Install of theHarvester on Ubuntu16.04

▪️Install
$sudo pip2 install request
$git clone https://github.com/laramies/theHarvester.git

▪️test
$ python2 theHarvester.py -d ****.com -l 500 -b all

Install of Volatility in Ubuntu16.04

▪️Required package
$ sudo apt-get install python python-pip unzip subversion pcregrep libpcre++-dev python-dev

▪️Install of PyCrypto
$ sudo pip install pycrypto
$ sudo pip install distorm3

▪️Install of YARA 3.70
$ get https://github.com/VirusTotal/yara/archive/v3.7.0.zip
$ unzip v3.7.0.zip
$ cd yara-3.7.0
$ ./bootstrap.sh
$ sudo apt-get install automake libtool make gcc
$ sudo apt-get install flex bison
$ ./configure
$ make
$ sudo make install

▪️Install of Volantility

$ git clone https://github.com/volatilityfoundation/volatility.git
$ cd volantility
$ sudo python setup.py install

PyTorch

Speaking of Deep Learning's library Tensorflow is famous. Since it was released a year and a half ago, I got a name recognition for a moment.
I began looking for other libraries, thinking that it would be better to use a more flexible library than Keras. Then what is Torch's Python version out there!
DeepMind has moved from Torch to Tensorflow, but I anticipate that you are already using PyTorch. Facebook is also one of the representative companies using Torch, and I am involved in the development of PyTorch.

Machine learning result (mnist recognition)

Imaging mnist data

——mnist_data_image.py------
1 # -*- coding: utf-8 -*-
2
3 import sys
4 import numpy as np
5 np.random.seed(20160715)
6
7 from keras.datasets import mnist
8 from keras.utils import np_utils
9
10 (X_train, y_train), (X_test, y_test) = mnist.load_data()
11
12 for xs in X_train[1]:
13 for x in xs:
14 sys.stdout.write('%03d ' % x)
15 sys.stdout.write('\n')
16
17 print('first sample is %d' % y_train[0])
18
19 Y_train = np_utils.to_categorical(y_train, 10)
20
21 sys.stdout.write('[')
22 for y in Y_train[0]:
23 sys.stdout.write('%f ' % y)
24 sys.stdout.write(']\n')

PWA (progressive web application) supported on iOS

As I wrote in an article I posted in the past, PWA (Progressive Web Application) that I could only use in Chrome until now can be used in Safari.

The advantages of PWA are described below.

1. It is possible to provide user experience that is the same as or close to the application on mobile sites

2. Page loading is fast

3. Push notification is possible

4. By using the service worker mechanism, pages can be used even offline. FINANCIAL TIMES is an example.

OpenCV 3.1.0 install

$ sudo apt-get install build-essential cmake git
$ sudo apt-get install ffmpeg libopencv-dev libgtk-3-dev python-numpy python3-numpy libdc1394-22 libdc1394-22-dev libjpeg-dev libpng12-dev libtiff5-dev libjasper-dev libavcodec-dev libavformat-dev libswscale-dev libxine2-dev libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libv4l-dev libtbb-dev qtbase5-dev libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils unzip

$ wget https://github.com/Itseez/opencv/archive/3.1.0.zip
$ cd opencv-3.1.0
$ mkdir build
$ cd build
$ cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D WITH_V4L=ON -D WITH_QT=ON -D WITH_OPENGL=ON ..
$ make
$ sudo make install
$ sudo /bin/bash -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf'
$ sudo ldconfig

$ sudo pip3 install opencv-python