Obfuscation isn't difficult in most programming languages. It's why we have "good practices" because it is so easy to hide what you mean in badly written code.
Obfuscation tends to be even easier in dynamic languages because of how forgiving they tend to be - and because they tend to give you direct access to the environment so that you can manipulate it.
Today, for fun, I'm going to obfuscate this code:
def _(n):
if n <= 0:
Andy Thomason is a Senior Programmer at Genomics PLC. He has been witing graphics systems, games and compilers since the '70s and specialises in code performance.
Today (April 16th 2019 at noon) the first major clues to discover key #1 was set to be released in a few cities. A QR code with the words 'orbital' were found at these locations and looked like this: (https://imgur.com/a/6rNmz7T). If you read the QR code with your phone you will be directed to this url: https://satoshistreasure.xyz/k1
At this URL you are prompted to input a passphrase to decrypt the first shard. An obvious first guess was to try the word 'orbital' from the QR code. Not suprisingly this worked! This reveals a congratulations page and presents the first key shard:
ST-0001-a36e904f9431ff6b18079881a20af2b3403b86b4a6bace5f3a6a47e945b95cce937c415bedaad6c86bb86b59f0b1d137442537a8.
Now, we were supposed to wait until April 17th to get clues from the other cities for keys #2 and #3 but that wouldn't stop me from digging around with all the new information we had. All that time "playing" notpron (http://notpron.org/notpron/) years ago was going to help me here.
The first thing I noticed was
| const PASS = ['32']; // green | |
| const FAIL = ['31', '1']; // red, bold | |
| function logStyle(ansiEscapeCodes, text) { | |
| console.log(`\x1b[${ansiEscapeCodes.join(';')}m${text}\x1b[0m`); | |
| } | |
| class Tester { | |
| constructor() {} |
| section ‹A Simple Graph Problem› | |
| text ‹ | |
| We shall prove the following: "In a finite group of people, some of whom are friends with some | |
| of the others there must be at least two people who have the same number of friends." | |
| › | |
| theory Friends | |
| imports Main | |
| Finite_Set |
This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).
Matrix multiplication is a mathematical operation that defines the product of
Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.
This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would
| #!/usr/bin/env xcrun swift -O | |
| /* | |
| gen.swift is a direct port of cfdrake's helloevolve.py from Python 2.7 to Swift 3 | |
| -------------------- https://gist.github.com/cfdrake/973505 --------------------- | |
| gen.swift implements a genetic algorithm that starts with a base | |
| population of randomly generated strings, iterates over a certain number of | |
| generations while implementing 'natural selection', and prints out the most fit | |
| string. | |
| The parameters of the simulation can be changed by modifying one of the many |
