Here we are again with the newest information on what happened in cyber and network security from June 15 to June 20. There has been a lot of events, so let's roll with the most critical ones.
Here we are again with the newest information on what happened in cyber and network security from June 15 to June 20. There has been a lot of events, so let's roll with the most critical ones.
Wow, that's been a week! Here's the blogpost copying our newsletter that covers all the newest information on what happened in cyber and network security from June 8 to June 13.
“In 1665, Cambridge University closed because of the plague. Issac Newton decided to work from home. He discovered calculus & the laws of motion.”
We live in a truly remarkable moment. With the year 2020 and the COVID-19 outbreak employees all over the world are staying home for quarantine, trying their best to sustain the normal flow of life, which means continue working. And this is something new compared to all the previous infectious pandemics humanity has survived through — this time we have the Internet.
github.com/QratorLabs/fastenum
pip install fast-enum
(If you think you know that — scroll down to the “Enums in Standard Library” section).
Imagine that you need to describe a set of all possible states for the entities in your database model. You'll probably use a bunch of constants defined as module-level attributes:
# /path/to/package/static.py:
INITIAL = 0
PROCESSING = 1
PROCESSED = 2
DECLINED = 3
RETURNED = 4
...
...or as class-level attributes defined in their own class:
class MyModelStates:
INITIAL = 0
PROCESSING = 1
PROCESSED = 2
DECLINED = 3
RETURNED = 4
That helps you refer to those states by their mnemonic names, while they persist in your storage as simple integers. By this, you get rid of magic numbers scattered through your code and make it more readable and self-descriptive.
But, both the module-level constant and the class with the static attributes suffer from the inherent nature of python objects: they are all mutable. You may accidentally assign a value to your constant at runtime, and that is a mess to debug and rollback your broken entities. So, you might want to make your set of constants immutable, which means both the number of constants declared and the values they are mapped to must not be modified at runtime.
A couple of reader alerts:
In order to (somewhat) simplify the description process and tighten the volume of the article we are going to write, it is essential to make a significant remark and state the primary constraint right away — everything we are going to tell you today on the practical side of the problematics is viable only in terms of TLS 1.3. Meaning that while your ECDSA certificate would still work in TLS 1.2 if you wish it worked, providing backwards compatibility, the description of the actual handshake process, cipher suits and client-server benchmarks covers TLS 1.3 only. Of course, this does not relate to the mathematical description of algorithms behind modern encryption systems.
This article was written by neither a mathematician nor an engineer — although those helped to find a way around scary math and reviewed this article. Many thanks to Qrator Labs employees.
The Diffie–Hellman legacy in the 21 century
Of course, this has started with neither Diffie nor Hellman. But to provide a correct timeline, we need to point out main dates and events.
There were several major personas in the development of modern cryptography. Most notably, Alan Turing and Claud Shannon both laid an incredible amount of work over the field of theory of computation and information theory as well as general cryptanalysis, and both Diffie and Hellman, are officially credited for coming up with the idea of public-key (or so-called asymmetric) cryptography (although it is known that in the UK there were made serious advances in cryptography that stayed under secrecy for a very long time), making those two gentlemen pioneers.
In what exactly?
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Best news, articles and scientific papers published since August 12 till 18 are below.
TL;DR: Client-server architecture of our internal configuration management tool, QControl.
At its basement, there’s a two-layered transport protocol working with gzip-compressed messages without decompression between endpoints. Distributed routers and endpoints receive the configuration updates, and the protocol itself makes it possible to install intermediary localized relays. It is based on a differential backup (“recent-stable,” explained further) design and employs JMESpath query language and Jinja templating for configuration rendering.
Qrator Labs operates on and maintains a globally distributed mitigation network. Our network is anycast, based on announcing our subnets via BGP. Being a BGP anycast network physically located in several regions across the Earth makes it possible for us to process and filter illegitimate traffic closer to the Internet backbone — Tier-1 operators.
On the other hand, being a geographically distributed network bears its difficulties. Communication between the network points-of-presence (PoP) is essential for a security provider to have a coherent configuration for all network nodes and update it in a timely and cohesive manner. So to provide the best possible service for customers, we had to find a way to synchronize the configuration data between different continents reliably.
In the beginning, there was the Word… which quickly became communication protocol in need of an upgrade.
This post represents a regular Cybersecurity Newsletter issue, available at the dedicated subscribe page.
This time, we are between August 5 and 11 with the best articles, blog posts, and preprints.
This blogpost represents a regular Cybersecurity Newsletter issue, available at the dedicated subscribe page.
This time, we're between July 29 and August 3 with the best articles posted.
