add tags_to_graphs.py in ecamples/situational-awareness

pull/27/head
Déborah Servili 2016-09-05 14:14:29 +02:00
parent 95654e083c
commit fa66c77cd1
5 changed files with 451 additions and 44 deletions

View File

@ -20,10 +20,10 @@
* tags_repartition_plot that present the raw data
* tags_repartition_trend_plot that present the general evolution for each tag
* Then each taxonomies will be represented in three plots:
* Raw datas: in plot folder, named with the name of the corresponding taxonomy
* Trend: in plot folder, named _taxonomy_\_trend. general evolution of the data (linear fitting, curve fitting at order 1)
* Curve fitting: in plotlib folder, name as the taxonomy it presents.
* Raw datas: in "plot" folder, named with the name of the corresponding taxonomy
* Trend: in "plot" folder, named _taxonomy_\_trend. general evolution of the data (linear fitting, curve fitting at order 1)
* Curve fitting: in "plotlib" folder, name as the taxonomy it presents.
* In order to visualize the last plots, a html file is also generated automaticaly (might be improved in the future)
:warning: These scripts are not time optimised

View File

@ -29,11 +29,15 @@ table td
{
border-left: 1px solid #cbcbcb;
border-width: 0 0 0 1px;
width: 150px;
width: 500px;
margin: 0;
padding: 0.5em 1em;
}
.test
{
width: 500px;
}
table tr:nth-child(2n-1) td
{

View File

@ -0,0 +1,41 @@
body
{
/*font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;*/
font-family: Consolas, "Liberation Mono", Menlo, Courier, monospace;
}
h1
{
font-size: 16px;
width: 290px;
text-align:center;
}
/*** Stats Tables ***/
table
{
border-collapse: collapse;
border-spacing: 0;
table-layout: fixed;
width: 6000px;
border: 1px solid #cbcbcb;
}
tbody
{
font-size:12px;
}
td
{
border-left: 1px solid #cbcbcb;
border-width: 0 0 0 1px;
margin: 0;
padding: 0.5em 1em;
}
table tr td:first-child
{
font-weight: bold;
}

View File

@ -0,0 +1,91 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from pymisp import PyMISP
from keys import misp_url, misp_key, misp_verifycert
import argparse
import tools
def formattingDataframe(dataframe, dates, NanValue):
dataframe.reverse()
dates.reverse()
dataframe = tools.concat(dataframe)
dataframe = tools.renameColumns(dataframe, dates)
dataframe = tools.replaceNaN(dataframe, 0)
return dataframe
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Show the evolution of trend of tags.')
parser.add_argument("-p", "--period", help='Define the studied period. Can be the past year (y), month (m) or week (w). Week is the default value if no valid value is given.')
parser.add_argument("-a", "--accuracy", help='Define the accuracy of the splits on the studied period. Can be per month (m) -for year only-, week (w) -month only- or day (d). The default value is always the biggest available.')
parser.add_argument("-o", "--order", type=int, help='Define the accuracy of the curve fitting. Default value is 3')
args = parser.parse_args()
misp = PyMISP(misp_url, misp_key, misp_verifycert)
if args.period == "y":
if args.accuracy == "d":
split = 360
size = 1
else:
split = 12
size = 30
last = '360d'
title = 'Tags repartition over the last 360 days'
elif args.period == "m":
if args.accuracy == "d":
split = 28
size = 1
else:
split = 4
size = 7
last = '28d'
title = 'Tags repartition over the last 28 days'
else:
split = 7
size = 1
last = '7d'
title = 'Tags repartition over the last 7 days'
result = misp.download_last(last)
events = tools.eventsListBuildFromArray(result)
result = []
dates = []
enddate = tools.getToday()
colourDict = {}
faketag = False
for i in range(split):
begindate = tools.getNDaysBefore(enddate, size)
dates.append(str(enddate.date()))
eventstemp = tools.selectInRange(events, begin=begindate, end=enddate)
if eventstemp is not None:
tags = tools.tagsListBuild(eventstemp)
if tags is not None:
tools.createDictTagsColour(colourDict, tags)
result.append(tools.getNbOccurenceTags(tags))
else:
result.append(tools.createFakeEmptyTagsSeries())
faketag = True
else:
result.append(tools.createFakeEmptyTagsSeries())
faketag = True
enddate = begindate
result = formattingDataframe(result, dates, 0)
if faketag:
result = tools.removeFaketagRow(result)
taxonomies, emptyOther = tools.getTaxonomies(tools.getCopyDataframe(result))
tools.tagsToLineChart(tools.getCopyDataframe(result), title, dates, colourDict)
tools.tagstrendToLineChart(tools.getCopyDataframe(result), title, dates, split, colourDict)
tools.tagsToTaxoLineChart(tools.getCopyDataframe(result), title, dates, colourDict, taxonomies, emptyOther)
tools.tagstrendToTaxoLineChart(tools.getCopyDataframe(result), title, dates, split, colourDict, taxonomies, emptyOther)
if args.order is None:
args.order = 3
tools.tagsToPolyChart(tools.getCopyDataframe(result), split, colourDict, taxonomies, emptyOther, args.order)
tools.createVisualisation(taxonomies)

View File

@ -9,8 +9,13 @@ import pandas
from datetime import datetime
from datetime import timedelta
from dateutil.parser import parse
# ############### Errors ################
import numpy
from scipy import stats
from pytaxonomies import Taxonomies
import re
import matplotlib.pyplot as plt
from matplotlib import pylab
import os
class DateError(Exception):
@ -20,30 +25,8 @@ class DateError(Exception):
def __str__(self):
return repr(self.value)
# ############### Tools ################
def buildDoubleIndex(index1, index2, datatype):
it = -1
newindex1 = []
for index in index2:
if index == 0:
it += 1
newindex1.append(index1[it])
arrays = [newindex1, index2]
tuples = list(zip(*arrays))
return pandas.MultiIndex.from_tuples(tuples, names=['event', datatype])
def buildNewColumn(index2, column):
it = -1
newcolumn = []
for index in index2:
if index == 0:
it += 1
newcolumn.append(column[it])
return newcolumn
# ############### Date Tools ################
def dateInRange(datetimeTested, begin=None, end=None):
if begin is None:
@ -53,10 +36,6 @@ def dateInRange(datetimeTested, begin=None, end=None):
return begin <= datetimeTested <= end
def addColumn(dataframe, columnList, columnName):
dataframe.loc[:, columnName] = pandas.Series(columnList, index=dataframe.index)
def toDatetime(date):
return parse(date)
@ -86,6 +65,115 @@ def setEnddate(enddate):
def getLastdate(last):
return (datetime.now() - timedelta(days=int(last))).replace(hour=0, minute=0, second=0, microsecond=0)
def getNDaysBefore(date, days):
return (date - timedelta(days=days)).replace(hour=0, minute=0, second=0, microsecond=0)
def getToday():
return (datetime.now()).replace(hour=0, minute=0, second=0, microsecond=0)
# ############### Tools ################
def getTaxonomies(dataframe):
taxonomies = Taxonomies()
taxonomies = list(taxonomies.keys())
notInTaxo = []
count = 0
for taxonomy in taxonomies:
empty = True
for it in dataframe.iterrows():
if it[0].startswith(taxonomy):
empty = False
dataframe = dataframe.drop([it[0]])
count = count + 1
if empty is True:
notInTaxo.append(taxonomy)
if dataframe.empty:
emptyOther = True
else:
emptyOther = False
for taxonomy in notInTaxo:
taxonomies.remove(taxonomy)
return taxonomies, emptyOther
def buildDoubleIndex(index1, index2, datatype):
it = -1
newindex1 = []
for index in index2:
if index == 0:
it += 1
newindex1.append(index1[it])
arrays = [newindex1, index2]
tuples = list(zip(*arrays))
return pandas.MultiIndex.from_tuples(tuples, names=['event', datatype])
def buildNewColumn(index2, column):
it = -1
newcolumn = []
for index in index2:
if index == 0:
it += 1
newcolumn.append(column[it])
return newcolumn
def addColumn(dataframe, columnList, columnName):
dataframe.loc[:, columnName] = pandas.Series(columnList, index=dataframe.index)
def concat(data):
return pandas.concat(data, axis=1)
def createFakeEmptyTagsSeries():
return pandas.Series({'Faketag': 0})
def removeFaketagRow(dataframe):
return dataframe.drop(['Faketag'])
def getCopyDataframe(dataframe):
return dataframe.copy()
def createDictTagsColour(colourDict, tags):
temp = tags.groupby(['name', 'colour']).count()['id']
levels_name = temp.index.levels[0]
levels_colour = temp.index.levels[1]
labels_name = temp.index.labels[0]
labels_colour = temp.index.labels[1]
for i in range(len(labels_name)):
colourDict[levels_name[labels_name[i]]] = levels_colour[labels_colour[i]]
def createTagsPlotStyle(dataframe, colourDict, taxonomy=None):
colours = []
if taxonomy is not None:
for it in dataframe.iterrows():
if it[0].startswith(taxonomy):
colours.append(colourDict[it[0]])
else:
for it in dataframe.iterrows():
colours.append(colourDict[it[0]])
style = Style(background='transparent',
plot_background='#eeeeee',
foreground='#111111',
foreground_strong='#111111',
foreground_subtle='#111111',
opacity='.6',
opacity_hover='.9',
transition='400ms ease-in',
colors=tuple(colours))
return style
# ############### Formatting ################
@ -129,15 +217,19 @@ def attributesListBuild(events):
def tagsListBuild(Events):
Tags = []
for Tag in Events['Tag']:
if type(Tag) is not list:
continue
Tags.append(pandas.DataFrame(Tag))
Tags = pandas.concat(Tags)
columnDate = buildNewColumn(Tags.index, Events['date'])
addColumn(Tags, columnDate, 'date')
index = buildDoubleIndex(Events.index, Tags.index, 'tag')
Tags = Tags.set_index(index)
if 'Tag' in Events.columns:
for Tag in Events['Tag']:
if type(Tag) is not list:
continue
Tags.append(pandas.DataFrame(Tag))
if Tags:
Tags = pandas.concat(Tags)
columnDate = buildNewColumn(Tags.index, Events['date'])
addColumn(Tags, columnDate, 'date')
index = buildDoubleIndex(Events.index, Tags.index, 'tag')
Tags = Tags.set_index(index)
else:
Tags = None
return Tags
@ -148,6 +240,8 @@ def selectInRange(Events, begin=None, end=None):
inRange.append(Event.tolist())
inRange = pandas.DataFrame(inRange)
temp = Events.columns.tolist()
if inRange.empty:
return None
inRange.columns = temp
return inRange
@ -160,6 +254,15 @@ def isTagIn(dataframe, tag):
index.append(temp[i][0])
return index
def renameColumns(dataframe, namelist):
dataframe.columns = namelist
return dataframe
def replaceNaN(dataframe, value):
return dataframe.fillna(value)
# ############### Basic Stats ################
@ -212,7 +315,7 @@ def createTreemap(data, title, treename='attribute_treemap.svg', tablename='attr
transition='400ms ease-in',
colors=tuple(colors.values()))
treemap = pygal.Treemap(pretty_print=True, legend_at_bottom=True, style=style, explicit_size=True, width=2048, height=2048)
treemap = pygal.Treemap(pretty_print=True, legend_at_bottom=True, style=style)
treemap.title = title
treemap.print_values = True
treemap.print_labels = True
@ -222,3 +325,171 @@ def createTreemap(data, title, treename='attribute_treemap.svg', tablename='attr
createTable(colors, categ_types_hash)
treemap.render_to_file(treename)
def tagsToLineChart(dataframe, title, dates, colourDict):
style = createTagsPlotStyle(dataframe, colourDict)
line_chart = pygal.Line(x_label_rotation=20, style=style, show_legend=False)
line_chart.title = title
line_chart.x_labels = dates
for it in dataframe.iterrows():
line_chart.add(it[0], it[1].tolist())
line_chart.render_to_file('tags_repartition_plot.svg')
def tagstrendToLineChart(dataframe, title, dates, split, colourDict):
style = createTagsPlotStyle(dataframe, colourDict)
line_chart = pygal.Line(x_label_rotation=20, style=style, show_legend=False)
line_chart.title = title
line_chart.x_labels = dates
xi = numpy.arange(split)
for it in dataframe.iterrows():
slope, intercept, r_value, p_value, std_err = stats.linregress(xi, it[1])
line = slope * xi + intercept
line_chart.add(it[0], line, show_dots=False)
line_chart.render_to_file('tags_repartition_trend_plot.svg')
def tagsToTaxoLineChart(dataframe, title, dates, colourDict, taxonomies, emptyOther):
style = createTagsPlotStyle(dataframe, colourDict)
line_chart = pygal.Line(x_label_rotation=20, style=style)
line_chart.title = title
line_chart.x_labels = dates
for taxonomy in taxonomies:
taxoStyle = createTagsPlotStyle(dataframe, colourDict, taxonomy)
taxo_line_chart = pygal.Line(x_label_rotation=20, style=taxoStyle)
taxo_line_chart.title = title + ': ' + taxonomy
taxo_line_chart.x_labels = dates
for it in dataframe.iterrows():
if it[0].startswith(taxonomy):
taxo_line_chart.add(re.sub(taxonomy + ':', '', it[0]), it[1].tolist())
dataframe = dataframe.drop([it[0]])
taxo_line_chart.render_to_file('plot/' + taxonomy + '.svg')
if not emptyOther:
taxoStyle = createTagsPlotStyle(dataframe, colourDict)
taxo_line_chart = pygal.Line(x_label_rotation=20, style=taxoStyle)
taxo_line_chart.title = title + ': other'
taxo_line_chart.x_labels = dates
for it in dataframe.iterrows():
taxo_line_chart.add(it[0], it[1].tolist())
taxo_line_chart.render_to_file('plot/other.svg')
def tagstrendToTaxoLineChart(dataframe, title, dates, split, colourDict, taxonomies, emptyOther):
style = createTagsPlotStyle(dataframe, colourDict)
line_chart = pygal.Line(x_label_rotation=20, style=style)
line_chart.title = title
line_chart.x_labels = dates
xi = numpy.arange(split)
for taxonomy in taxonomies:
taxoStyle = createTagsPlotStyle(dataframe, colourDict, taxonomy)
taxo_line_chart = pygal.Line(x_label_rotation=20, style=taxoStyle)
taxo_line_chart.title = title + ': ' + taxonomy
taxo_line_chart.x_labels = dates
for it in dataframe.iterrows():
if it[0].startswith(taxonomy):
slope, intercept, r_value, p_value, std_err = stats.linregress(xi, it[1])
line = slope * xi + intercept
taxo_line_chart.add(re.sub(taxonomy + ':', '', it[0]), line, show_dots=False)
dataframe = dataframe.drop([it[0]])
taxo_line_chart.render_to_file('plot/' + taxonomy + '_trend.svg')
if not emptyOther:
taxoStyle = createTagsPlotStyle(dataframe, colourDict)
taxo_line_chart = pygal.Line(x_label_rotation=20, style=taxoStyle)
taxo_line_chart.title = title + ': other'
taxo_line_chart.x_labels = dates
for it in dataframe.iterrows():
slope, intercept, r_value, p_value, std_err = stats.linregress(xi, it[1])
line = slope * xi + intercept
taxo_line_chart.add(it[0], line, show_dots=False)
taxo_line_chart.render_to_file('plot/other_trend.svg')
def tagsToPolyChart(dataframe, split, colourDict, taxonomies, emptyOther, order):
for taxonomy in taxonomies:
for it in dataframe.iterrows():
if it[0].startswith(taxonomy):
points = []
for i in range(split):
points.append((i, it[1][i]))
color = colourDict[it[0]]
label = re.sub(taxonomy + ':', '', it[0])
points = numpy.array(points)
dataframe = dataframe.drop([it[0]])
# get x and y vectors
x = points[:, 0]
y = points[:, 1]
# calculate polynomial
z = numpy.polyfit(x, y, order)
f = numpy.poly1d(z)
# calculate new x's and y's
x_new = numpy.linspace(x[0], x[-1], 50)
y_new = f(x_new)
plt.plot(x, y, '.', color=color)
plt.plot(x_new, y_new, color=color, label=label + 'trend')
pylab.title('Polynomial Fit with Matplotlib: ' + taxonomy)
pylab.legend(loc='center left', bbox_to_anchor=(1, 0.5))
ax = plt.gca()
ax.set_facecolor((0.898, 0.898, 0.898))
box = ax.get_position()
ax.set_position([box.x0 - 0.01, box.y0, box.width * 0.78, box.height])
fig = plt.gcf()
fig.set_size_inches(20, 15)
fig.savefig('plotlib/' + taxonomy + '.png')
fig.clf()
if not emptyOther:
for it in dataframe.iterrows():
points = []
for i in range(split):
points.append((i, it[1][i]))
color = colourDict[it[0]]
label = it[0]
points = numpy.array(points)
# get x and y vectors
x = points[:, 0]
y = points[:, 1]
# calculate polynomial
z = numpy.polyfit(x, y, order)
f = numpy.poly1d(z)
# calculate new x's and y's
x_new = numpy.linspace(x[0], x[-1], 50)
y_new = f(x_new)
plt.plot(x, y, '.', color=color, label=label)
plt.plot(x_new, y_new, color=color, label=label + 'trend')
pylab.title('Polynomial Fit with Matplotlib: other')
pylab.legend(loc='center left', bbox_to_anchor=(1, 0.5))
ax = plt.gca()
ax.set_facecolor((0.898, 0.898, 0.898))
box = ax.get_position()
ax.set_position([box.x0 - 0.01, box.y0, box.width * 0.78, box.height])
fig = plt.gcf()
fig.set_size_inches(20, 15)
fig.savefig('plotlib/other.png')
def createVisualisation(taxonomies):
chain = '<!DOCTYPE html>\n<html>\n\t<head>\n\t\t<link rel="stylesheet" href="style2.css">\n\t</head>\n\t<body>'
chain = chain + '<table>'
for taxonomy in taxonomies:
chain = chain + '<tr><td><object type="image/svg+xml" data="plot\\' + taxonomy + '.svg"></object></td><td><img src="plotlib\\' + taxonomy + '.png" alt="graph" /></td><td><object type="image/svg+xml" data="plot\\' + taxonomy + '_trend.svg"></object></td></tr>\n'
chain = chain + '<tr><td><object type="image/svg+xml" data="plot\other.svg"></object></td><td><img src="plotlib\other.png" alt="graph" /></td><td><object type="image/svg+xml" data="plot\other_trend.svg"></object></td></tr>\n'
chain = chain + '</table>'
chain = chain + '\n\t</body>\n</html>'
with open('test_tags_trend.html', 'w') as target:
target.write(chain)