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metasploitable3-download-instructions

This is the instruction on how to download the metasploitable3 successfully

References include:

Additional information

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git_practice

My notebook for git tutorial

1.Delete a branch

show the current working branch:

git branch

show all the branches:

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cuckoo-download-instructions

Coming from my article on medium Cuckoo Configuration

This is the article about how to download and deploy the cuckoo for malware analysis. It took me around two months to figure it out(only with weekends of course). The host machine is win10 with ubuntu WSL and the guset machine is win7X64.

Attention:

When you download the python, make sure it is v2X. Cuckoo can only be run with python2X. So when you download any libraries with pip, make sure the pip is version2.

The commands to check the version:

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airflow_complete_tutorial

The right way to initialize the airflow from the beginning

1.build your workplace

  mkdir xx/airflow_test

2. build the virtual environment

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1 Download zeek correctly.

Step1 - Download the dependencies!

According to the installing instructions on zeek.

Step2 - Setting the environment!

Before you go through the ./configure step, setting the path first. If not, you won't be able to use it normally.

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1. Download

Download the server side:

sudo apt-get install argus-server

And open the daemon then:

sudo argus -P 561 -d -w test.argus

Then leave it.

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Linux-trouble-shouting

Full Screen:

# if the auto pop up does not work, try
sudo sh ./VboxLinuxAdditions.run

1. Kill the processing with specified names:

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from sklearn.linear_model import Lasso
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import MinMaxScaler

from regression_model.processing import preprocessors
from regression_model.processing import features
from regression_model.config import config

import logging

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import tensorflow as tf


mnist = tf.keras.datasets.mnist


(x_train, y_train),(x_test, y_test) = mnist.load_data()
# this is the class can stop the epochs when the condition is acceptable
class myCallback(tf.keras.callbacks.Callback):
  def on_epoch_end(self, epoch,logs={}):

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1. Check the live docker instances:

docker ps

2. Stop an instance with the container ID:

docker stop 71f1db29d705 

3. Show all the docker images: