Question

因此，我有以下嵌套列表（已从Nmap XML输出文件中解析出）。这基本上是IP地址及其所有开放端口的列表：

[['192.168.23.78', ['53', '88', '135', '139', '389', '445', '3389']],
 ['192.168.27.243', ['135', '139', '445', '3389', '5800', '5900']],
 ['192.168.99.164', ['135', '139', '445', '3389', '5800', '5900']],
 ['192.168.228.211', ['80']],
 ['192.168.171.74', ['135', '139', '445', '3389', '5800', '5900']]]

我想根据此数据创建一个表，其中每个第一项（所有IP地址）都打印为行。然后，我希望遍历第二个项目（每个IP地址所有端口的列表），并计算每个唯一的端口号。我希望这个新计数的唯一端口列表可以打印为表的列标题。然后，我的空表应该大致如下：

                 53  80  88  135  139  389  445  3389  5800  5900
192.168.23.78
192.168.27.243
192.168.99.164
192.168.228.211
192.168.171.74

然后我希望将X放在具有给定开放端口的每个IP地址的每个正确单元格中，如下所示：

                 53  80  88  135  139  389  445  3389  5800  5900
192.168.23.78    X   X       X    X    X         X
192.168.27.243               X    X         X    X     X     X
192.168.99.164               X    X         X    X     X     X
192.168.228.211      X
192.168.171.74               X    X         X    X     X     X

我该如何处理我的数据集？

我是一个新手，但是我很可能想出如何遍历所有端口号并获得唯一的端口列表。但是我绝对不知道如何在正确的单元格中将X绘制在桌子上

到目前为止，这是我的代码：

#!/usr/bin/env python

from pprint import pprint
import xml.etree.ElementTree as ET

def loopy(item):
    for port in host.findall('ports/port'):
        if port.get('protocol') == "tcp":
            portid = port.get('portid')
            for state in port.findall('state'):
                if state.get('state') == "open":
                    if item == "address":
                        list_addr.append(addr)
                        return
                    elif item == "portid":
                        list_portid.append(portid)

root = ET.parse('scan5.xml').getroot()
result = []
for host in root.findall('host'):
    list_portid = []
    list_addr = []
    address = host.find('address')
    addr = address.get('addr')
    loopy("address")
    loopy("portid")
    if list_addr:
        result.append([list_addr[0], list_portid])

pprint(result)

我的嵌套列表现在位于result中，但是我不知道如何从中创建表。

到目前为止，我的代码仅生成原始列表：

[['10.133.23.78', ['53', '88', '135', '139', '389', '445', '3389']],
 ['10.133.27.243', ['135', '139', '445', '3389', '5800', '5900']],
 ['10.133.99.164', ['135', '139', '445', '3389', '5800', '5900']],
 ['10.135.228.211', ['80']],
 ['10.133.171.74', ['135', '139', '445', '3389', '5800', '5900']]]

Answer 1

您可以使用install并使用prettytable包来可视化漂亮的表

第一个pip install prettytable

然后输入代码

from prettytable import PrettyTable

data = [['192.168.23.78', ['53', '88', '135', '139', '389', '445', '3389']],
        ['192.168.27.243', ['135', '139', '445', '3389', '5800', '5900']],
        ['192.168.99.164', ['135', '139', '445', '3389', '5800', '5900']],
        ['192.168.228.211', ['80']],
        ['192.168.171.74', ['135', '139', '445', '3389', '5800', '5900']]]

ports = sorted(set([int(port) for _, open_ports in data for port in open_ports]))

my_table = PrettyTable()
header = ['ip']
header.extend(ports)
my_table.field_names = header
for ip_address, open_ports in data:
    row = [ip_address]
    row.extend('X' if str(port) in open_ports else '' for port in ports)
    my_table.add_row(row)

print(my_table)

输出

+-----------------+----+----+----+-----+-----+-----+-----+------+------+------+
|        ip       | 53 | 80 | 88 | 135 | 139 | 389 | 445 | 3389 | 5800 | 5900 |
+-----------------+----+----+----+-----+-----+-----+-----+------+------+------+
|  192.168.23.78  | X  |    | X  |  X  |  X  |  X  |  X  |  X   |      |      |
|  192.168.27.243 |    |    |    |  X  |  X  |     |  X  |  X   |  X   |  X   |
|  192.168.99.164 |    |    |    |  X  |  X  |     |  X  |  X   |  X   |  X   |
| 192.168.228.211 |    | X  |    |     |     |     |     |      |      |      |
|  192.168.171.74 |    |    |    |  X  |  X  |     |  X  |  X   |  X   |  X   |
+-----------------+----+----+----+-----+-----+-----+-----+------+------+------+

Answer 2

您可以使用numpy和pandas

import pandas as pd
import numpy as np

table = [['192.168.23.78', ['53', '88', '135', '139', '389', '445', '3389']],
         ['192.168.27.243', ['135', '139', '445', '3389', '5800', '5900']],
         ['192.168.99.164', ['135', '139', '445', '3389', '5800', '5900']],
         ['192.168.228.211', ['80']],
         ['192.168.171.74', ['135', '139', '445', '3389', '5800', '5900']]]

# Collect the ip_addresses
ip_addresses = [el[0] for el in table]

# Collect the column names. Temporarily convert to integers to sort them properly
columns = sorted(np.unique([c for el in table for c in el[1]]), key = lambda x: int(x))


# Initialize numpy matrix to hold strings
table_matrix = np.zeros((len(ip_addresses), len(columns)), str)

for row in table:
    # Get the row index of the IP address
    for i, ip in enumerate(ip_addresses):
        if row[0] == ip:
            rdx = i
    # Check which columns have values in the row that corresponds to the IP address    
    for c in row[1]:
        for j, col in enumerate(columns):
            # Add an X if the row has that column
            if c == col:
                table_matrix[rdx, j] = 'X'

# Create DataFrame
df = pd.DataFrame(table_matrix, index = ip_addresses, columns = columns)

输出：

Out[24]: 
                53 80 88 135 139 389 445 3389 5800 5900
192.168.23.78    X     X   X   X   X   X    X          
192.168.27.243             X   X       X    X    X    X
192.168.99.164             X   X       X    X    X    X
192.168.228.211     X                                  
192.168.171.74             X   X       X    X    X    X

Python 3：如何从嵌套列表生成表作为输入

2 个答案: