ericfourrier

• nmap 192.168.1.0/24: This scans the entire class C range
• nmap -p <port ranges>: This scans specific ports
• nmap -sP 192.168.1.0/24: This scans the network/find servers and devices that are running
• sudo nmap -sP 192.168.1.0/24 : Using sudo can be necessary on mac to get the MAC Adress
• nmap -O 192.168.1.1-42 : Scan from port 1 to 42
• nmap -O 192.168.1.150 :# Os detection with target ip
• nmap –iflist: This shows host interfaces and routes
• nmap –sV 192.168.1.1: This detects remote services' version numbers
• nmap –sS 192.168.1.1: This performs a stealthy TCP SYN scan
• nmap –sO 192.168.1.1: This scans for the IP protocol

ericfourrier

#!/bin/sh
cd /tmp
wget http://archive.raspberrypi.org/debian/pool/main/r/raspi-config/raspi-config_20160210_all.deb
apt-get install libnewt0.52 whiptail parted triggerhappy lua5.1 alsa_utils
dpkg -i raspi-config_20160210_all.deb

ericfourrier

docker ps -a | grep 'weeks ago' | awk '{print $1}' | xargs --no-run-if-empty docker rm

ericfourrier

# scan all ports 
nmap -sP 192.168.1.0/24

# scan all ports and try to detect mac address
sudo nmap -sP 192.168.1.0/24

# scan list of posts 
nmap -O 192.168.1.1-42 # scan from 1 to 42

# Os detection 

ericfourrier

#History of logins
cat /var/log/auth.log

ericfourrier

df_season=df.groupby(df.date.dt.month)[colname].sum()
df_season=df.groupby(df.date.dt.dayofweek)[colname].sum()
df_season=df.groupby(df.date.dt.quarter)[colname].sum()
#etc

ericfourrier

scp -c blowfish -C username@ip:path_remote path_client

ericfourrier

SELECT table_schema AS "database_name", SUM(data_length + index_length) / 1024 / 1024 AS "Size (MB)" FROM information_schema.TABLES GROUP BY table_schema;

ericfourrier

# Quick look to the size of mysql of all databases
ls -lah /var/lib/mysql

ericfourrier

# Load library   ------------------------------------------------------------
library(dplyr)

# Basic functions to explore NA in Dataframe  --------------------------------------------------------------


# Identify all missing variables per columns 
countNaCol <- function(data) {
  result <- vapply(data,function(x) sum(is.na(x)),integer(1))
  result <- data.frame(Nbna = result, napercentage = round(result/nrow(data),3))