Hai-Anh Trinh aht

Grammarly iOS Keyboard – Unboxing

Grammarly is a lovely writing assistant. Twenty million people use the tool across the globe according to the statistics available on the site. I use it too. No complaints, it does its job quite well, and I am a happy user. The only thing that always worried me is the Grammarly iOS Keyboard. As an iOS engineer, I know how easily you can collect different data, sensitive information, and even do not ask users about the consent. So, let's check what is inside the Grammarly iOS application.

TL;DR

Grammarly iOS uses at least three trackers (Adjust, AppsFlyer, Internal analytics)
Grammarly Keyboard has access to keystrokes, sensitive data, and able to send them over the network

Frameworks

303 See Other

Location: https://github.com/wsargent/docker-cheat-sheet

Hi there!

The docker cheat sheet has moved to a Github project under https://github.com/wsargent/docker-cheat-sheet.

Please click on the link above to go to the cheat sheet.

This is a review of "Quantitative Analysis of the Full Bitcoin Transaction Graph" by Dorit Ron and Adi Shamir.

There are some incorrect details and analyses that warrant attention.

Oct. 31 UPDATE

The authors have introduced several revisions to their paper, available at the same URL as before.

The criticism below may be outdated in part or in full.

	from numpy.random import RandomState
	import pyspark.sql.functions as f
	from pyspark import StorageLevel


	def hashmin_jaccard_spark(
	sdf, node_col, edge_basis_col, suffixes=('A', 'B'),
	n_draws=100, storage_level=None, seed=42, verbose=False):
	"""
	Calculate a sparse Jaccard similarity matrix using MinHash.

	"""
	A deep neural network with or w/o dropout in one file.

	License: Do What The Fuck You Want to Public License http://www.wtfpl.net/
	"""

	import numpy, theano, sys, math
	from theano import tensor as T
	from theano import shared
	from theano.tensor.shared_randomstreams import RandomStreams

	// 1. Go to page https://www.linkedin.com/settings/email-frequency
	// 2. You may need to login
	// 3. Open JS console
	// ([How to?](http://webmasters.stackexchange.com/questions/8525/how-to-open-the-javascript-console-in-different-browsers))
	// 4. Copy the following code in and execute
	// 5. No more emails
	//
	// Bookmarklet version:
	// http://chengyin.github.io/linkedin-unsubscribed/

	###############################################################################
	# Copyright (c) 2013, William Stein
	# All rights reserved.
	#
	# Redistribution and use in source and binary forms, with or without
	# modification, are permitted provided that the following conditions are met:
	#
	# 1. Redistributions of source code must retain the above copyright notice, this
	# list of conditions and the following disclaimer.
	# 2. Redistributions in binary form must reproduce the above copyright notice,

	from __future__ import print_function
	from tornado.gen import Task, Return, coroutine
	import tornado.process
	from tornado.ioloop import IOLoop
	import subprocess
	import time


	STREAM = tornado.process.Subprocess.STREAM

	import sys

	from pyspark.context import SparkContext
	from numpy import array, random as np_random
	from sklearn import linear_model as lm
	from sklearn.base import copy

	N = 10000 # Number of data points
	D = 10 # Numer of dimensions
	ITERATIONS = 5