ID2T-toolkit-BotnetTraffic/code/Attack/DDoSAttack.py

import logging
from random import randint, uniform, choice #Aidmar choice

from lea import Lea
from scipy.stats import gamma

from Attack import BaseAttack
from Attack.AttackParameters import Parameter as Param
from Attack.AttackParameters import ParameterTypes

logging.getLogger("scapy.runtime").setLevel(logging.ERROR)
# noinspection PyPep8
from scapy.layers.inet import IP, Ether, TCP, RandShort
from collections import deque


class DDoSAttack(BaseAttack.BaseAttack):
    def __init__(self):
        """
        Creates a new instance of the DDoS attack.
<<<<<<< HEAD

=======
>>>>>>> 48c729f6dbfeb1e2670c762729090a48d5f0b490
        """
        # Initialize attack
        super(DDoSAttack, self).__init__("DDoS Attack", "Injects a DDoS attack'",
                                        "Resource Exhaustion")

        # Define allowed parameters and their type
        self.supported_params = {
            Param.IP_SOURCE: ParameterTypes.TYPE_IP_ADDRESS,
            Param.MAC_SOURCE: ParameterTypes.TYPE_MAC_ADDRESS,
            Param.PORT_SOURCE: ParameterTypes.TYPE_PORT,
            Param.IP_DESTINATION: ParameterTypes.TYPE_IP_ADDRESS,
            Param.MAC_DESTINATION: ParameterTypes.TYPE_MAC_ADDRESS,
            Param.PORT_DESTINATION: ParameterTypes.TYPE_PORT,
            Param.INJECT_AT_TIMESTAMP: ParameterTypes.TYPE_FLOAT,
            Param.INJECT_AFTER_PACKET: ParameterTypes.TYPE_PACKET_POSITION,
            Param.PACKETS_PER_SECOND: ParameterTypes.TYPE_FLOAT,
            Param.PACKETS_LIMIT: ParameterTypes.TYPE_INTEGER_POSITIVE,
            Param.NUMBER_ATTACKERS: ParameterTypes.TYPE_INTEGER_POSITIVE,
            Param.ATTACK_DURATION: ParameterTypes.TYPE_INTEGER_POSITIVE,
            Param.VICTIM_BUFFER: ParameterTypes.TYPE_INTEGER_POSITIVE
        }

    def init_params(self):
        """
        Initialize the parameters of this attack using the user supplied command line parameters.
<<<<<<< HEAD
        Use the provided statistics to calculate default parameters and to process user
=======
        Use the provided statistics to calculate default parameters and to process user 
>>>>>>> 48c729f6dbfeb1e2670c762729090a48d5f0b490
        supplied queries.

        :param statistics: Reference to a statistics object.
        """
        # PARAMETERS: initialize with default values
        # (values are overwritten if user specifies them)
        self.add_param_value(Param.INJECT_AFTER_PACKET, randint(0, self.statistics.get_packet_count()))
        # attacker configuration
        num_attackers = randint(1, 16)
        # The most used IP class in background traffic
        most_used_ip_class = self.statistics.process_db_query("most_used(ipClass)")

        self.add_param_value(Param.IP_SOURCE, self.generate_random_ipv4_address(most_used_ip_class, num_attackers))
        self.add_param_value(Param.MAC_SOURCE, self.generate_random_mac_address(num_attackers))
        self.add_param_value(Param.PORT_SOURCE, str(RandShort()))
        self.add_param_value(Param.PACKETS_PER_SECOND, 0)
        self.add_param_value(Param.ATTACK_DURATION, randint(5,30))

        # victim configuration
        random_ip_address = self.statistics.get_random_ip_address()
        self.add_param_value(Param.IP_DESTINATION, random_ip_address)
        destination_mac = self.statistics.get_mac_address(random_ip_address)
        if isinstance(destination_mac, list) and len(destination_mac) == 0:
            destination_mac = self.generate_random_mac_address()
        self.add_param_value(Param.MAC_DESTINATION, destination_mac)
        self.add_param_value(Param.VICTIM_BUFFER, randint(1000,10000))
        self.add_param_value(Param.PACKETS_LIMIT, 0)

    def generate_attack_pcap(self):
        def update_timestamp(timestamp, pps, delay=0):
            """
            Calculates the next timestamp to be used based on the packet per second rate (pps) and the maximum delay.

            :return: Timestamp to be used for the next packet.
            """
            if delay == 0:
                # Calculate the request timestamp
                # A distribution to imitate the bursty behavior of traffic
                randomdelay = Lea.fromValFreqsDict({1 / pps: 70, 2 / pps: 20, 5 / pps: 7, 10 / pps: 3})
                return timestamp + uniform(1 / pps, randomdelay.random())
            else:
                # Calculate the reply timestamp
                randomdelay = Lea.fromValFreqsDict({2 * delay: 70, 3 * delay: 20, 5 * delay: 7, 10 * delay: 3})
                return timestamp + uniform(1 / pps + delay, 1 / pps + randomdelay.random())

        def get_nth_random_element(*element_list):
            """
            Returns the n-th element of every list from an arbitrary number of given lists.
            For example, list1 contains IP addresses, list 2 contains MAC addresses. Use of this function ensures that
            the n-th IP address uses always the n-th MAC address.
            :param element_list: An arbitrary number of lists.
            :return: A tuple of the n-th element of every list.
            """
            range_max = min([len(x) for x in element_list])
            if range_max > 0: range_max -= 1
            n = randint(0, range_max)
            return tuple(x[n] for x in element_list)

        def index_increment(number: int, max: int):
            if number + 1 < max:
                return number + 1
            else:
                return 0

        def getIntervalPPS(complement_interval_pps, timestamp):
            """
            Gets the packet rate (pps) for a specific time interval.
            :param complement_interval_pps: an array of tuples (the last timestamp in the interval, the packet rate in the crresponding interval).
            :param timestamp: the timestamp at which the packet rate is required.
            :return: the corresponding packet rate (pps) .
            """
            for row in complement_interval_pps:
                if timestamp <= row[0]:
                    return row[1]
            # In case the timestamp > capture max timestamp
            return complement_interval_pps[-1][1]

        def get_attacker_config(ipAddress: str):
            """
            Returns the attacker configuration depending on the IP address, this includes the port for the next
            attacking packet and the previously used (fixed) TTL value.
            :param ipAddress: The IP address of the attacker
            :return: A tuple consisting of (port, ttlValue)
            """
            # Determine port
            port = attacker_port_mapping.get(ipAddress)
            if port is not None:  # use next port
                next_port = attacker_port_mapping.get(ipAddress) + 1
                if next_port > (2 ** 16 - 1):
                    next_port = 1
            else:  # generate starting port
                next_port = RandShort()
            attacker_port_mapping[ipAddress] = next_port
            # Determine TTL value
            ttl = attacker_ttl_mapping.get(ipAddress)
            if ttl is None:  # determine TTL value
                is_invalid = True
                pos = ip_source_list.index(ipAddress)
                pos_max = len(gd)
                while is_invalid:
                    ttl = int(round(gd[pos]))
                    if 0 < ttl < 256:  # validity check
                        is_invalid = False
                    else:
                        pos = index_increment(pos, pos_max)
                attacker_ttl_mapping[ipAddress] = ttl
            # return port and TTL
            return next_port, ttl

        BUFFER_SIZE = 1000

        # Determine source IP and MAC address
        num_attackers = self.get_param_value(Param.NUMBER_ATTACKERS)
        if num_attackers is not None:  # user supplied Param.NUMBER_ATTACKERS
            # The most used IP class in background traffic
            most_used_ip_class = self.statistics.process_db_query("most_used(ipClass)")
            # Create random attackers based on user input Param.NUMBER_ATTACKERS
            ip_source_list = self.generate_random_ipv4_address(most_used_ip_class, num_attackers)
            mac_source_list = self.generate_random_mac_address(num_attackers)
        else:  # user did not supply Param.NUMBER_ATTACKS
            # use default values for IP_SOURCE/MAC_SOURCE or overwritten values
            # if user supplied any values for those params
            ip_source_list = self.get_param_value(Param.IP_SOURCE)
            mac_source_list = self.get_param_value(Param.MAC_SOURCE)

        # Initialize parameters
        packets = deque(maxlen=BUFFER_SIZE)
        port_source_list = self.get_param_value(Param.PORT_SOURCE)
        mac_destination = self.get_param_value(Param.MAC_DESTINATION)
        ip_destination = self.get_param_value(Param.IP_DESTINATION)


        most_used_ip_address = self.statistics.get_most_used_ip_address()
        pps = self.get_param_value(Param.PACKETS_PER_SECOND)
        if pps == 0:
            result = self.statistics.process_db_query("SELECT MAX(maxPktRate) FROM ip_statistics WHERE ipAddress='"+ip_destination+"';")
            if result:
                pps = num_attackers * result
            else:
                result = self.statistics.process_db_query("SELECT MAX(maxPktRate) FROM ip_statistics WHERE ipAddress='"+most_used_ip_address+"';")
                pps = num_attackers * result

        # Calculate complement packet rates of the background traffic for each interval
        attacker_pps = pps / num_attackers
        complement_interval_attacker_pps = self.statistics.calculate_complement_packet_rates(attacker_pps)

        # Check ip.src == ip.dst
        self.ip_src_dst_equal_check(ip_source_list, ip_destination)

        # Aidmar
        port_destination = self.get_param_value(Param.PORT_DESTINATION)
        if not port_destination:  # user did not define port_dest
            port_destination = self.statistics.process_db_query(
                "SELECT portNumber FROM ip_ports WHERE portDirection='in' AND ipAddress='" + ip_destination + "' ORDER BY portCount DESC LIMIT 1;")
        if not port_destination:  # no port was retrieved
            port_destination = self.statistics.process_db_query(
                "SELECT portNumber FROM ip_ports WHERE portDirection='in' GROUP BY portNumber ORDER BY SUM(portCount) DESC LIMIT 1;")
        if not port_destination:
            port_destination = max(1, str(RandShort()))

        attacker_port_mapping = {}
        attacker_ttl_mapping = {}

        # Gamma distribution parameters derived from MAWI 13.8G dataset
        alpha, loc, beta = (2.3261710235, -0.188306914406, 44.4853123884)
        gd = gamma.rvs(alpha, loc=loc, scale=beta, size=len(ip_source_list))

        path_attack_pcap = None

        # Aidmar
        timestamp_prv_reply, timestamp_confirm = 0, 0
        minDelay, maxDelay = self.get_reply_delay(ip_destination)
        victim_buffer = self.get_param_value(Param.VICTIM_BUFFER)

        # Aidmar
        pkts_num = self.get_param_value(Param.PACKETS_LIMIT)
        if pkts_num == 0:
            attack_duration = self.get_param_value(Param.ATTACK_DURATION)
            pkts_num = int(pps * attack_duration)

        source_win_sizes = self.statistics.process_db_query(
                "SELECT DISTINCT winSize FROM tcp_win ORDER BY RANDOM() LIMIT "+str(pkts_num)+";")

        destination_win_dist = self.statistics.get_win_distribution(ip_destination)
        if len(destination_win_dist) > 0:
            destination_win_prob_dict = Lea.fromValFreqsDict(destination_win_dist)
            destination_win_value = destination_win_prob_dict.random()
        else:
            destination_win_value = self.statistics.process_db_query("most_used(winSize)")

        # MSS that was used by IP destination in background traffic
        mss_dst = self.statistics.get_most_used_mss(ip_destination)
        if mss_dst is None:
            mss_dst = self.statistics.process_db_query("most_used(mssValue)")

        replies_count = 0

        # Aidmar
        for attacker in range(num_attackers):
            # Timestamp
            timestamp_next_pkt = self.get_param_value(Param.INJECT_AT_TIMESTAMP)
            timestamp_next_pkt = update_timestamp(timestamp_next_pkt, attacker_pps)
            attacker_pkts_num = int(pkts_num / num_attackers) + randint(0,100)
            for pkt_num in range(attacker_pkts_num):
                # Build request package
                # Select one IP address and its corresponding MAC address
                (ip_source, mac_source) = get_nth_random_element(ip_source_list, mac_source_list)
                # Determine source port
                (port_source, ttl_value) = get_attacker_config(ip_source)
                request_ether = Ether(dst=mac_destination, src=mac_source)
                request_ip = IP(src=ip_source, dst=ip_destination, ttl=ttl_value)
                # Aidmar - random win size for each packet
                # request_tcp = TCP(sport=port_source, dport=port_destination, flags='S', ack=0)
                source_win_size = choice(source_win_sizes)
                request_tcp = TCP(sport=port_source, dport=port_destination, flags='S', ack=0, window=source_win_size)

                request = (request_ether / request_ip / request_tcp)
                request.time = timestamp_next_pkt
                # Append request
                packets.append(request)

                # Build reply package
                # Aidmar
                if replies_count <= victim_buffer:
                    reply_ether = Ether(src=mac_destination, dst=mac_source)
                    reply_ip = IP(src=ip_destination, dst=ip_source, flags='DF')
                    reply_tcp = TCP(sport=port_destination, dport=port_source, seq=0, ack=1, flags='SA', window=destination_win_value,options=[('MSS', mss_dst)])
                    reply = (reply_ether / reply_ip / reply_tcp)

                    timestamp_reply = update_timestamp(timestamp_next_pkt, attacker_pps, minDelay)
                    while (timestamp_reply <= timestamp_prv_reply):
                        timestamp_reply = update_timestamp(timestamp_prv_reply, attacker_pps, minDelay)
                    timestamp_prv_reply = timestamp_reply

                    reply.time = timestamp_reply
                    packets.append(reply)
                    replies_count+=1

                attacker_pps = max(getIntervalPPS(complement_interval_attacker_pps, timestamp_next_pkt), (pps/num_attackers)/2)
                timestamp_next_pkt = update_timestamp(timestamp_next_pkt, attacker_pps)

                # Store timestamp of first packet (for attack label)
                if pkt_num == 1:
                    self.attack_start_utime = packets[0].time
                elif pkt_num % BUFFER_SIZE == 0: # every 1000 packets write them to the pcap file (append)
                    last_packet = packets[-1]
                    packets = sorted(packets, key=lambda pkt: pkt.time)
                    path_attack_pcap = self.write_attack_pcap(packets, True, path_attack_pcap)
                    packets = []

        if len(packets) > 0:
            packets = sorted(packets, key=lambda pkt: pkt.time)
            path_attack_pcap = self.write_attack_pcap(packets, True, path_attack_pcap)

        # Store timestamp of last packet
        self.attack_end_utime = last_packet.time

        # return packets sorted by packet time_sec_start
        # pkt_num+1: because pkt_num starts at 0
        return pkt_num + 1, path_attack_pcap