetNTLMv2
Speed.#1.........: 753.1 MH/s (55.29ms) @ Accel:256 Loops:64 Thr:256 Vec:1
Hashmode: 1500 - descrypt, DES (Unix), Traditional DES
Speed.#1.........: 413.1 MH/s (50.31ms) @ Accel:8 Loops:1024 Thr:256 Vec:1
Hashmode: 500 - md5crypt, MD5 (Unix), Cisco-IOS $1$ (MD5) (Iterations: 1000)
Speed.#1.........: 4362.7 kH/s (69.37ms) @ Accel:1024 Loops:1000 Thr:32 Vec:1
Hashmode: 3200 - bcrypt $2*$, Blowfish (Unix) (Iterations: 32)
Speed.#1.........: 7800 H/s (39.82ms) @ Accel:16 Loops:8 Thr:8 Vec:1
Hashmode: 1800 - sha512crypt $6$, SHA512 (Unix) (Iterations: 5000)
Speed.#1.........: 64347 H/s (62.78ms) @ Accel:512 Loops:128 Thr:32 Vec:1
Hashmode: 7500 - Kerberos 5 AS-REQ Pre-Auth etype 23
Speed.#1.........: 149.8 MH/s (69.63ms) @ Accel:256 Loops:64 Thr:64 Vec:1
Hashmode: 13100 - Kerberos 5 TGS-REP etype 23
Speed.#1.........: 148.7 MH/s (70.14ms) @ Accel:256 Loops:64 Thr:64 Vec:1
Hashmode: 15300 - DPAPI masterkey file v1 (Iterations: 23999)
Speed.#1.........: 30273 H/s (57.32ms) @ Accel:256 Loops:64 Thr:256 Vec:1
Hashmode: 15900 - DPAPI masterkey file v2 (Iterations: 7999)
Speed.#1.........: 21634 H/s (59.68ms) @ Accel:256 Loops:128 Thr:32 Vec:1
Hashmode: 7100 - macOS v10.8+ (PBKDF2-SHA512) (Iterations: 35000)
Speed.#1.........: 5368 H/s (55.40ms) @ Accel:128 Loops:32 Thr:256 Vec:1
Hashmode: 11600 - 7-Zip (Iterations: 524288)
Speed.#1.........: 4257 H/s (74.59ms) @ Accel:512 Loops:128 Thr:256 Vec:1
Hashmode: 12500 - RAR3-hp (Iterations: 262144)
Speed.#1.........: 19661 H/s (64.79ms) @ Accel:8 Loops:16384 Thr:256 Vec:1
Hashmode: 13000 - RAR5 (Iterations: 32767)
Speed.#1.........: 17069 H/s (74.45ms) @ Accel:256 Loops:64 Thr:256 Vec:1
Hashmode: 6211 - TrueCrypt PBKDF2-HMAC-RIPEMD160 + XTS 512 bit (Iterations: 2000)
Speed.#1.........: 114.9 kH/s (77.80ms) @ Accel:128 Loops:64 Thr:256 Vec:1
Hashmode: 13400 - KeePass 1 (AES/Twofish) and KeePass 2 (AES) (Iterations: 6000)
Speed.#1.........: 64510 H/s (105.32ms) @ Accel:512 Loops:256 Thr:32 Vec:1
Hashmode: 6800 - LastPass + LastPass sniffed (Iterations: 500)
Speed.#1.........: 1054.6 kH/s (73.71ms) @ Accel:128 Loops:125 Thr:256 Vec:1
Hashmode: 11300 - Bitcoin/Litecoin wallet.dat (Iterations: 199999)
Speed.#1.........: 1996 H/s (52.22ms) @ Accel:128 Loops:64 Thr:256 Vec:1
Started: Mon Mar 18 19:42:54 2019
Stopped: Mon Mar 18 19:48:43 2019
Note that the 6GB variant does also have slightly more streaming processors than the 3GB, so the performance will be a bit less.
Might be also interesting for you:
https://hashcat.net/forum/thread-7765.html
Thanks a lot, I'll get a 1060 3GB as is a good piece to pay around and learn.