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. """ # 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. Use the provided statistics to calculate default parameters and to process user 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