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pcap to csv pipeline
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3
.gitignore
vendored
3
.gitignore
vendored
@ -1 +1,4 @@
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*.pcap*
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*.gz*
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*.csv*
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*.tsv*
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@ -6,10 +6,12 @@
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- maybe GRE for VPN usage?
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- L3 - IPv6 is only around 10%, let's drop it
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- Selection (of fields):
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- Timestamp - note: capture window is from 0500-0515 UTC
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- Timestamp
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- capture window is from 0500-0515 UTC
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- nanosecond precision, use DateTime64 data type in ClickHouse
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- IP
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- addresses - src, dst
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- protocol - 6 (TCP) or 17 (UDP). cld go for boolean to save space
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- TCP
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- protocol - TCP or UDP. cld go for boolean in ClickHouse to save space
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- TCP/UDP
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- ports - sport, dport
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- Packet size - in bytes - could exclude L2?
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- Packet size - in bytes
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148
preprocessing/pcap_processor.py
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148
preprocessing/pcap_processor.py
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@ -0,0 +1,148 @@
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from argparse import ArgumentParser
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from datetime import datetime, timezone
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import csv
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from scapy.packet import Packet
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from scapy.utils import PcapReader
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from scapy.layers.inet import IP, TCP, UDP
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dbg_print = lambda *x: DEBUG and print(f"[DEBUG] {x}")
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def pkt_filter(pkt: Packet) -> bool:
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"""filter to include/exclude a packet"""
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try:
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assert IP in pkt
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assert pkt[IP].version == 4
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assert (TCP in pkt) or (UDP in pkt)
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return True
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except AssertionError:
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return False
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def pkt_extract(pkt: Packet) -> list:
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"""extract select attributes from a packet"""
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l4_proto = None
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if TCP in pkt:
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l4_proto = TCP
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elif UDP in pkt:
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l4_proto = UDP
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pkt_attrs = [
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float(pkt.time),
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pkt.getlayer(l4_proto).name,
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pkt[IP].src,
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pkt[IP].dst,
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pkt[l4_proto].sport,
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pkt[l4_proto].dport,
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len(pkt),
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]
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pkt_time_str = str(datetime.fromtimestamp(float(pkt.time), timezone.utc))
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dbg_print(
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"[{}] {} {}:{} -> {}:{} - {} bytes".format(
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pkt_time_str,
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pkt.getlayer(l4_proto).name,
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pkt[IP].src,
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pkt[l4_proto].sport,
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pkt[IP].dst,
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pkt[l4_proto].dport,
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len(pkt),
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)
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)
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return pkt_attrs
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def prep_csv(out_file: str):
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with open(out_file, "w", newline="") as csvfile:
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writer = csv.writer(csvfile)
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# header row
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writer.writerow(
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[
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"time",
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"l4_proto",
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"src_addr",
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"dst_addr",
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"src_port",
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"dst_port",
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"pkt_len",
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]
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)
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def pkts_write_csv(pkts: list, out_file: str):
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with open(out_file, "a", newline="") as csvfile:
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writer = csv.writer(csvfile)
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writer.writerows(pkts)
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if __name__ == "__main__":
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argp = ArgumentParser()
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argp.add_argument("-f", "--pcap_file", required=True, dest="_pcap")
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argp.add_argument("-o", "--out_file", required=False, dest="_out")
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argp.add_argument(
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"-x",
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"--sample",
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required=False,
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default=False,
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dest="_sample",
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action="store_true",
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)
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argp.add_argument(
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"-s",
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"--stream",
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required=False,
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default=False,
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dest="_stream",
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action="store_true",
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)
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argp.add_argument(
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"-d",
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"--debug",
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required=False,
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default=False,
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dest="_debug",
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action="store_true",
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)
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args = argp.parse_args()
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pcap_file = args._pcap
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out_file = args._out
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streaming = args._stream
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sample = args._sample
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DEBUG = args._debug
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sample_size = 1000000
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batch_size = 100000
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pcap_rdr = PcapReader(pcap_file)
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if not streaming:
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assert args._out and args._out != ""
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prep_csv(out_file)
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pkts = []
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for idx, pkt in enumerate(pcap_rdr):
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# filter packets
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if not pkt_filter(pkt):
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continue
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if not streaming:
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# write to file
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pkts.append(pkt_extract(pkt))
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if sample and idx > sample_size:
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break
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if idx > 0 and idx % batch_size == 0:
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pkts_write_csv(pkts, out_file)
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pkts = []
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else:
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# direct streaming to kafka goes here
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pass
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# flush remaining
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if not streaming and len(pkts) > 0:
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pkts_write_csv(pkts, out_file)
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601819
preprocessing/sample_output.csv
Normal file
601819
preprocessing/sample_output.csv
Normal file
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