This document contains excerpts from my web server logs collected over a period of 7 years that shows various kinds of recon and attack vectors.
There were a total of 37.2 million lines of logs out of which 1.1 million unique HTTP requests (Method + URI) were found.
$ sed 's/^.* - - \[.*\] "\(.*\) HTTP\/.*" .*/\1/' access.log > requests.txt
There are multiple ways to get a full disk encrypted arch linux system on raspberry. In this tutorial, we will install a 64-bit arch linux armv8 system, using dropbear as ssh server for remote pre-boot unlocking of the root filesystem. However, it will still be possible to unlock and use the pi as usual, with a keyboard and monitor. We will also create an unencrypted partition in the installation process, usable as a rescue system.
Differences to the 32-bit arch linux arm version:
| """ | |
| Train a neural network to implement the discrete Fourier transform | |
| """ | |
| import matplotlib.pyplot as plt | |
| import numpy as np | |
| from tensorflow.keras.layers import Dense | |
| from tensorflow.keras.models import Sequential | |
| N = 32 | |
| batch = 10000 |
A list of useful commands for the FFmpeg command line tool.
Download FFmpeg: https://www.ffmpeg.org/download.html
Full documentation: https://www.ffmpeg.org/ffmpeg.html
Rich Hickey • 3 years ago
Sorry, I have to disagree with the entire premise here.
A wide variety of experiences might lead to well-roundedness, but not to greatness, nor even goodness. By constantly switching from one thing to another you are always reaching above your comfort zone, yes, but doing so by resetting your skill and knowledge level to zero.
Mastery comes from a combination of at least several of the following:
RDBMS-based job queues have been criticized recently for being unable to handle heavy loads. And they deserve it, to some extent, because the queries used to safely lock a job have been pretty hairy. SELECT FOR UPDATE followed by an UPDATE works fine at first, but then you add more workers, and each is trying to SELECT FOR UPDATE the same row (and maybe throwing NOWAIT in there, then catching the errors and retrying), and things slow down.
On top of that, they have to actually update the row to mark it as locked, so the rest of your workers are sitting there waiting while one of them propagates its lock to disk (and the disks of however many servers you're replicating to). QueueClassic got some mileage out of the novel idea of randomly picking a row near the front of the queue to lock, but I can't still seem to get more than an an extra few hundred jobs per second out of it under heavy load.
So, many developers have started going straight t
Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.
$ python -m SimpleHTTPServer 8000
| Latency Comparison Numbers (~2012) | |
| ---------------------------------- | |
| L1 cache reference 0.5 ns | |
| Branch mispredict 5 ns | |
| L2 cache reference 7 ns 14x L1 cache | |
| Mutex lock/unlock 25 ns | |
| Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
| Compress 1K bytes with Zippy 3,000 ns 3 us | |
| Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
| Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |