clGetPlatformIDs(): CL_PLATFORM_NOT_FOUND_KHR Hashcat

Question

我正在尝试在我的

Zen Archlinux

上运行 hashcat，我使用的是

4.15.4-1-zen

内核版本。我有一个 NVIDIA Geforce 920MX 和一个 Intel i6189DU。 我安装了最新的

nvidia-dkms

驱动程序以及

opencl-nvidia

软件包。 我还安装了最新的Hashcat版本。

当我运行 hashcat 命令时，我收到此错误：

clGetPlatformIDs(): CL_PLATFORM_NOT_FOUND_KHR

。 我使用一个工具来确定可用的 openCL 平台

clinfo

，输出仅显示我的 CPU 平台而不是我的 GPU，但

hashcat

命令仍然输出相同的错误。

有什么帮助吗？

Answer 1

这里的弓箭手同事，我找到了一种修复损坏的 hashcat 的方法，如您所见：

    $ hashcat -b
    hashcat (...) starting in benchmark mode...

    clGetPlatformIDs(): CL_PLATFORM_NOT_FOUND_KHR

    ATTENTION! No OpenCL-compatible or CUDA-compatible platform found.
    You are probably missing the OpenCL or CUDA runtime installation.

    $ pacman -S clinfo
    $ clinfo 
    Number of platforms                               0

修复此问题的一种方法是安装 pocl（Portable OpenCL 是 OpenCL 的开源实现）：

    $ pacman -S pocl
    $ clinfo
    Number of platforms                               1
      Platform Name                                   Portable Computing Language
      Platform Vendor                                 The pocl project
      ...

    $ hashcat -b
    hashcat (...) starting in benchmark mode...

    OpenCL API (...) - Platform #1 [The pocl project]
    =========================================================================================================================
    * Device #1: pthread-Intel(R) ...

    Benchmark relevant options:
    ===========================
    * --optimized-kernel-enable

    Hashmode: 0 - MD5

    Speed.#1.........:   ...
    ...

快乐破解！ ( ͡° ͜ʖ ͡°)

Answer 2

Linuxmint 22.1：

sudo apt-get install pocl-opencl-icd

Answer 3

import binascii, hashlib
import sys


def generate_ntlm_hash(text):
    ntlm_hash = binascii.hexlify(hashlib.new('md4', text.encode('utf-16le')).digest())
    return ntlm_hash


min_distance = float('inf')
closest_hash = ""
closest_word = ""
def read_hashes_from_file(filename):
    hashes = []
    with open(filename, 'r') as file:
        for line in file:
            line = line.strip()
            if line:
                hashes.append(line)
    return hashes

def hamming_distance(hash1, hash2):
    bin_hash1 = bin(int(hash1, 16))[2:].zfill(32)
    bin_hash2 = bin(int(hash2, 16))[2:].zfill(32)
    distance = sum(bit1 != bit2 for bit1, bit2 in zip(bin_hash1, bin_hash2))
    return distance

def find_closest_hash(target_hash, hash_list, word):
    global min_distance
    global closest_hash
    global closest_word
    for hash_value in hash_list:
        distance = hamming_distance(target_hash, hash_value)
        if distance < min_distance:
            min_distance = distance
            closest_hash = hash_value
            closest_word = word
    return



def main():
    dictionary_file = input("Enter the name of the dictionary file (e.g., michael.txt): ")
    hash_file = input("Enter the name of the hashes file (e.g., hashes.txt): ")
    try:
        with open(dictionary_file, 'r') as file:
            words = [word.strip() for word in file]
    except FileNotFoundError:
        print("Dictionary file not found.")
        return

    known_hashes = read_hashes_from_file(hash_file)
    total_words = len(words)
    current_word = 0

    for word in words:
        ntlm_hash = generate_ntlm_hash(word)
        if ntlm_hash in known_hashes:
            print(f"Word: {word}, NTLM Hash: {ntlm_hash}, Status: Cracked!")
        else:
            find_closest_hash(ntlm_hash, known_hashes,word)
            completion_percentage = (current_word / total_words) * 100
            sys.stdout.write(f"\rProcessing: {completion_percentage:.2f}% closest_word: {closest_word}, Min_distance: {min_distance:.2f}")
            sys.stdout.flush()
        current_word += 1

    print(f"Word: {closest_word}, Closest Hash: {closest_hash}")
    print("\nProcessing completed.")

if __name__ == "__main__":
    main()

现在它确实显示了破解的百分比，并找到您尝试过的所有密码文本中最接近的汉明距离，并且还打印了最接近的单词。