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Message-ID: <!&!AAAAAAAAAAAYAAAAAAAAAHkpcheVEOpDkVRLau6glY7CgAAAEAAAADbT8FB7BY9KktaV1XuaCQUBAAAAAA==@home.se>
Date: Mon, 4 Jan 2021 16:34:34 +0100
From: "Anton Berggren" <antonb@...e.se>
To: <john-users@...ts.openwall.com>
Subject: Sv: Cracking rar password with rar-opencl
Thanks for all help!
Im new to this. Really dont know what im doing but i have read and tried all
kinds of examples in the documentation.
My test results for your example benchmark of rar and rar-opencl gave me
this.
C:\Users\Anton\Downloads\john-1.9.0-jumbo-1-win64\run>john --test
-format=rar
Will run 4 OpenMP threads
Benchmarking: rar, RAR3 (length 5) [SHA1 256/256 AVX2 8x AES]... (4xOMP)
DONE
Raw: 555 c/s real, 139 c/s virtual
C:\Users\Anton\Downloads\john-1.9.0-jumbo-1-win64\run>john --test
-format=rar-opencl
Will run 4 OpenMP threads
Device 3: GeForce GTX 760
Benchmarking: rar-opencl, RAR3 (length 5) [SHA1 OpenCL AES]... (4xOMP) DONE
Raw: 8353 c/s real, 8336 c/s virtual
Rar-archive is really small. 12,3kb.
I will try everything as you people suggest.
clinfo.exe gave me this:
C:\Users\Anton\Downloads>clinfo.exe
Number of platforms 2
Platform Name NVIDIA CUDA
Platform Vendor NVIDIA Corporation
Platform Version OpenCL 1.2 CUDA 11.2.66
Platform Profile FULL_PROFILE
Platform Extensions
cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics
cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics
cl_khr_fp64 cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing
cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll
cl_nv_d3d10_sharing cl_khr_d3d10_sharing cl_nv_d3d11_sharing cl_nv_copy_opts
cl_nv_create_buffer cl_khr_int64_base_atomics cl_khr_device_uuid
Platform Extensions function suffix NV
Platform Name Intel(R) OpenCL
Platform Vendor Intel(R) Corporation
Platform Version OpenCL 1.2
Platform Profile FULL_PROFILE
Platform Extensions cl_intel_dx9_media_sharing
cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_d3d11_sharing
cl_khr_depth_images cl_khr_dx9_media_sharing cl_khr_gl_sharing
cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics
cl_khr_icd cl_khr_local_int32_base_atomics
cl_khr_local_int32_extended_atomics cl_khr_spir
Platform Extensions function suffix INTEL
Platform Name NVIDIA CUDA
Number of devices 1
Device Name GeForce GTX 760
Device Vendor NVIDIA Corporation
Device Vendor ID 0x10de
Device Version OpenCL 1.2 CUDA
Device UUID
054b42bb-0b83-fced-93da-ee6fe9337453
Driver UUID
054b42bb-0b83-fced-93da-ee6fe9337453
Valid Device LUID Yes
Device LUID 5ba3-000000000000
Device Node Mask 0x1
Driver Version 460.89
Device OpenCL C Version OpenCL C 1.2
Device Type GPU
Device Topology (NV) PCI-E, 01:00.0
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 6
Max clock frequency 1150MHz
Compute Capability (NV) 3.0
Device Partition (core)
Max number of sub-devices 1
Supported partition types None
Supported affinity domains (n/a)
Max work item dimensions 3
Max work item sizes 1024x1024x64
Max work group size 1024
Preferred work group size multiple (kernel) 32
Warp size (NV) 32
Preferred / native vector sizes
char 1 / 1
short 1 / 1
int 1 / 1
long 1 / 1
half 0 / 0 (n/a)
float 1 / 1
double 1 / 1
(cl_khr_fp64)
Half-precision Floating-point support (n/a)
Single-precision Floating-point support (core)
Denormals Yes
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity Yes
IEEE754-2008 fused multiply-add Yes
Support is emulated in software No
Correctly-rounded divide and sqrt operations Yes
Double-precision Floating-point support (cl_khr_fp64)
Denormals Yes
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity Yes
IEEE754-2008 fused multiply-add Yes
Support is emulated in software No
Address bits 64, Little-Endian
Global memory size 2147483648 (2GiB)
Error Correction support No
Max memory allocation 536870912 (512MiB)
Unified memory for Host and Device No
Integrated memory (NV) No
Minimum alignment for any data type 128 bytes
Alignment of base address 4096 bits (512 bytes)
Global Memory cache type Read/Write
Global Memory cache size 98304 (96KiB)
Global Memory cache line size 128 bytes
Image support Yes
Max number of samplers per kernel 32
Max size for 1D images from buffer 134217728 pixels
Max 1D or 2D image array size 2048 images
Max 2D image size 16384x16384 pixels
Max 3D image size 4096x4096x4096 pixels
Max number of read image args 256
Max number of write image args 16
Local memory type Local
Local memory size 49152 (48KiB)
Registers per block (NV) 65536
Max number of constant args 9
Max constant buffer size 65536 (64KiB)
Max size of kernel argument 4352 (4.25KiB)
Queue properties
Out-of-order execution Yes
Profiling Yes
Prefer user sync for interop No
Profiling timer resolution 1000ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels No
Kernel execution timeout (NV) Yes
Concurrent copy and kernel execution (NV) Yes
Number of async copy engines 1
printf() buffer size 1048576 (1024KiB)
Built-in kernels (n/a)
Device Extensions
cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics
cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics
cl_khr_fp64 cl_khr_byte_addressable_store cl_khr_icd cl_khr_gl_sharing
cl_nv_compiler_options cl_nv_device_attribute_query cl_nv_pragma_unroll
cl_nv_d3d10_sharing cl_khr_d3d10_sharing cl_nv_d3d11_sharing cl_nv_copy_opts
cl_nv_create_buffer cl_khr_int64_base_atomics cl_khr_device_uuid
Platform Name Intel(R) OpenCL
Number of devices 2
Device Name Intel(R) HD Graphics 4600
Device Vendor Intel(R) Corporation
Device Vendor ID 0x8086
Device Version OpenCL 1.2
Driver Version 20.19.15.5166
Device OpenCL C Version OpenCL C 1.2
Device Type GPU
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 20
Max clock frequency 1200MHz
Device Partition (core)
Max number of sub-devices 0
Supported partition types by <unknown>
(0x9400000000000000)
Supported affinity domains (n/a)
Max work item dimensions 3
Max work item sizes 512x512x512
Max work group size 512
Preferred work group size multiple (kernel) 32
Preferred / native vector sizes
char 1 / 1
short 1 / 1
int 1 / 1
long 1 / 1
half 0 / 0 (n/a)
float 1 / 1
double 0 / 0 (n/a)
Half-precision Floating-point support (n/a)
Single-precision Floating-point support (core)
Denormals No
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity Yes
IEEE754-2008 fused multiply-add No
Support is emulated in software No
Correctly-rounded divide and sqrt operations Yes
Double-precision Floating-point support (n/a)
Address bits 64, Little-Endian
Global memory size 1708759450 (1.591GiB)
Error Correction support No
Max memory allocation 427189862 (407.4MiB)
Unified memory for Host and Device Yes
Minimum alignment for any data type 128 bytes
Alignment of base address 1024 bits (128 bytes)
Global Memory cache type Read/Write
Global Memory cache size 262144 (256KiB)
Global Memory cache line size 64 bytes
Image support Yes
Max number of samplers per kernel 16
Max size for 1D images from buffer 26699366 pixels
Max 1D or 2D image array size 2048 images
Base address alignment for 2D image buffers 4096 bytes
Pitch alignment for 2D image buffers 64 pixels
Max 2D image size 16384x16384 pixels
Max 3D image size 2048x2048x2048 pixels
Max number of read image args 128
Max number of write image args 128
Local memory type Local
Local memory size 65536 (64KiB)
Max number of constant args 8
Max constant buffer size 65536 (64KiB)
Max size of kernel argument 1024
Queue properties
Out-of-order execution No
Profiling Yes
Prefer user sync for interop Yes
Number of simultaneous interops (Intel) 1
Simultaneous interops GL WGL D3D11
Profiling timer resolution 80ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels No
SPIR versions 1.2
printf() buffer size 4194304 (4MiB)
Built-in kernels
block_motion_estimate_intel;block_advanced_motion_estimate_check_intel;block
_advanced_motion_estimate_bidirectional_check_intel
Motion Estimation accelerator version (Intel) 2
Device Extensions cl_intel_accelerator
cl_intel_advanced_motion_estimation cl_intel_ctz
cl_intel_d3d11_nv12_media_sharing cl_intel_dx9_media_sharing
cl_intel_motion_estimation cl_intel_simultaneous_sharing cl_intel_subgroups
cl_khr_3d_image_writes cl_khr_byte_addressable_store cl_khr_d3d10_sharing
cl_khr_d3d11_sharing cl_khr_depth_images cl_khr_dx9_media_sharing
cl_khr_gl_depth_images cl_khr_gl_event cl_khr_gl_msaa_sharing
cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics
cl_khr_gl_sharing cl_khr_icd cl_khr_image2d_from_buffer
cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics
cl_khr_spir
Device Name Intel(R) Core(TM) i5-4670K
CPU @ 3.40GHz
Device Vendor Intel(R) Corporation
Device Vendor ID 0x8086
Device Version OpenCL 1.2 (Build 10094)
Driver Version 5.2.0.10094
Device OpenCL C Version OpenCL C 1.2
Device Type CPU
Device Profile FULL_PROFILE
Device Available Yes
Compiler Available Yes
Linker Available Yes
Max compute units 4
Max clock frequency 3400MHz
Device Partition (core)
Max number of sub-devices 4
Supported partition types by counts, equally, by
names (Intel)
Supported affinity domains (n/a)
Max work item dimensions 3
Max work item sizes 8192x8192x8192
Max work group size 8192
Preferred work group size multiple (kernel) 128
Preferred / native vector sizes
char 1 / 32
short 1 / 16
int 1 / 8
long 1 / 4
half 0 / 0 (n/a)
float 1 / 8
double 1 / 4
(cl_khr_fp64)
Half-precision Floating-point support (n/a)
Single-precision Floating-point support (core)
Denormals Yes
Infinity and NANs Yes
Round to nearest Yes
Round to zero No
Round to infinity No
IEEE754-2008 fused multiply-add No
Support is emulated in software No
Correctly-rounded divide and sqrt operations No
Double-precision Floating-point support (cl_khr_fp64)
Denormals Yes
Infinity and NANs Yes
Round to nearest Yes
Round to zero Yes
Round to infinity Yes
IEEE754-2008 fused multiply-add Yes
Support is emulated in software No
Address bits 64, Little-Endian
Global memory size 17041711104 (15.87GiB)
Error Correction support No
Max memory allocation 4260427776 (3.968GiB)
Unified memory for Host and Device Yes
Minimum alignment for any data type 128 bytes
Alignment of base address 1024 bits (128 bytes)
Global Memory cache type Read/Write
Global Memory cache size 262144 (256KiB)
Global Memory cache line size 64 bytes
Image support Yes
Max number of samplers per kernel 480
Max size for 1D images from buffer 266276736 pixels
Max 1D or 2D image array size 2048 images
Max 2D image size 16384x16384 pixels
Max 3D image size 2048x2048x2048 pixels
Max number of read image args 480
Max number of write image args 480
Local memory type Global
Local memory size 32768 (32KiB)
Max number of constant args 480
Max constant buffer size 131072 (128KiB)
Max size of kernel argument 3840 (3.75KiB)
Queue properties
Out-of-order execution Yes
Profiling Yes
Local thread execution (Intel) Yes
Prefer user sync for interop No
Profiling timer resolution 100ns
Execution capabilities
Run OpenCL kernels Yes
Run native kernels Yes
SPIR versions 1.2
printf() buffer size 1048576 (1024KiB)
Built-in kernels (n/a)
Device Extensions cl_khr_icd
cl_khr_global_int32_base_atomics cl_khr_global_int32_extended_atomics
cl_khr_local_int32_base_atomics cl_khr_local_int32_extended_atomics
cl_khr_byte_addressable_store cl_khr_depth_images cl_khr_3d_image_writes
cl_intel_exec_by_local_thread cl_khr_spir cl_khr_dx9_media_sharing
cl_intel_dx9_media_sharing cl_khr_d3d11_sharing cl_khr_gl_sharing
cl_khr_fp64
NULL platform behavior
clGetPlatformInfo(NULL, CL_PLATFORM_NAME, ...) No platform
clGetDeviceIDs(NULL, CL_DEVICE_TYPE_ALL, ...) No platform
clCreateContext(NULL, ...) [default] No platform
clCreateContext(NULL, ...) [other] Success [NV]
clCreateContextFromType(NULL, CL_DEVICE_TYPE_DEFAULT) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CPU) No devices found in
platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_GPU) No platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ACCELERATOR) No devices
found in platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_CUSTOM) Invalid device type
for platform
clCreateContextFromType(NULL, CL_DEVICE_TYPE_ALL) No platform
-----Ursprungligt meddelande-----
Från: Solar Designer <solar@...nwall.com>
Skickat: den 4 januari 2021 15:15
Till: john-users@...ts.openwall.com
Ämne: Re: [john-users] Cracking rar password with rar-opencl
Hi Anton,
On Mon, Jan 04, 2021 at 11:55:52AM +0100, Anton Berggren wrote:
> Device #0 (1) name: Intel(R) HD Graphics 4600
> Device #1 (2) name: Intel(R) Core(TM) i5-4670K CPU @ 3.40GHz
This embedded GPU is of comparable performance to the CPU. Here's i7-4770K
under Linux:
$ ./john -test -format=rar-opencl -dev=1 Will run 8 OpenMP threads Device 1:
Intel(R) HD Graphics
Benchmarking: rar-opencl, RAR3 (length 5) [SHA1 OpenCL AES]... (8xOMP) Build
log: fcl build 1 succeeded.
fcl build 2 succeeded.
bcl build succeeded.
LWS=16 GWS=640 (40 blocks) DONE
Raw: 680 c/s real, 96000 c/s virtual
$ ./john -test -format=rar-opencl -dev=2 Will run 8 OpenMP threads Device 2:
Intel(R) Core(TM) i7-4770K CPU @ 3.50GHz
Benchmarking: rar-opencl, RAR3 (length 5) [SHA1 OpenCL AES]... (8xOMP) Build
log: Compilation started Compilation done Linking started Linking done
Device build started Device build done Kernel <RarInit> was not vectorized
Kernel <RarHashLoop> was successfully vectorized (8) Kernel <RarFinal> was
successfully vectorized (8) Kernel <RarCheck> was not vectorized Done.
LWS=128 GWS=1024 (8 blocks) DONE
Raw: 459 c/s real, 57.8 c/s virtual
$ ./john -test -format=rar
Will run 8 OpenMP threads
Benchmarking: rar, RAR3 (length 5) [SHA1 256/256 AVX2 8x AES]... (8xOMP)
DONE
Raw: 512 c/s real, 64.5 c/s virtual
Please note that rar-opencl also makes some use of the CPU via OpenMP, even
when its target device is a GPU.
You'll probably want to run similar tests for all 3 of your devices, and
perhaps post the results in here.
> And i resume with this command and get the output
> C:\Users\Anton\Downloads\john-1.9.0-jumbo-1-win64\run>john --restore
> Device 3: GeForce GTX 760 Loaded 1 password hash (rar-opencl, RAR3
> [SHA1 OpenCL AES]) Will run 4 OpenMP threads Proceeding with
> incremental:ASCII Press 'q' or Ctrl-C to abort, almost any other key
> for status
>
> Is it only using my Nvidia GPU? How can i utilize all my decices? Can
> i optimize my rar password cracking for a more effective usage?
> It seems that my GPU usage isnt constant. It goes up and down.. up and
> down.. up and down... about 10-30%. That is what windows reports anyway.
Do you mean 10-30% utilization, or 10-30% left idle (so 70-90% load)?
The fluctuating utilization is possibly because of post-processing done on
the CPU. How large is the RAR archive?
You might increase average GPU utilization by running more than one attack
on it - either start a second instance of JtR with a different "--session"
name and configured to test different candidate passwords (a non-overlapping
wordlist, etc.) or use "--fork=2" (yes, with just one NVIDIA GPU device).
Using the CPU more directly and using its embedded GPU isn't necessarily a
good idea as it'd likely lower your NVIDIA GPU utilization, but feel free to
give this a try with separate sessions. You'll likely want to set a lower
CPU thread count via the environment variable OMP_NUM_THREADS to reduce
competition for the CPU (competition can be very wasteful).
Using all devices in one session (like you technically could with
"--devices=1,2,3 --fork=3" is almost certainly a bad idea since the devices
are so different and since the best way to use a CPU is generally by using
the non-OpenCL format, but feel free to try anyway.
(Maybe I'm over-estimating your NVIDIA GPU's performance, and it's actually
similar to your CPU and your embedded GPU? I notice it's a Kepler era
device, and isn't large.)
Again regarding the fluctuating GPU utilization, see also the "rar-opencl
performance" thread we had in here in September:
https://www.openwall.com/lists/john-users/2020/09/
Windows might be under-reporting GPU utilization. We recently had a thread
in here where this was found to be the case for AMD GPUs. For more reliable
reporting, please use tools that come with the GPU driver.
Anyway, far more importantly than all of the above, you need to focus the
attack to test candidate passwords that are actually likely. You might want
to share in here what you know/recall about the password in plain English,
and we'll help you encode that into options to "john".
Alexander
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