01 from scapy.all import *
02 from collections import Counter
03 import plotly
04
05 packets = rdpcap("example.pcap")
06
07 lookups=[]
08 for pkt in packets:
09   if IP in pkt:
10     try:
11       if pkt.haslayer(DNS) and pkt.getlayer(DNS).qr == 0:
12         lookup=(pkt.getlayer(DNS).qd.qname).decode("utf-8")
13         lookups.append(lookup)
14     except:
15       pass
16
17 cnt=Counter()
18 for lookup in lookups:
19   cnt[lookup] += 1
20
21 xData=[]
22 yData=[]
23
24 for lookup, count in cnt.most_common():
25   xData.append(lookup)
26   yData.append(count)
27
28 plotly.offline.plot({
29   "data":[plotly.graph_objs.Bar(x=xData, y=yData)] })

01 from scapy.all import *
02 import plotly
03 from datetime import datetime
04 import pandas as pd
05
06 #Read the packets from file
07 packets = rdpcap('example.pcap')
08
09 #Lists to hold packet info
10 pktBytes=[]
11 pktTimes=[]
12
13 #Read each packet and append to the lists.
14 for pkt in packets:
15   if IP in pkt:
16     try:
17       pktBytes.append(pkt[IP].len)
18
19       #First we need to covert Epoch time to a datetime
20       pktTime=datetime.fromtimestamp(pkt.time)
21       #Then convert to a format we like
22       pktTimes.append(pktTime.strftime("%Y-%m-%d %H:%M:%S.%f"))
23
24     except:
25       pass
26
27 #This converts list to series
28 bytes = pd.Series(pktBytes).astype(int)
29
30 #Convert the timestamp list to a pd date_time
31 times = pd.to_datetime(pd.Series(pktTimes).astype(str), errors='coerce')
32
33 #Create the dataframe
34 df = pd.DataFrame({"Bytes": bytes, "Times":times})
35
36 #set the date from a range to an timestamp
37 df = df.set_index('Times')
38
39 #Create a new dataframe of 2 second sums to pass to plotly
40 df2=df.resample('2S').sum()
41 print(df2)
42
43 #Create the graph
44 plotly.offline.plot({
45   "data":[plotly.graph_objs.Scatter(x=df2.index, y=df2['Bytes'])],
46   "layout":plotly.graph_objs.Layout(title="Bytes over Time ",
47     xaxis=dict(title="Time"),
48     yaxis=dict(title="Bytes"))})