Install NVIDIA GPU Drivers

Do not attempt this in a VM. It is possible in theory, however this likely will not work and we do not recommend that users attempt this.

This document explains how to install NVIDIA GPU drivers and CUDA support, allowing integration with popular penetration testing tools.

**This guide is also for a dedicated card (desktops users) and Optimus (notebook users).


First, you’ll need to ensure that your card supports CUDA.

GPUs with a CUDA compute capability > 5.0 are recommended, but GPUs with less will still work.

Afterwards, make sure you have contrib & non-free components are enabled in your network Repositories and that your system is fully up-to-date.

[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
[email protected]:~$

Let’s determine the exact GPU installed, and check the kernel modules it’s using:

[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: <access denied>
        Kernel driver in use: nouveau
        Kernel modules: nouveau

[email protected]:~$

For optimus (or laptops or notebooks):

[email protected]:~$ lspci | grep -i vga
00:02.0 VGA compatible controller: Intel Corporation HD Graphics 620 (rev 02)

Well for primary it’s always gonna give this same result, so don’t worry and even upon using lspci maybe you don’t see nvidia. So for nvidia, we need to install nvidia-detect using sudo apt install nvidia-detect and run it…

[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]:~$ 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: <access denied>
        Kernel driver in use: nouveau
        Kernel modules: nouveau

That’s your nvidia card. and rest are same for both.

Notice how Kernel driver in use & Kernel modules are using nouveau? This is the open source driver for nVidia. This guide covers installing the close source, from NVIDIA.

There is a package called nvidia-detect which will fail to detect the driver due to Kali being a rolling distribution and requires a stable release.


Once the system has rebooted from doing an OS upgrade, we will proceed to install the 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 a reboot is required:

[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.                  │
│                                                                                                           │
│                                                  <Ok>                                                     │
│                                                                                                           │

[email protected]:~$
[email protected]:~$ sudo reboot -f
[email protected]:~$


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.

[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.


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.


[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:
* Device #2: WARNING! Kernel exec timeout is not disabled.
             This may cause "CL_OUT_OF_RESOURCES" or related errors.
             To disable the timeout, see:
* 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.


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
[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
        GPU Current Temp            : 49 C
        GPU Shutdown Temp           : 102 C
        GPU Slowdown Temp           : 99 C
        Graphics                    : 139 MHz
        SM                          : 139 MHz
        Memory                      : 405 MHz
        Video                       : 544 MHz
        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: 2022-Jul-01
Author: g0tmi1k