small changes

code/Attack/AttackParameters.py

@@ -56,4 +56,4 @@ class ParameterTypes(Enum):
     TYPE_PACKET_POSITION = 7  # used to derive timestamp from parameter INJECT_AFTER_PACKET
 
     # Aidmar
-    TYPE_URI = 8
+    TYPE_DOMAIN = 8

code/Attack/BaseAttack.py

@@ -1,5 +1,5 @@
 # Aidmar
-#import validators # TO-DO: it needs to be added to required packages
+from scapy.layers.inet import Ether
 
 import ipaddress
 import os
@@ -17,6 +17,7 @@ from Attack.AttackParameters import Parameter
 from Attack.AttackParameters import ParameterTypes
 
 
+
 class BaseAttack(metaclass=ABCMeta):
     """
     Abstract base class for all attack classes. Provides basic functionalities, like parameter validation.
@@ -213,14 +214,15 @@ class BaseAttack(metaclass=ABCMeta):
 
     # Aidmar
     @staticmethod
-    def _is_uri(uri: str):
+    def _is_domain(val: str):
         """
         Verifies that the given string is a valid URI.
 
         :param uri: The URI as string.
         :return: True if URI is valid, otherwise False.
         """
-        return validators.url(uri)
+        domain = re.match('^(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\(\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+$', val)
+        return (domain is not None)
 
 
     #########################################
@@ -294,9 +296,9 @@ class BaseAttack(metaclass=ABCMeta):
                 is_valid = True
                 param_name = Parameter.INJECT_AT_TIMESTAMP
                 value = (ts / 1000000)  # convert microseconds from getTimestampMuSec into seconds
-        # Aidmar - TO-DO
-        elif param_type == ParameterTypes.TYPE_URI:
-            is_valid = True#self._is_uri(value)
+        # Aidmar
+        elif param_type == ParameterTypes.TYPE_DOMAIN:
+            is_valid = self._is_domain(value)
 
         # add value iff validation was successful
         if is_valid:
@@ -482,6 +484,13 @@ class BaseAttack(metaclass=ABCMeta):
 
     # Aidmar
     def get_reply_delay(self, ip_dst):
+        """
+           Gets the minimum and the maximum reply delay for all the connections of a specific IP.
+           :param ip_dst: The IP to reterive its reply delay.
+           :return minDelay: minimum delay
+           :return maxDelay: maximum delay
+
+           """
         minDelay = self.statistics.process_db_query(
             "SELECT minDelay FROM conv_statistics WHERE ipAddressB='" + ip_dst + "' LIMIT 1")
         maxDelay = self.statistics.process_db_query(
@@ -493,4 +502,45 @@ class BaseAttack(metaclass=ABCMeta):
             maxDelay = np.median(allMaxDelays)
         minDelay = int(minDelay) * 10 ** -6  # convert from micro to seconds
         maxDelay = int(maxDelay) * 10 ** -6
-        return minDelay,maxDelay
+        return minDelay,maxDelay
+
+    # Group the packets in conversations
+    def packetsToConvs(self,exploit_raw_packets):
+        """
+           Classifies a bunch of packets to conversations groups. A conversation is a set of packets go between host A (IP,port)
+           to host B (IP,port)
+           :param exploit_raw_packets: A set of packets contains several conversations.
+           :return conversations: A set of arrays, each array contains the packet of specifc conversation
+           :return orderList_conversations: An array contains the conversations ids (IP_A,port_A, IP_b,port_B) in the order
+           they appeared in the original packets.
+           """
+        conversations = {}
+        orderList_conversations = []
+        for pkt_num, pkt in enumerate(exploit_raw_packets):
+            eth_frame = Ether(pkt[0])
+
+            ip_pkt = eth_frame.payload
+            ip_dst = ip_pkt.getfieldval("dst")
+            ip_src = ip_pkt.getfieldval("src")
+
+            tcp_pkt = ip_pkt.payload
+            port_dst = tcp_pkt.getfieldval("dport")
+            port_src = tcp_pkt.getfieldval("sport")
+
+            conv_req = (ip_src, port_src, ip_dst, port_dst)
+            conv_rep = (ip_dst, port_dst, ip_src, port_src)
+            if conv_req not in conversations and conv_rep not in conversations:
+                pktList = [pkt]
+                conversations[conv_req] = pktList
+                # Order list of conv
+                orderList_conversations.append(conv_req)
+            else:
+                if conv_req in conversations:
+                    pktList = conversations[conv_req]
+                    pktList.append(pkt)
+                    conversations[conv_req] = pktList
+                else:
+                    pktList = conversations[conv_rep]
+                    pktList.append(pkt)
+                    conversations[conv_rep] = pktList
+        return (conversations, orderList_conversations)

code/Attack/JoomlaRegPrivExploit.py

@@ -55,8 +55,8 @@ class JoomlaRegPrivExploit(BaseAttack.BaseAttack):
             Param.IP_SOURCE: ParameterTypes.TYPE_IP_ADDRESS,
             Param.MAC_DESTINATION: ParameterTypes.TYPE_MAC_ADDRESS,
             Param.IP_DESTINATION: ParameterTypes.TYPE_IP_ADDRESS,
-            Param.TARGET_HOST: ParameterTypes.TYPE_URI,
-            Param.TARGET_URI: ParameterTypes.TYPE_URI,
+            Param.TARGET_HOST: ParameterTypes.TYPE_DOMAIN,
+            #Param.TARGET_URI: ParameterTypes.TYPE_URI,
             Param.INJECT_AT_TIMESTAMP: ParameterTypes.TYPE_FLOAT,
             Param.INJECT_AFTER_PACKET: ParameterTypes.TYPE_PACKET_POSITION,
             Param.PACKETS_PER_SECOND: ParameterTypes.TYPE_FLOAT
@@ -69,7 +69,7 @@ class JoomlaRegPrivExploit(BaseAttack.BaseAttack):
             most_used_ip_address = most_used_ip_address[0]
         self.add_param_value(Param.IP_SOURCE, most_used_ip_address)
         self.add_param_value(Param.MAC_SOURCE, self.statistics.get_mac_address(most_used_ip_address))
-        self.add_param_value(Param.TARGET_URI, '/')
+        #self.add_param_value(Param.TARGET_URI, '/')
         self.add_param_value(Param.TARGET_HOST, "www.hackme.com")
         self.add_param_value(Param.INJECT_AFTER_PACKET, randint(0, self.statistics.get_packet_count()))
         self.add_param_value(Param.PACKETS_PER_SECOND,self.maxDefaultPPS)
@@ -121,7 +121,7 @@ class JoomlaRegPrivExploit(BaseAttack.BaseAttack):
         mac_destination = self.get_param_value(Param.MAC_DESTINATION)
         ip_destination = self.get_param_value(Param.IP_DESTINATION)
         target_host = self.get_param_value(Param.TARGET_HOST)
-        target_uri = self.get_param_value(Param.TARGET_URI)
+        target_uri = "/" #self.get_param_value(Param.TARGET_URI)
 
         # Check ip.src == ip.dst
         if ip_source == ip_destination:
@@ -132,6 +132,21 @@ class JoomlaRegPrivExploit(BaseAttack.BaseAttack):
         path_attack_pcap = None
         minDelay, maxDelay = self.get_reply_delay(ip_destination)
 
+        # Set TTL based on TTL distribution of IP address
+        source_ttl_dist = self.statistics.get_ttl_distribution(ip_source)
+        if len(source_ttl_dist) > 0:
+            source_ttl_prob_dict = Lea.fromValFreqsDict(source_ttl_dist)
+            source_ttl_value = source_ttl_prob_dict.random()
+        else:
+            source_ttl_value = self.statistics.process_db_query("most_used(ttlValue)")
+
+        destination_ttl_dist = self.statistics.get_ttl_distribution(ip_destination)
+        if len(destination_ttl_dist) > 0:
+            destination_ttl_prob_dict = Lea.fromValFreqsDict(destination_ttl_dist)
+            destination_ttl_value = destination_ttl_prob_dict.random()
+        else:
+            destination_ttl_value = self.statistics.process_db_query("most_used(ttlValue)")
+
         # Inject Joomla_registration_privesc
         # Read joomla_registration_privesc pcap file
         orig_ip_dst = None
@@ -179,6 +194,7 @@ class JoomlaRegPrivExploit(BaseAttack.BaseAttack):
                 # IP
                 ip_pkt.setfieldval("src", ip_source)
                 ip_pkt.setfieldval("dst", ip_destination)
+                ip_pkt.setfieldval("ttl", source_ttl_value)
                 # TCP
                 tcp_pkt.setfieldval("sport",port_source)
 
@@ -204,8 +220,7 @@ class JoomlaRegPrivExploit(BaseAttack.BaseAttack):
                 new_pkt.time = timestamp_next_pkt
 
                 maxdelay = randomdelay.random()
-                pps = self.minDefaultPPS if getIntervalPPS(complement_interval_pps, timestamp_next_pkt) is None else max(
-                    getIntervalPPS(complement_interval_pps, timestamp_next_pkt), self.minDefaultPPS)
+                pps = max(getIntervalPPS(complement_interval_pps, timestamp_next_pkt), self.minDefaultPPS)
                 timestamp_next_pkt = update_timestamp(timestamp_next_pkt, pps, maxdelay)
 
             # Reply: Victim --> attacker
@@ -216,6 +231,7 @@ class JoomlaRegPrivExploit(BaseAttack.BaseAttack):
                 # IP
                 ip_pkt.setfieldval("src", ip_destination)
                 ip_pkt.setfieldval("dst", ip_source)
+                ip_pkt.setfieldval("ttl", destination_ttl_value)
                 # TCP
                 tcp_pkt.setfieldval("dport", port_source)
 

code/Attack/PortscanAttack.py

@@ -228,12 +228,20 @@ class PortscanAttack(BaseAttack.BaseAttack):
         # mss = self.statistics.get_mss(ip_destination)
 
         # Set TTL based on TTL distribution of IP address
-        ttl_dist = self.statistics.get_ttl_distribution(ip_source)
-        if len(ttl_dist) > 0:
-            ttl_prob_dict = Lea.fromValFreqsDict(ttl_dist)
-            ttl_value = ttl_prob_dict.random()
+        # Aidmar - create two ttl for source and destination
+        source_ttl_dist = self.statistics.get_ttl_distribution(ip_source)
+        if len(source_ttl_dist) > 0:
+            source_ttl_prob_dict = Lea.fromValFreqsDict(source_ttl_dist)
+            source_ttl_value = source_ttl_prob_dict.random()
         else:
-            ttl_value = self.statistics.process_db_query("most_used(ttlValue)")
+            source_ttl_value = self.statistics.process_db_query("most_used(ttlValue)")
+
+        destination_ttl_dist = self.statistics.get_ttl_distribution(ip_destination)
+        if len(destination_ttl_dist) > 0:
+            destination_ttl_prob_dict = Lea.fromValFreqsDict(destination_ttl_dist)
+            destination_ttl_value = destination_ttl_prob_dict.random()
+        else:
+            destination_ttl_value = self.statistics.process_db_query("most_used(ttlValue)")
 
         # Aidmar
         A_B_packets = []
@@ -247,7 +255,7 @@ class PortscanAttack(BaseAttack.BaseAttack):
 
             # 1) Build request package
             request_ether = Ether(src=mac_source, dst=mac_destination)
-            request_ip = IP(src=ip_source, dst=ip_destination, ttl=ttl_value)
+            request_ip = IP(src=ip_source, dst=ip_destination, ttl=source_ttl_value)
 
             # Aidmar - random src port for each packet
             sport = randint(1, 65535)
@@ -267,7 +275,7 @@ class PortscanAttack(BaseAttack.BaseAttack):
             # 2) Build reply (for open ports) package
             if dport in ports_open:  # destination port is OPEN
                 reply_ether = Ether(src=mac_destination, dst=mac_source)
-                reply_ip = IP(src=ip_destination, dst=ip_source, flags='DF')
+                reply_ip = IP(src=ip_destination, dst=ip_source, ttl=destination_ttl_value, flags='DF')
                 #if mss_dst is None:
                 #   reply_tcp = TCP(sport=dport, dport=sport, seq=0, ack=1, flags='SA', window=29200)
                 #else:
@@ -317,7 +325,8 @@ class PortscanAttack(BaseAttack.BaseAttack):
             packets.append(request)
 
             # Aidmar
-            pps = self.minDefaultPPS if getIntervalPPS(complement_interval_pps, timestamp_next_pkt) is None else max(getIntervalPPS(complement_interval_pps, timestamp_next_pkt),self.minDefaultPPS) # avoid case of pps = 0
+            #pps = self.minDefaultPPS if getIntervalPPS(complement_interval_pps, timestamp_next_pkt) is None else max(getIntervalPPS(complement_interval_pps, timestamp_next_pkt),self.minDefaultPPS) # avoid case of pps = 0
+            pps = max(getIntervalPPS(complement_interval_pps, timestamp_next_pkt),self.minDefaultPPS)
             timestamp_next_pkt = update_timestamp(timestamp_next_pkt, pps, maxDelay)
 
         # Aidmar - In case all requests are already sent, send all replies and confirms

code/ID2TLib/Statistics.py

@@ -774,9 +774,9 @@ class Statistics:
                 graphy.append(row[1])
 
             plt.autoscale(enable=True, axis='both')
-            plt.title("IP New Values Distribution")
+            plt.title("IP Novelity Distribution")
             plt.xlabel('Timestamp')
-            plt.ylabel('New values count')
+            plt.ylabel('Novel values count')
             plt.xlim([0, len(graphx)])
             plt.grid(True)
             width = 0.1
@@ -791,7 +791,7 @@ class Statistics:
             plt.locator_params(axis='x', nbins=20)
 
             plt.bar(x, graphy, width, align='center', linewidth=1, color='red', edgecolor='red')
-            out = self.pcap_filepath.replace('.pcap', '_plot-interval-new-ip-dist' + file_ending)
+            out = self.pcap_filepath.replace('.pcap', '_plot-interval-novel-ip-dist' + file_ending)
             plt.savefig(out, dpi=500)
 
             print("IP Standard Deviation:")
@@ -810,9 +810,9 @@ class Statistics:
                     graphy.append(row[1])
 
                 plt.autoscale(enable=True, axis='both')
-                plt.title("TTL New Values Distribution")
+                plt.title("TTL Novelity Distribution")
                 plt.xlabel('Timestamp')
-                plt.ylabel('New values count')
+                plt.ylabel('Novel values count')
                 plt.xlim([0, len(graphx)])
                 plt.grid(True)
                 width = 0.1
@@ -827,7 +827,7 @@ class Statistics:
                 plt.locator_params(axis='x', nbins=20)
 
                 plt.bar(x, graphy, width, align='center', linewidth=1, color='red', edgecolor='red')
-                out = self.pcap_filepath.replace('.pcap', '_plot-interval-new-ttl-dist' + file_ending)
+                out = self.pcap_filepath.replace('.pcap', '_plot-interval-novel-ttl-dist' + file_ending)
                 plt.savefig(out, dpi=500)
 
                 print("TTL Standard Deviation:")
@@ -847,9 +847,9 @@ class Statistics:
                 graphy.append(row[1])
 
             plt.autoscale(enable=True, axis='both')
-            plt.title("ToS New Values Distribution")
+            plt.title("ToS Novelity Distribution")
             plt.xlabel('Timestamp')
-            plt.ylabel('New values count')
+            plt.ylabel('Novel values count')
             plt.xlim([0, len(graphx)])
             plt.grid(True)
             width = 0.1
@@ -864,7 +864,7 @@ class Statistics:
             plt.locator_params(axis='x', nbins=20)
 
             plt.bar(x, graphy, width, align='center', linewidth=1, color='red', edgecolor='red')
-            out = self.pcap_filepath.replace('.pcap', '_plot-interval-new-tos-dist' + file_ending)
+            out = self.pcap_filepath.replace('.pcap', '_plot-interval-novel-tos-dist' + file_ending)
             plt.savefig(out, dpi=500)
 
             print("ToS Standard Deviation:")
@@ -884,9 +884,9 @@ class Statistics:
                     graphy.append(row[1])
 
                 plt.autoscale(enable=True, axis='both')
-                plt.title("Window Size New Values Distribution")
+                plt.title("Window Size Novelity Distribution")
                 plt.xlabel('Timestamp')
-                plt.ylabel('New values count')
+                plt.ylabel('Novel values count')
                 plt.xlim([0, len(graphx)])
                 plt.grid(True)
                 width = 0.1
@@ -901,7 +901,7 @@ class Statistics:
                 plt.locator_params(axis='x', nbins=20)
 
                 plt.bar(x, graphy, width, align='center', linewidth=1, color='red', edgecolor='red')
-                out = self.pcap_filepath.replace('.pcap', '_plot-interval-new-win-size-dist' + file_ending)
+                out = self.pcap_filepath.replace('.pcap', '_plot-interval-novel-win-size-dist' + file_ending)
                 plt.savefig(out, dpi=500)
 
                 # Calculate Standart Deviation
@@ -924,9 +924,9 @@ class Statistics:
                     graphy.append(row[1])
 
                 plt.autoscale(enable=True, axis='both')
-                plt.title("MSS New Values Distribution")
+                plt.title("MSS Novelity Distribution")
                 plt.xlabel('Timestamp')
-                plt.ylabel('New values count')
+                plt.ylabel('Novel values count')
                 plt.xlim([0, len(graphx)])
                 plt.grid(True)
                 width = 0.1
@@ -941,7 +941,7 @@ class Statistics:
                 plt.locator_params(axis='x', nbins=20)
 
                 plt.bar(x, graphy, width, align='center', linewidth=1, color='red', edgecolor='red')
-                out = self.pcap_filepath.replace('.pcap', '_plot-interval-new-mss-dist' + file_ending)
+                out = self.pcap_filepath.replace('.pcap', '_plot-interval-novel-mss-dist' + file_ending)
                 plt.savefig(out, dpi=500)
 
                 # Calculate Standart Deviation
@@ -976,7 +976,7 @@ class Statistics:
      # Aidmar
     def calculate_complement_packet_rates(self, pps):
         """
-        Calculates the complement packet rates of the background traffic packet rates per interval.
+        Calculates the complement packet rates of the background traffic packet rates for each interval.
         Then normalize it to maximum boundary, which is the input parameter pps
 
         :return: normalized packet rates for each time interval.

code/capture_1.pcap.stat

@@ -1,26 +0,0 @@
-====================== 
-PCAP file information 
-====================== 
-Pcap file:	capture_1.pcap
-#Packets:	23211 packets
-Capture length:	32.503 seconds
-Capture start:	2017-06-12 15:40:36.142820
-Capture end:	2017-06-12 15:47:08.645789
-====================== 
-General statistics 
-====================== 
-Avg. packet rate:	714.1194 packets/sec
-Avg. packet size:	0.0 kbytes
-Avg. packets sent:	321.0 packets
-Avg. bandwidth in:	57.2475 kbit/s
-Avg. bandwidth out:	57.2475 kbit/s
-====================== 
-Tests statistics 
-====================== 
-Payload ratio:	0.0 %
-Incorrect TCP checksum ratio:	0 %
-Avg. new IP:	0.72 
-Avg. new TTL:	0.27 
-Avg. new WinSize:	0.1 
-Avg. new ToS:	0.04 
-Avg. new MSS:	0.04 

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