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pic_carver.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Sept 7 18:37:30 2020
@author: edoardottt
"""
import re
import zlib
import cv2
from scapy.all import *
pictures_directory = "INSERT-PIC-DIR"
faces_directory = "INSERT-FACES-DIR"
pcap_file = "bhp.pcap"
def face_detect(path, file_name):
img = cv2.imread(path)
cascade = cv2.CascadeClassifier("haarcascade_frontalface_alt.xml")
rects = cascade.detectMultiScale(img, 1.3, 4, cv2.cv.CV_HAAR_SCALE_IMAGE, (20, 20))
if len(rects) == 0:
return False
rects[:, 2:] += rects[:, :2]
# 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("{}{}-{}".format(faces_directory, pcap_file, file_name), img)
return True
def get_http_headers(http_payload):
try:
# split the headers off it is HTTP traffic
headers_raw = http_payload[: http_payload.index("\r\n\r\n") + 2]
# break out the headers
headers = dict(re.findall(r"(?P<name>.*?): (?P<value>.*?)\r\n", headers_raw))
except:
return None
if "Content-Type" not in headers:
return None
return headers
def extract_image(headers, http_payload):
image = None
image_type = None
try:
if "image" in headers["Content-Type"]:
# grab the image type and image body
image_type = headers["Content-Type"].split("/")[1]
image = http_payload[http_payload.index("\r\n\r\n") + 4 :]
# if we detect compression decompress the image
try:
if "Content-Encoding" in headers.keys():
if headers["Content-Encoding"] == "gzip":
image = zlib.decompress(image, 16 + zlib.MAX_WBITS)
elif headers["Content-Encoding"] == "deflate":
image = zlib.decompress(image)
except:
pass
except:
return None, None
return image, image_type
def http_assembler(pcap_file):
carved_images = 0
faces_detected = 0
a = rdpcap(pcap_file)
sessions = a.sessions()
for session in sessions:
http_payload = ""
for packet in sessions[session]:
try:
if packet[TCP].dport == 80 or packet[TCP].sport == 80:
# reassemble the stream
http_payload += str(packet[TCP].payload)
except:
pass
headers = get_http_headers(http_payload)
if headers is None:
continue
image, image_type = extract_image(headers, http_payload)
if image is not None and image_type is not None:
# store the image
file_name = "{}-pic_carver_{}.{}".format(
pcap_file, carved_images, image_type
)
fd = open("{}/{}".format(pictures_directory, file_name), "wb")
fd.write(image)
fd.close()
carved_images += 1
# now attempt face detection
try:
result = face_detect(
"{}/{}".format(pictures_directory, file_name), file_name
)
if result is True:
faces_detected += 1
except:
pass
return carved_images, faces_detected
carved_images, faces_detected = http_assembler(pcap_file)
print("Extracted: {} images".format(carved_images))
print("Detected: {} images".format(faces_detected))