mirror of
https://github.com/ntop/ntopng.git
synced 2026-04-29 07:29:32 +00:00
279 lines
8 KiB
Python
Executable file
279 lines
8 KiB
Python
Executable file
#!/usr/bin/env python3
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"""
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Report creation script for the ntopng Python API
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"""
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import os
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import sys
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import time
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import getopt
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import pandas as pd
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from fpdf import FPDF
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import plotly.figure_factory as ff
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import plotly.graph_objects as go
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sys.path.insert(0, '../')
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from ntopng.ntopng import Ntopng
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### NTOPNG API SETUP
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username = "admin"
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password = "password"
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ntopng_url = "http://localhost:4000"
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iface_id = 2
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auth_token = None
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enable_debug = False
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host_ip = "127.0.0.1"
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actual_ts = int(time.time())
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yesterday = (actual_ts - 86400)
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##################################
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######### DATA COLLECTOR #########
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##################################
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try:
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my_ntopng = Ntopng(username, password, auth_token, ntopng_url)
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if(enable_debug):
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my_ntopng.enable_debug()
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except ValueError as e:
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print(e)
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os._exit(-1)
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try:
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my_interface = my_ntopng.get_interface(iface_id)
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my_historical = my_ntopng.get_historical_interface(iface_id)
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except ValueError as e:
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print(e)
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os._exit(-1)
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def get_alerts_severity():
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"""
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Return a dataframe with alerts and severity
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"""
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alert_count_severity = my_historical.get_alerts_stats(yesterday, actual_ts)
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alert_severity_df = pd.DataFrame(alert_count_severity[0]["value"])
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alert_severity_df.drop(["key", "title"], axis= 1, inplace=True)
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return alert_severity_df
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def get_top_client_server():
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"""
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Return a dataframe with top clients and servers seen on the interface specified in the above script init data
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"""
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top_client_server = my_historical.get_flow_alerts_stats(yesterday, actual_ts)
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top_client_server_df = pd.DataFrame(top_client_server[0]["value"])
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top_client_server_df.drop(["key", "value"], axis= 1, inplace=True)
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return top_client_server_df
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def get_host_info(ip):
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"""
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Return a dataframe with alerts and severity
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:param ip: ip of the desired host to get data of
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"""
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my_host = my_interface.get_host(ip)
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return my_host
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def get_upload_download():
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"""
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Return a list where => data[0] = uploaded MB, data[1] = downloaded MB for the interface specified in the above script init data
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"""
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up_down = my_historical.get_interface_timeseries("iface:traffic_rxtx", yesterday, actual_ts)
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data = [(up_down["bytes_sent"].sum()/1000000), (up_down["bytes_rcvd"].sum()/1000000)]
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return data
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def get_interface_data():
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"""
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Return a dict with info about the interface specified in the above script init data
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"""
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host_data = my_interface.get_data()
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host_info = {"flow_count": host_data["num_flows"], "local_hosts": host_data["num_local_hosts"], "hosts_count": host_data["num_hosts"], "local_hosts_anomalies": host_data["num_local_hosts_anomalies"], "alerted_flows": host_data["alerted_flows"], "num_flows": host_data["num_flows"],
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"flows_warning": host_data["alerted_flows_warning"], "flows_error": host_data["alerted_flows_error"]}
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return host_info
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def get_interfaces():
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"""
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Return a df with a list of all the interfaces
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"""
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interfaces = my_ntopng.get_interfaces_list()
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interfaces_df = pd.DataFrame(interfaces)
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interfaces_df.drop("name", axis=1, inplace=True)
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return interfaces_df
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def get_interfaces_count():
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"""
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Return number of interfaces
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"""
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interfaces = my_ntopng.get_interfaces_list()
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return len(interfaces)
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##################################
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############# UTILS ##############
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##################################
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def delete_file(fname):
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"""
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Deletes the table png from the current path
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:param fname: name of png to delete
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"""
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current_dir = os.getcwd()
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path = current_dir+"/"+fname
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try:
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os.path.exists(path)
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os.remove(path)
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except Exception as e:
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print(f"FILE: {path} DOES NOT EXIST...")
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os._exit(-1)
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def df_to_table_png(df, fname):
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"""
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Return creates a png of the df specified with name
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:param df: dataframe to save to png
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:param fname: name of the file to save
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"""
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fig = ff.create_table(df, colorscale=[[0, "#f3a114"], [.5, "#d9d9d9"], [1, "#ffffff"]])
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fig.update_layout(autosize=False, width=1100, height=350)
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fig.write_image(str(fname), scale=2)
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def plot_up_down():
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"""
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Plots a png of the timeseries
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"""
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up_down = my_historical.get_interface_timeseries("iface:traffic_rxtx", yesterday, actual_ts)
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up_down.reset_index(inplace=True)
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up_down['ts'] = up_down['index'].apply(lambda x: x.left)
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up_down['ts'] = pd.to_datetime(up_down['ts'], unit='s')
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layout = dict(plot_bgcolor='rgba(255,255,255, 0.3)')
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fig = go.Figure(layout=layout)
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fig.add_trace(go.Scatter(x=up_down["ts"], y=up_down["bytes_rcvd"],
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mode='lines',
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name='Downloaded bytes',
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line_color='#f3a114'))
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fig.add_trace(go.Scatter(x=up_down["ts"], y=up_down["bytes_sent"],
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mode='lines',
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name='Uploaded bytes',
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line_color='#000000'))
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#fig.update_xaxes(showgrid=True, gridwidth=1, gridcolor='black')
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#fig.update_yaxes(showgrid=True, gridwidth=1, gridcolor='black')
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fig.write_image("series.png", width=1280, height=720)
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##################################
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######## DATA COLLECTION #########
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##################################
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created_files = []
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interfaces_count = get_interfaces_count()
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data_sent_rcvd = get_upload_download()
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interface_data = get_interface_data()
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#interfaces table
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#interfaces_df = get_interfaces()
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#interfaces_df_fname = "interfaces_table.png"
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#created_files.append(interfaces_df_fname)
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#df_to_table_png(interfaces_df, interfaces_df_fname)
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#alerts table
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alerts_df = get_alerts_severity()
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alerts_df.columns = ["Alert Type", "Score", "Alert occurrence %"]
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alerts_df_fname = "alerts_table.png"
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created_files.append(alerts_df_fname)
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df_to_table_png(alerts_df, alerts_df_fname)
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#client/server table
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hosts_df = get_top_client_server()
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hosts_df.columns = ["Host occurrence %", "Vlan", "IP", "Host Name"]
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hosts_df = hosts_df[["Host Name", "IP", "Host occurrence %", "Vlan"]]
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hosts_df
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hosts_df_fname = "hosts_table.png"
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created_files.append(hosts_df_fname)
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df_to_table_png(hosts_df, hosts_df_fname)
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## UPLOADED/DOWNLOADED IN MB
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uploaded = data_sent_rcvd[0]
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downloaded = data_sent_rcvd[1]
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## INFO FOR SPECIFIED IFID
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flows = interface_data["num_flows"]
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host_num = interface_data["hosts_count"]
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local_hosts_num = interface_data["local_hosts"]
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flows_errors = interface_data["flows_error"]
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flows_warnings = interface_data["flows_warning"]
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##################################
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########## PDF CREATION ##########
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##################################
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MARGIN = 10
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pw = 25 - 2*MARGIN
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ch = 50
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pdf = FPDF()
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pdf.add_page()
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## LOGO
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pdf.image("img/ntop.png", x=140, y=8, w=68.2, h=17.8)
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## HOST PC SPECS AND STATS ##
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pdf.set_font("Helvetica", "B", 14)
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pdf.set_text_color(r= 0, g= 0, b = 0)
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pdf.ln(9)
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pdf.cell(w=0, h=10, txt="HOST INFO", ln=1)
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pdf.set_font("Helvetica", "", 11)
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pdf.cell(w=0, h=5, txt=f"Host: {host_ip}")
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pdf.ln(5)
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pdf.cell(w=0, h=5, txt=f"Timestamp: {time.strftime('%d-%m-%Y %H:%M:%S', time.localtime(actual_ts))}")
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pdf.ln(5)
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pdf.cell(w=0, h=5, txt=f"# Interfaces: {interfaces_count}")
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pdf.ln(7)
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## 24hr stats ##
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pdf.set_font("Helvetica", "B", 14)
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pdf.cell(w=0, h=10, txt="24h STATS")
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pdf.ln(5)
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pdf.set_font("Helvetica", "", 11)
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pdf.cell(w=(pw/2), h=(ch/4), txt=f"Flows: {flows}")
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pdf.ln(5)
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pdf.cell(w=(pw/2), h=(ch/4), txt=f"Hosts count: {host_num}")
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pdf.ln(5)
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pdf.cell(w=(pw/2), h=(ch/4), txt=f"Local hosts count: {local_hosts_num}")
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pdf.ln(5)
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pdf.cell(w=(pw/2), h=(ch/4), txt=f"UP/DOWN MB: {uploaded:.3f}/{downloaded:.3f}")
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pdf.ln(5)
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pdf.cell(w=(pw/2), h=(ch/4), txt=f"Flows errors: {flows_errors}")
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pdf.ln(5)
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pdf.cell(w=(pw/2), h=(ch/4), txt=f"Flows warnings: {flows_warnings}")
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pdf.ln(5)
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# Alerts
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pdf.image("alerts_table.png", x=10, y=75, w=190, h=65)
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## Hosts
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pdf.image("hosts_table.png", x=10, y=135, w=190, h=65)
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# Series plot
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plot_up_down()
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pdf.image("series.png", x=10, y=210, w=190, h=85)
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created_files.append("report.pdf")
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created_files.append("series.png")
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pdf.output(f"./report.pdf", "F")
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for file in created_files:
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delete_file(file)
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