Social engineering is the technique by which an attacker can make a person do something that is not usually in their best interest. In this article, we will look at a few common ways Social Engineers try to manipulate you.
Disclaimer: My articles are purely educational. If you read them and cause damage to someone, that's on you. I don't encourage any malicious activity or black hat practices. Read the code of ethics here.
Remember the Nigerian scammers sending you emails about the rich prince that needs your help? All you had to do was transfer a thousand dollars in exchange for a multi-million dollar fortune.
There are similar scams that have circulated the internet: The IRS scam, Lottery scams, and so on. …
Numpy is a python library for performing large scale numerical computations. It is extremely useful, especially in machine learning. Let's look at what Numpy has to offer.
Introduction
NumPy is a Python library used to perform numerical computations with large datasets. Numpy stands for Numerical Python and it is a popular library used by data scientists, especially for machine learning problems. NumPy is useful during pre-processing the data before you train it using a machine learning algorithm.
Working with n-dimensional arrays is easier in Numpy compared to Python lists. Numpy arrays are also faster than Python lists since unlike lists, NumPy arrays are stored at one continuous place in memory. This enables the processor to perform computations efficiently with NumPy arrays.
In this article, we will look at the basics of working with Numpy including array operations, matrix transformations, generating random values, and so on. …
Hope you had a great weekend. Here are the stories from last week.
- Penetration Testing — 100 Terms You Need To Know — This article will help you understand some of the common terms you will come across as a security engineer.
- WiFi Hacking — Securing Wifi Networks With Aircrack-NG — In this article, we will look at how to audit wireless networks using Aircrack.
Have a great week :)
Cheers,
Manish
Find me at https://www.linkedin.com/in/manishmshiva
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