Kali linux установить драйвера адаптера
Live boot currently is not supported. The following documentation assumes an installed version of Kali Linux, whether that is a VM or bare-metal.
This document explains how to install NVIDIA GPU drivers and CUDA support, allowing integration with popular penetration testing tools. We will not be using nouveau, being the open-source driver for NVIDIA, instead we will installing the close-source from NVIDIA.
We recommend that you do not attempt this in a Virtual Machine. It is possible, however its not straight forward, and should only be done if you have a deep understanding of Linux. It is not covered in this guide, as there are too many items to cover for everyone’s environment and setup.
Prerequisites
First, you’ll need to ensure that your NVIDIA card supports CUDA.
GPUs with a CUDA compute capability > 5.0 are recommended, but GPUs with less will still work.
[email protected]:~$ grep "contrib non-free" /etc/apt/sources.list deb http://http.kali.org/kali kali-rolling main contrib non-free non-free-firmware [email protected]:~$ [email protected]:~$ sudo apt update [. ] [email protected]:~$ [email protected]:~$ sudo apt -y full-upgrade -y [. ] [email protected]:~$ [email protected]:~$ [ -f /var/run/reboot-required ] && sudo reboot -f Dedicated cards
Let’s determine the exact GPU installed, and check the kernel modules it’s using. Take note, the lspci command contains a unique PCI bus address. Be sure to include the correct address lspci -s XX.XX.X -v :
[email protected]:~$ lspci | grep -i vga 07:00.0 VGA compatible controller: NVIDIA Corporation GP106 [GeForce GTX 1060 6GB] (rev a1) [email protected]:~$ [email protected]:~$ lspci -s 07:00.0 -v 07:00.0 VGA compatible controller: NVIDIA Corporation GP106 [GeForce GTX 1060 6GB] (rev a1) (prog-if 00 [VGA controller]) Subsystem: Gigabyte Technology Co., Ltd GP106 [GeForce GTX 1060 6GB] Flags: bus master, fast devsel, latency 0, IRQ 100 Memory at f6000000 (32-bit, non-prefetchable) [size=16M] Memory at e0000000 (64-bit, prefetchable) [size=256M] Memory at f0000000 (64-bit, prefetchable) [size=32M] I/O ports at e000 [size=128] Expansion ROM at 000c0000 [disabled] [size=128K] Capabilities: Kernel driver in use: nouveau Kernel modules: nouveau [email protected]:~$ Optimus cards
For optimus (laptops and notebooks), you will not see NVIDIA for the primary card. You may also not even see NVIDIA listed at all. You can see what the primary card is by doing:
[email protected]:~$ lspci | grep -i vga 00:02.0 VGA compatible controller: Intel Corporation HD Graphics 620 (rev 02) [email protected]:~$ To detect the NVIDIA card, we need to install nvidia-detect :
[email protected]:~$ sudo apt install -y nvidia-detect [. ] [email protected]:~$ nvidia-detect Detected NVIDIA GPUs: 01:00.0 3D controller [0302]: NVIDIA Corporation GM108M [GeForce 940MX] [10de:134d] (rev a2) Checking card: NVIDIA Corporation GM108M [GeForce 940MX] (rev a2) Uh oh. Failed to identify your Debian suite. [email protected]:~$ [email protected]:~$ lspci -s 01:00.0 -v 01:00.0 3D controller: NVIDIA Corporation GM108M [GeForce 940MX] (rev a2) Subsystem: Lenovo GM108M [GeForce 940MX] Flags: bus master, fast devsel, latency 0, IRQ 132, IOMMU group 10 Memory at 93000000 (32-bit, non-prefetchable) [size=16M] Memory at 80000000 (64-bit, prefetchable) [size=256M] Memory at 90000000 (64-bit, prefetchable) [size=32M] I/O ports at 5000 [size=128] Capabilities: Kernel driver in use: nouveau Kernel modules: nouveau [email protected]:~$ They nvidia-detect package may fail in places due to Kali being a rolling distribution as it requires a stable release.
Installation
Notice how Kernel driver in use & Kernel modules from lspci are using nouveau, signalling the open-source driver for NVIDIA cards. We are now going to switch to the close-source drivers, and the CUDA toolkit (allowing for tool to take advantage of the GPU).
During installation of the drivers the system created new kernel modules, so its best for to-do a reboot:
[email protected]:~$ sudo apt install -y nvidia-driver nvidia-cuda-toolkit ┌─────────────────────────────────┤ Configuring xserver-xorg-video-nvidia ├─────────────────────────────────┐ │ │ │ Conflicting nouveau kernel module loaded │ │ │ │ The free nouveau kernel module is currently loaded and conflicts with the non-free nvidia kernel module. │ │ │ │ The easiest way to fix this is to reboot the machine once the installation has finished. │ │ │ │ │ │ │ └───────────────────────────────────────────────────────────────────────────────────────────────────────────┘ [email protected]:~$ [email protected]:~$ sudo reboot -f [email protected]:~$ Dots Per Inch (DPI) & Pixels Per Unch PPI
Upon Kali starting back up, certain things may appear different than what is expected:
- If certain things are smaller, this could because of HiDPI
- However, if certain things are larger, this could because the DPI is incorrect
Verify Driver Installation
Now that our system should be ready to go, we need to verify the drivers have been loaded correctly. We can quickly verify this by running the nvidia-smi tool and lspci once again:
[email protected]:~$ nvidia-smi Tue Jan 28 11:37:47 2020 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 430.64 Driver Version: 430.64 CUDA Version: 10.1 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | |===============================+======================+======================| | 0 GeForce GTX 106. Off | 00000000:07:00.0 On | N/A | | 0% 50C P8 7W / 120W | 116MiB / 6075MiB | 0% Default | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: GPU Memory | | GPU PID Type Process name Usage | |=============================================================================| | 0 807 G /usr/lib/xorg/Xorg 112MiB | | 0 979 G xfwm4 2MiB | +-----------------------------------------------------------------------------+ [email protected]:~$ [email protected]:~$ lspci | grep -i vga 07:00.0 VGA compatible controller: NVIDIA Corporation GP106 [GeForce GTX 1060 6GB] (rev a1) [email protected]:~$ [email protected]:~$ lspci -s 07:00.0 -v [. ] Kernel driver in use: nvidia Kernel modules: nvidia [email protected]:~$ You can see our hardware has been detected we are using nvidia rather than nouveau drive now!
Hashcat
With the output displaying our driver and GPU correctly, we can now dive into benchmarking (using the CUDA toolkit). Before we get too far ahead, let’s double check to make sure hashcat and CUDA are working together:
[email protected]:~$ sudo apt install -y hashcat [email protected]:~$ [email protected]:~$ hashcat -I hashcat (v6.0.0) starting. CUDA Info: ========== CUDA.Version.: 10.2 Backend Device ID #1 (Alias: #2) Name. GeForce GTX 1060 6GB Processor(s). 10 Clock. 1771 Memory.Total. 6075 MB Memory.Free. 5908 MB OpenCL Info: ============ OpenCL Platform ID #1 Vendor. NVIDIA Corporation Name. NVIDIA CUDA Version.: OpenCL 1.2 CUDA 10.2.185 Backend Device ID #2 (Alias: #1) Type. GPU Vendor.ID. 32 Vendor. NVIDIA Corporation Name. GeForce GTX 1060 6GB Version. OpenCL 1.2 CUDA Processor(s). 10 Clock. 1771 Memory.Total. 6075 MB (limited to 1518 MB allocatable in one block) Memory.Free. 5888 MB OpenCL.Version.: OpenCL C 1.2 Driver.Version.: 440.100 [email protected]:~$ It appears everything is working, let’s go ahead and run hashcat’s inbuilt benchmark test.
Benchmarking
[email protected]:~$ hashcat -b | uniq hashcat (v6.0.0) 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 * Device #2: 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 CUDA API (CUDA 10.2) ==================== * Device #1: GeForce GTX 1060 6GB, 5908/6075 MB, 10MCU OpenCL API (OpenCL 1.2 CUDA 10.2.185) - Platform #1 [NVIDIA Corporation] ======================================================================== * Device #2: GeForce GTX 1060 6GB, skipped Benchmark relevant options: =========================== * --optimized-kernel-enable Hashmode: 0 - MD5 Speed.#1. 14350.4 MH/s (46.67ms) @ Accel:64 Loops:1024 Thr:1024 Vec:8 Hashmode: 100 - SHA1 Speed.#1. 4800.5 MH/s (69.83ms) @ Accel:32 Loops:1024 Thr:1024 Vec:1 [. ] Started: Tue Jul 21 17:12:39 2020 Stopped: Tue Jul 21 17:16:10 2020 [email protected]:~$ There are a multitude of configurations to improve cracking speed, not mentioned in this guide. However, we encourage you to take a look at the hashcat documentation for your specific cases.
Troubleshooting
In the event setup isn’t going as planned, we’ll install clinfo for detailed troubleshooting information:
[email protected]:~$ sudo apt install -y clinfo [email protected]:~$ [email protected]:~$ clinfo Number of platforms 1 Platform Name NVIDIA CUDA Platform Vendor NVIDIA Corporation Platform Version OpenCL 1.2 CUDA 10.1.120 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_copy_opts cl_nv_create_buffer Platform Extensions function suffix NV Platform Name NVIDIA CUDA [. ] [email protected]:~$ [email protected]:~$ clinfo | wc -l 116 [email protected]:~$ OpenCL Loaders
It may be necessary to check for additional packages that may be conflicting with our setup. Let’s first check to see what OpenCL Loader we have installed. The NVIDIA OpenCL Loader and the generic OpenCL Loader will both work for our system:
[email protected]:~$ dpkg -l | grep -i icd ii nvidia-egl-icd:amd64 430.64-5 amd64 NVIDIA EGL installable client driver (ICD) ii nvidia-opencl-icd:amd64 430.64-5 amd64 NVIDIA OpenCL installable client driver (ICD) ii nvidia-vulkan-icd:amd64 430.64-5 amd64 NVIDIA Vulkan installable client driver (ICD) ii ocl-icd-libopencl1:amd64 2.2.12-2 amd64 Generic OpenCL ICD Loader ii ocl-icd-opencl-dev:amd64 2.2.12-2 amd64 OpenCL development files [email protected]:~$ If mesa-opencl-icd is installed, we should remove it:
[email protected]:~$ dpkg -l | grep -i mesa-opencl-icd ii mesa-opencl-icd:amd64 19.3.2-1 amd64 free implementation of the OpenCL API -- ICD runtime [email protected]:~$ [email protected]:~$ sudo apt remove mesa-opencl-icd [email protected]:~$ Since we have determined that we have a compatible ICD loader installed, we can easily determine which loader is currently being used:
[email protected]:~$ clinfo | grep -i "icd loader" ICD loader properties ICD loader Name OpenCL ICD Loader ICD loader Vendor OCL Icd free software ICD loader Version 2.2.12 ICD loader Profile OpenCL 2.2 [email protected]:~$ As expected, our setup is using the open source loader that was installed earlier. Now, let’s get some detailed information about the system.
Querying GPU Information
We’ll use nvidia-smi once again, but with a much more verbose output:
[email protected]:~$ nvidia-smi -i 0 -q ==============NVSMI LOG============== Timestamp : Fri Feb 14 13:26:21 2020 Driver Version : 430.64 CUDA Version : 10.1 Attached GPUs : 1 GPU 00000000:07:00.0 Product Name : GeForce GTX 1060 6GB Product Brand : GeForce Display Mode : Enabled Display Active : Enabled Persistence Mode : Disabled Accounting Mode : Disabled Accounting Mode Buffer Size : 4000 [. ] Temperature GPU Current Temp : 49 C GPU Shutdown Temp : 102 C GPU Slowdown Temp : 99 C [. ] Clocks Graphics : 139 MHz SM : 139 MHz Memory : 405 MHz Video : 544 MHz [. ] Processes Process ID : 815 Type : G Name : /usr/lib/xorg/Xorg Used GPU Memory : 132 MiB Process ID : 994 Type : G Name : xfwm4 Used GPU Memory : 2 MiB [email protected]:~$ It looks like our GPU is being recognized correctly, so let’s use glxinfo to determine if 3D Rendering is enabled:
[email protected]:~$ sudo apt install -y mesa-utils [email protected]:~$ [email protected]:~$ glxinfo | grep -i "direct rendering" direct rendering: Yes [email protected]:~$ The combination of these tools should assist the troubleshooting process greatly. If you still experience issues, we recommend searching for similar setups and any nuances that may affect your specific system.
Updated on: 2023-Mar-06
Author: g0tmi1k