pic_carver.py

import re
import zlib
import cv2

from scapy.all import *

pic_dir = "/root/Desktop/bh_python_book/pics"
faces_dir = "/root/Desktop/bh_python_book/faces"
pcap_file = "http_witp_jpegs.cap"




def get_http_headers(http_payload):
    
    try:
        # split the headers off
        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 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 face_detect(path, file_name):
    img = cv2.imread(path)
    cascade = cv2.CascadeClassifier("haarcascade_frontface_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
    for x1, y1, x2, y2 in rects:
        cv2.rectangle(img, (x1, y1),(x2, y2),(127,255,0),2)
    cv2.imwrite("%s/%s-%s"%(faces_dir, pcap_file, file_name), img)
    return True




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 = "%s-pic_aradaw_%d.%s"%(pcap_file, carved_images, image_type)
            print "%s/%s"%(pic_dir, file_name)
            fd = open("%s/%s"%(pic_dir, file_name),"w+")
            fd.write(image)
            fd.close()
            
            carved_images += 1
            
            #now attempt face detection
            try:
                result = face_detect("%s%s"%(pic_dir, 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: %d images"%carved_images
print "Detected: %d faces"%faces_detected