import logging from random import randint, uniform, 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.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)) 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) num_attackers = len(ip_source_list) # 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 is not None and not 0: 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) 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 timestamp_prv_reply, timestamp_confirm = 0, 0 minDelay, maxDelay = self.get_reply_delay(ip_destination) victim_buffer = self.get_param_value(Param.VICTIM_BUFFER) 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 total_pkt_num = 0 # For each attacker, generate his own packets, then merge all packets for attacker in range(num_attackers): # Timestamp timestamp_next_pkt = self.get_param_value(Param.INJECT_AT_TIMESTAMP) attack_ends_time = timestamp_next_pkt + attack_duration 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): # Stop the attack when it exceeds the duration if timestamp_next_pkt > attack_ends_time: break # 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) # Random win size for each packet 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) total_pkt_num +=1 # Build reply package 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 total_pkt_num += 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 total_pkt_num <= 2 : 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 total_pkt_num , path_attack_pcap