venerdì 7 giugno 2019

Various SDR OS / Distro / LiveOS / Virtual Machine / Bootable Linux image

Various SDR OS / Distro / LiveOS / Virtual Machine / Bootable Linux image

below are some operating systems, virtual machines, file names and related descriptions useful for online research of those who want to manage SDR hardware and radio signals.




GNU Radio Live SDR Environment
  • ubuntu-14.04.1-desktop-amd64-gnuradio-3.7.6.1.iso
  • ubuntu-14.04.1-desktop-amd64-gnuradio.iso
  • ubuntu-14.04.4-desktop-amd64-gnuradio-3.7.9.2.iso
  • ubuntu-16.04.2-desktop-amd64-gnuradio-3.7.11.iso
  • ubuntu-14.04.5-desktop-amd64-gnuradio-3.7.10.1.iso
Description: The GNU Radio Live SDR Environment, produced by Corgan Labs, is a bootable Ubuntu Linux DVD or USB drive image, with GNU Radio and third party software pre-installed. It is designed for quick and easy testing and experimentation with GNU Radio without having to make any permanent modifications to a PC or laptop. It does not, however, provide for permanent installation.
It is supplied as an ISO image to be downloaded and burned onto a recordable DVD disc or copied to a USB flash drive using a utility such as the Ubuntu Startup Disk Creator (Ubuntu Linux OS) or Unetbootin (Windows, MacOS, Linux). Creating a USB drive from the image will provide much faster booting and operation, and allow making changes and storing files. Finally, the ISO image may be booted within a virtual environment such as VirtualBox, QEMU/kvm, VMware, or Parallels.


RTL-SDR/HackRF Live DVD
  • ubuntu-12.04.2-custom-sdr-amd64.iso
  • ubuntu-12.04.3-desktop-amd64-gnuradio-2013-0926.iso
  • ubuntu-12.04.3-desktop-amd64-gnuradio-2013-1110.iso
Description:  If you’ve been wanting to use your RTL-SDR or HackRF on Linux, but didn’t know how to or couldn’t be bothered installing all the software, there is now a live DVD downloadable thanks to Reddit user rtl_sdr_is_fun. With a live DVD you can boot into an Ubuntu OS (with many pre-installed SDR related programs) directly from the DVD without the need to install anything.
The Live DVD is only available for 64-bit CPUs.


SigintOS
  • sigintos.iso
  • sigintos-1.1.iso
Description: SigintOS; as the name suggests, SIGINT is an improved Linux distribution for Signal Intelligence. This distribution is based on Ubuntu Linux. It has its own software called SigintOS. With this software, many SIGINT operations can be performed via a single graphical interface.
Hardware and software installation problems faced by many people interested in signal processing are completely eliminated with SigintOS. HackRF, BladeRF, USRP, RTL-SDR are already installed, and the most used Gnuradio, Gsm and Gps applications are also included in the distribution.


Skywavelinux
  • skywavelinux-1.0.iso
  • skywavelinux-2.1.iso
  • skywavelinux-2.2.iso
Description: Skywave Linux is an operating system using bleeding-edge technology to robustly access broadcast, utility, military, and amateur radio signals from almost anywhere in the world, including countries with restrictive internet environments. Skywave Linux connects to a large and growing network of state-of-the art software defined radio (SDR) servers, making it possible to experience high performance SDR operation without your own large antennas or on-site radio hardware. All you need to do is boot the system on a computer with internet connectivity. Skywave Linux can also operate numerous types of SDR hardware, plugged in or on the local network. Downloading, installing and configuring SDR software can be difficult for many computer users; Skywave Linux eliminates the hassle by including several applications installed, configured, and ready to run.


Ubuntu-remix
  • ubuntu-remix-14-32bit.iso
  • ubuntu-remix-14-64bit.iso
Description: This is a remastered version of Ubuntu Linux. There are 32-bit and 64-bit versions available, as well as an (older) image for the PengPod 1000.
This version contains a lot of amateur radio software including Fldigi, NBEMS, Gpredict, earthtrack, xcwcp and qrq, XLog and cqrlog, flrig and grig, xnec2c, fl_moxgen, aa-analyzer, owx, VOACAP, glfer, Xastir, gqrx, gEDA, GNU Radio Companion, quisk, direwolf, linamc, FreeDV, wsjt-x, Micro-Fox 15 Config, and a TinyTrak3 configuration program.
Version 16 is updated to match Ubuntu 14.01.1 LTS, including updated packet radio software and repairs to VOACAP.
This software collection uses the icewm window manager with menus customized for Amateur Radio use. It is designed to be light weight to run on older computers, while still having modern functionality.
Recommended: 1GHz CPU and 1GB memory at an absolute bare minimum (SDR applications will require more). 


KB1OIQ - Andy's Ham Radio Linux
  • andy-v17-32bit.iso
  • andy-v17-64bit.iso
Description: This is a remastered version of Ubuntu Linux. There are 32-bit and 64-bit versions available, as well as an (older) image for the PengPod 1000.
This version contains a lot of amateur radio software including Fldigi, NBEMS, Gpredict, earthtrack, xcwcp and qrq, XLog and cqrlog, flrig and grig, xnec2c, fl_moxgen, aa-analyzer, owx, VOACAP, glfer, Xastir, gqrx, gEDA, GNU Radio Companion, quisk, direwolf, linamc, FreeDV, wsjt-x, Micro-Fox 15 Config, and a TinyTrak3 configuration program.
Version 16 is updated to match Ubuntu 14.01.1 LTS, including updated packet radio software and repairs to VOACAP.
This software collection uses the icewm window manager with menus customized for Amateur Radio use. It is designed to be light weight to run on older computers, while still having modern functionality.
Recommended: 1GHz CPU and 1GB memory at an absolute bare minimum (SDR applications will require more).


Debian Hamradio Pure Blend
  • debian-live-8.5.0-amd64-hamradio.iso
  • debian-live-8.5.0-i386-hamradio.iso
Description: The Debian Hamradio Pure Blend is a project of the Debian Hamradio Maintainers Team who collaborate on maintenance of amateur-radio related packages for Debian. Every Pure Blend is a subset of Debian that is configured to support a particular target group out-of-the-box. This blend aims to support the needs of radio amateurs.


Shackbox
  • shackbox_premium.iso

Description: Shackbox is an open source, out-of-the-box and totally free Live Linux distribution that provides over 150 applications for Ham radio operators, trunking software, antenna design apps, and a lot of other applications related to electronics.
Shackbox is based on the Ubuntu Linux operating system, but without the Unity user interface and all the KDE related applications. In addition the distro offers SDR support for rtl2832 devices and a GNU Radio companion plugin.


Tetra Live Monitor

Description: telive - Tetra Live Monitor (c) 2014-2015 Jacek Lipkowski sq5bpf@lipkowski.org
telive is a program which can be used to display information like signalling, calls etc from a Tetra network. It is also possible to log the signalling information, listen to the audio in realtime and to record the audio. Playing the audio and recompressing it into ogg is done via external scripts.


LilacSat2
  • lilacsat-2_livecd_20151010.iso

Pentoo
  • pentoo-i686-default-2015.0_RC3.7.iso
  • pentoo-i686-hardened-2015.0_RC3.7.iso

AttifyOS
  • AttifyOS1.3.ova
Description: AttifyOS is a penetration testing distro for security professionals to assess the security of Internet of Things (IoT) devices. The distro is based on LUbuntu and contains pre-configured tools to help you with your next IoT pentest.
Embedded software such as Binwalk, Attify Badge tool, Baudrate.py, Openocd, Flashrom, Spiflash.py.
Firmware and Software software such as Binwalk, Firmware-Mod-Kit (FMK), Firmware Analysis Toolkit (FAT), radare2, IDA Demo, Dex2Jar, JADx, ROPGadget.
Radio software such as GQRX, GNURadio, Ubertooth-Utils, HackRF, KillerBee / Attify ZigBee Framework,


Other famous Pentest LiveOS with SDR support package:

  • Kali
  • NetHunter
  • BackTrack

Virtual Machine Image:

  • KickSat
  • Ubuntu R36
  • Ubuntu R37


giovedì 6 giugno 2019

How to catch Charging station interface Device online with search engine like zoomeye shodan censys fofa

To capture Charging station interface Device online via search engines for Internet-connected devices is not difficult.

https://en.wikipedia.org/wiki/Charging_station

An electric vehicle charging station, also called EV charging station, electric recharging point, charging point, charge point, ECS (electronic charging station), and EVSE (electric vehicle supply equipment), is an element in an infrastructure that supplies electric energy for the recharging of plug-in electric vehicles—including electric cars, neighborhood electric vehicles and plug-in hybrids.
For charging at home or work, some EVs have onboard converters that can plug into a standard electrical outlet or a high-capacity appliance outlet. Others either require or can use a charging station that provides electrical conversion, monitoring, or safety functionality. These stations are also needed when traveling, and many support faster charging at higher voltages and currents than are available from residential EVSEs. Public charging stations are typically on-street facilities provided by electric utility companies or located at retail shopping centers, restaurants and parking places, operated by a range of private companies.
Charging stations provide a range of heavy duty or special connectors that conform to the variety of standards. For common rapid charging and DC, the Combined Charging System (CCS) is becoming the universal standard. Others are CHAdeMO, and the Type 2 connector.


Example link of search engines:

www.shodan.io

www.zoomeye.org
 
https://censys.io/

https://fofa.so/




Example code to search:
  • Charging station
  • Charging station interface
  • Charging station interface 4.32-4932
  • Charging station interface 4.33-4964
  • Charging station interface 4.40-5038
  • Charging station interface 4.31-4881
  • Charging station interface 4.34-4979
  • Charging station interface 4.52-5419


Fast search:

https://www.shodan.io/search?query=%22Charging+station%22
https://www.zoomeye.org/searchResult?q=%22Charging%20station%22
https://censys.io/ipv4?q=%22Charging+station%22
https://fofa.so/result?q="Charging+station"


https://www.shodan.io/search?query=%22Charging+station+interface%22
https://www.zoomeye.org/searchResult?q=%22Charging%20station%20interface%22
https://censys.io/ipv4?q=%22Charging+station+interface%22
https://fofa.so/result?q="Charging+station+interface"

https://www.shodan.io/search?query=%22Charging+station+interface+4.32-4932%22
https://www.zoomeye.org/searchResult?q=%22Charging%20station%20interface%204.32-4932%22
https://censys.io/ipv4?q=%22Charging+station+interface+4.32-4932%22
https://fofa.so/result?q="Charging+station+interface+4.32-4932"

https://www.shodan.io/search?query=%22Charging+station+interface+4.33-4964%22
https://www.zoomeye.org/searchResult?q=%22Charging%20station%20interface%204.33-4964%22
https://censys.io/ipv4?q=%22Charging+station+interface+4.33-4964%22
https://fofa.so/result?q="Charging+station+interface+4.33-4964"

https://www.shodan.io/search?query=%22Charging+station+interface+4.40-5038%22
https://www.zoomeye.org/searchResult?q=%22Charging%20station%20interface%204.40-5038%22
https://censys.io/ipv4?q=%22Charging+station+interface+4.40-5038%22
https://fofa.so/result?q="Charging+station+interface+4.40-5038"


it is very interesting to observe how the search results of the various search engines are very different ....

venerdì 19 aprile 2019

How to catch GPS Device online with search engine like shodan

How to catch GPS Device online with search engine like shodan

To capture GPS Device online via search engines for Internet-connected devices is not difficult.

Example link of search engines:

www.shodan.io
www.zoomeye.org

Example code to search:

  • AIVDM
  • AIVDO
  • NMEA
  • GPRMC
  • GPGGA
  • GPZDA
  • GPVTG
  • GPGSA
  • GPGLL
  • GPGSA
  • GPGSV
  • GNSS
  • RTCM3
  • RTCM3X
  • RTCM2
  • RTCM
  • GPS
  • GLONASS
  • BKGNtripcaster
  • FFFREMONT
  • Leica+GPS
  • Leica+GNSS
  • TMP_OUTERNET
  • POPNet+GNSS
  • GLONASS
  • Galileo
  • BeiDou
  • QZSS
  • IRNSS
  • SBAS
  • GNSS
  • GLO
  • Trimble+GPS
  • Trimble+GNSS
  • DGNSS
  • SWEPOS
  • GNSS Server
  •  VRS+GPS
  •  FReDNet
  •  ETRF2000

Fast search:

https://www.shodan.io/search?query=AIVDM
https://www.zoomeye.org/searchResult?q=AIVDM

https://www.shodan.io/search?query=AIVDO
https://www.zoomeye.org/searchResult?q=AIVDO

https://www.shodan.io/search?query=NMEA
https://www.zoomeye.org/searchResult?q=NMEA

https://www.shodan.io/search?query=GPRMC
https://www.zoomeye.org/searchResult?q=GPRMC

https://www.shodan.io/search?query=GPGGA
https://www.zoomeye.org/searchResult?q=GPGGA

https://www.shodan.io/search?query=GPZDA
https://www.zoomeye.org/searchResult?q=GPZDA

https://www.shodan.io/search?query=GPVTG
https://www.zoomeye.org/searchResult?q=GPVTG

https://www.shodan.io/search?query=GPGSA
https://www.zoomeye.org/searchResult?q=GPGSA

https://www.shodan.io/search?query=GPGLL
https://www.zoomeye.org/searchResult?q=GPGLL

https://www.shodan.io/search?query=GPGSA
https://www.zoomeye.org/searchResult?q=GPGSA

https://www.shodan.io/search?query=GPGSV
https://www.zoomeye.org/searchResult?q=GPGSV

https://www.shodan.io/search?query=GNSS
https://www.zoomeye.org/searchResult?q=GNSS

https://www.shodan.io/search?query=RTCM3
https://www.zoomeye.org/searchResult?q=RTCM3

https://www.shodan.io/search?query=RTCM3X
https://www.zoomeye.org/searchResult?q=RTCM3X

https://www.shodan.io/search?query=RTCM2
https://www.zoomeye.org/searchResult?q=RTCM2

https://www.shodan.io/search?query=RTCM
https://www.zoomeye.org/searchResult?q=RTCM

https://www.shodan.io/search?query=GPS
https://www.zoomeye.org/searchResult?q=GPS

https://www.shodan.io/search?query=GLONASS
https://www.zoomeye.org/searchResult?q=GLONASS

https://www.shodan.io/search?query=BKGNtripcaster
https://www.zoomeye.org/searchResult?q=BKGNtripcaster

https://www.shodan.io/search?query=FFFREMONT
https://www.zoomeye.org/searchResult?q=FFFREMONT

https://www.shodan.io/search?query=Leica+GPS
https://www.zoomeye.org/searchResult?q=Leica+GPS

https://www.shodan.io/search?query=Leica+GNSS
https://www.zoomeye.org/searchResult?q=Leica+GNSS

https://www.shodan.io/search?query=TMP_OUTERNET
https://www.zoomeye.org/searchResult?q=TMP_OUTERNET

https://www.shodan.io/search?query=POPNet+GNSS
https://www.zoomeye.org/searchResult?q=POPNet+GNSS

https://www.shodan.io/search?query=GLONASS
https://www.zoomeye.org/searchResult?q=GLONASS

https://www.shodan.io/search?query=Galileo
https://www.zoomeye.org/searchResult?q=Galileo

https://www.shodan.io/search?query=BeiDou
https://www.zoomeye.org/searchResult?q=BeiDou

https://www.shodan.io/search?query=QZSS
https://www.zoomeye.org/searchResult?q=QZSS

https://www.shodan.io/search?query=IRNSS
https://www.zoomeye.org/searchResult?q=IRNSS

https://www.shodan.io/search?query=SBAS
https://www.zoomeye.org/searchResult?q=SBAS

https://www.shodan.io/search?query=GNSS
https://www.zoomeye.org/searchResult?q=GNSS

https://www.shodan.io/search?query=GLO
https://www.zoomeye.org/searchResult?q=GLO

https://www.shodan.io/search?query=Trimble+GPS
https://www.zoomeye.org/searchResult?q=Trimble+GPS

https://www.shodan.io/search?query=Trimble+GNSS
https://www.zoomeye.org/searchResult?q=Trimble+GNSS

https://www.shodan.io/search?query=DGNSS
https://www.zoomeye.org/searchResult?q=DGNSS

https://www.shodan.io/search?query=SWEPOS
https://www.zoomeye.org/searchResult?q=SWEPOS

https://www.shodan.io/search?query=GNSS+Server
https://www.zoomeye.org/searchResult?q=GNSS+Server

https://www.shodan.io/search?query=VRS+GPS
https://www.zoomeye.org/searchResult?q=VRS+GPS

https://www.shodan.io/search?query=FReDNet
https://www.zoomeye.org/searchResult?q=FReDNet

https://www.shodan.io/search?query=ETRF2000
https://www.zoomeye.org/searchResult?q=ETRF2000

Link decoder online:

to decode AIVDM / AIVDO message online:

https://rl.se/aivdm
http://catb.org/gpsd/AIVDM.html

to decode NMEA message online:

http://freenmea.net/decoder

to decode GPRMC / GPGGA message online:

https://rl.se/gprmc


Varoious Link:

http://www.rtcm-ntrip.org/home

http://www.euref-ip.net/home


Product:

https://leica-geosystems.com/en-US/products/gnss-reference-networks

https://www.trimble.com/Real-Time-Networks/Trimble-NetR9.aspx

https://www.topconpositioning.com/epp_gnss_eu

giovedì 11 aprile 2019

TRACKING DICTATORS AROUND THE WORLD WITH ADS-B DATA - SHODANnoDICTATORSHIPS

I read the article:

https://www.rtl-sdr.com/tracking-dictators-around-the-world-with-ads-b-data/

very interested and would like to contribute to the collection of information. some time ago I published how to intercept online information on GPS devices with search engines like shodan and zoomeye. some of this information related to GPS is related to aeronautical technologies. the links of the publications are:


https://giammaiot.blogspot.com/2019/02/how-to-catch-sdr-receiver-online-with.html

https://giammaiot.blogspot.com/2019/01/how-to-catch-sdr-online-with-search.html


precisely, I would like to highlight these researches:

https://www.shodan.io/search?query=ICAO
https://www.zoomeye.org/searchResult?q=ICAO

you might find interesting things even with the following searches:

https://www.shodan.io/search?query=ADS-B
https://www.zoomeye.org/searchResult?q=ADS-B

https://www.shodan.io/search?query=PiAware
https://www.zoomeye.org/searchResult?q=PiAware

https://www.shodan.io/search?query=ATFM
https://www.zoomeye.org/searchResult?q=ATFM

https://www.shodan.io/search?query=S%2FMLAT
https://www.zoomeye.org/searchResult?q=S%2FMLAT

https://www.shodan.io/search?query=notams
https://www.zoomeye.org/searchResult?q=notams

https://www.shodan.io/search?query=CPDLC
https://www.zoomeye.org/searchResult?q=CPDLC

https://www.shodan.io/search?query=ADS%C
https://www.zoomeye.org/searchResult?q=ADS%C

https://www.shodan.io/search?query=UAT
https://www.zoomeye.org/searchResult?q=UAT

https://www.shodan.io/search?query=1090ES
https://www.zoomeye.org/searchResult?q=1090ES

https://www.shodan.io/search?query=TCAS
https://www.zoomeye.org/searchResult?q=TCAS

https://www.shodan.io/search?query=TIS%B
https://www.zoomeye.org/searchResult?q=TIS%B

https://www.shodan.io/search?query=METAR
https://www.zoomeye.org/searchResult?q=METAR

https://www.shodan.io/search?query=TAF
https://www.zoomeye.org/searchResult?q=TAF


a further publication that could be useful is the following:

https://giammaiot.blogspot.com/2019/01/how-to-catch-sdr-online-with-search.html

Good Researches

martedì 2 aprile 2019

ZR6AIC: How to use AI (Artificial Intelligence) to identify Radio signals using a RTL SDR dongle and Linux (Ubuntu) Identifying Radio stations

ZR6AIC: How to use AI (Artificial Intelligence) to identif...: How to use AI (Artificial Intelligence) to identify Radio signals using a RTL SDR dongle and Linux (Ubuntu) Identifying Radio stations ...



How to use AI (Artificial Intelligence) to identify Radio signals using a RTL SDR dongle and Linux (Ubuntu)


How to use AI (Artificial Intelligence) to identify Radio signals using a RTL SDR dongle and Linux (Ubuntu)

Identifying Radio stations


I was wondering if there is not a good framework to identify RF signals
as I wanted to add some capabilities to my SDR's to identify RF signal.



I was thinking of a way to recognize Satellite signals and the
automatically apply the necessary Demodulator's and decoders for the
specific satellite.



I was looking at AI Deep Learning library to be able to identify RF
Radio signals. There are countless deep learning frameworks available
today.



By using Python3 and rtl-sdr dongle it would be possible to scan a frequency range trying to identify a satellite.



Here is a graph with all the most used Deep learning frameworks available.

Deep Learning Frameworks.


I found this opensource project called cnn-rtlsdr and it is available from github here https://github.com/randaller/cnn-rtlsdr



This framework is using Keras and TensorFlow to learn and recognize the RF signals.



So how dose it work?

You first need take an clean RF signal and digitize it and then let the
framework learn its signature. The more you letting the AI framework
learn a specific signal the more accurate it will able to recognize the
RF Signal.







Here is my instillation procedure to get it working on my Ubuntu 18.10 Laptop

Installation Procedure.

Lets check if you have version 2 or 3 of python.

You need version 3
python -V

apt-get install git
git clone https://github.com/randaller/cnn-rtlsdr.git
cd cnn-rtlsdr





sudo apt-get update


sudo apt-get install python3-pip
sudo apt-get install rtl-sdr


sudo apt-get install build-essential libssl-dev libffi-dev python-dev

sudo pip3 install --upgrade pip

sudo pip3 install tensorflow
sudo pip3 install pyrtlsdr


sudo pip3 install scipy

[remove dongle]
rmmod dvb_usb_rtl28xxu rtl2832
[insert dongle]




Installing rtl-sdr and calibrating the frequency offset.

Using the Kal utility to calibrate your dongle offset using the GSM network.

Installing Kal

sudo apt-get install automake
sudo apt-get install libtool
sudo apt-get install libfftw3–dev
sudo apt-get install librtlsdr-dev
sudo apt-get install libusb1.0.0-dev


git clone https://github.com/steve-m/kalibrate-rtl.git

cd kalibrate-rtl/

./bootstrap
 ./configure
 make
 sudo make install




In south Africa we can use the GSM900 frequency

Lets run Kal

kal -s GSM900
Found 1 device(s):
  0:  Generic RTL2832U OEM

Using device 0: Generic RTL2832U OEM
Found Rafael Micro R820T tuner
Exact sample rate is: 270833.002142 Hz
[R82XX] PLL not locked!
kal: Scanning for GSM-900 base stations.
GSM-900:
    chan: 40 (943.0MHz - 736Hz)    power: 25909.17
    chan: 47 (944.4MHz - 817Hz)    power: 28430.99
    chan: 63 (947.6MHz - 128Hz)    power: 29010.57
    chan: 69 (948.8MHz - 597Hz)    power: 32479.73


We now select the strongest Station to measure the average frequency offset

kal -c 69
Found 1 device(s):
  0:  Generic RTL2832U OEM

Using device 0: Generic RTL2832U OEM
Found Rafael Micro R820T tuner
Exact sample rate is: 270833.002142 Hz
[R82XX] PLL not locked!
kal: Calculating clock frequency offset.
Using GSM-900 channel 69 (948.8MHz)
average        [min, max]    (range, stddev)
- 413Hz        [-460, -354]    (106, 30.402500)
overruns: 0
not found: 0
average absolute error: 0.435 ppm






We now need to test to see if we can identify any signals using the default test learn data.

Final test

The Default script will scan the normal FM broadcast band 88 to 108Mhz.

Although it detects the radio stations as TV is ok as the test data id was tv.



sudo python3 predict_scan.py
Found Rafael Micro R820T tuner
[R82XX] PLL not locked!
88.400 MHz - tv 99.98%
89.600 MHz - tv 99.91%
91.500 MHz - tv 99.99%
92.700 MHz - tv 99.93%
94.700 MHz - tv 99.13%
95.900 MHz - tv 98.04%
98.000 MHz - tv 100.00%
99.200 MHz - tv 99.95%
99.600 MHz - tv 81.13%
101.500 MHz - tv 99.91%
102.700 MHz - tv 100.00%
105.100 MHz - tv 100.00%
106.300 MHz - tv 99.56%






We now need to learn the different Rf signals so we can identify it.

Best way to do this is with an rtl dongle and your signal of interest.



Learning from existing RF signal Database.

1) "wfm" Wide band FM
2) "tv" TV signal
3) "gsm" GSM signal
4) "tetra" Tetra DMR
5) "dmr" DMR
5) "other"

Link to database https://drive.google.com/file/d/1PuhzXkk6AVwXPPKjtFUCpQVsqOOlszu8/view

Some
RF signals have been learned by other users so you don't need to learn
the common RF signals but just import the learn database.

Unzip the file in the cnn-rtlsdr directory

Then run the following command to learn the RF signal

It takes about 80secons to learn a sample. So go and have a coffee or a bear :-)

Make sure you have your rtl_sdr dongle connected as the code will do a test at the end of the learning procedure.

python3 train_keras.py

You
will need a lot of memory for your application tu run so close all
necessary applications otherwise you will get an out of memory error..

Learning RF samples for the following RF signals.
When the learning is complete the script will do a test with the RTL-sdr dongle.

Testing signals with the new database. 





Lets learn our own signal not yet in database.

I want to learn a Satellite Telemetry signal from Satellite.



Learning my own unique signal.





python3 train_keras.py
Using TensorFlow backend.
WARNING:tensorflow:From

/usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1062:
calling reduce_prod (from tensorflow.python.ops.math_ops) with
keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
WARNING:tensorflow:From

/usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:2550:
calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims
is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
WARNING:tensorflow:From

/usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:1123:
calling reduce_mean (from tensorflow.python.ops.math_ops) with
keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
Train on 64972 samples, validate on 27844 samples
Epoch 1/50
64972/64972 [==============================] - 70s - loss: 0.3469 - acc: 0.8527 - val_loss: 0.0716 - val_acc: 0.9836
Epoch 2/50
64972/64972 [==============================] - 72s - loss: 0.0575 - acc: 0.9839 - val_loss: 0.0731 - val_acc: 0.9791



...

64972/64972 [==============================] - 79s - loss: 0.0016 - acc: 0.9995 - val_loss: 0.0069 - val_acc: 0.9984
Epoch 49/50
64972/64972 [==============================] - 80s - loss: 7.5126e-04 - acc: 0.9998 - val_loss: 0.0093 - val_acc: 0.9981
Epoch 50/50
64972/64972 [==============================] - 78s - loss: 0.0065 - acc: 0.9983 - val_loss: 0.0357 - val_acc: 0.9923

Found Rafael Micro R820T tuner
[R82XX] PLL not locked!
92.9 wfm 99.9636411667
49.25 other 99.8086333275
95.0 other 99.9997735023
104.0 other 99.9999880791
422.6 other 99.9927401543
100.5 other 99.9997496605
120.0 other 100.0
106.3 wfm 100.0
942.2 other 99.999666214
107.8 other 100.0
Validation: 30.0

How to catch various Petrol information online with search engine like shodan - PetrolShodan

Online you can find interesting information about traffic, storage and management of petroleum products.



Example link of search engines:

www.shodan.io
www.zoomeye.org

Example code to search:


  • fuel tank
  • TC-VOLUME
  • TANK PRODUCT
  • TANK VOLUME
  • TANK PETROL
  • VOLUME PETROL
  • Oil Terminals
  • TANK PORT
  • Diesel Kero
  • US Oil
  • I20100



Fast search:

https://www.shodan.io/search?query=fuel+tank
https://www.zoomeye.org/searchResult?q=fuel+tank

https://www.shodan.io/search?query=TC-VOLUME
https://www.zoomeye.org/searchResult?q=TC-VOLUME

https://www.shodan.io/search?query=TANK+PRODUCT
https://www.zoomeye.org/searchResult?q=TANK+PRODUCT

https://www.shodan.io/search?query=TANK+VOLUME
https://www.zoomeye.org/searchResult?q=TANK+VOLUME

https://www.shodan.io/search?query=TANK+PETROL
https://www.zoomeye.org/searchResult?q=TANK+PETROL

https://www.shodan.io/search?query=VOLUME+PETROL
https://www.zoomeye.org/searchResult?q=VOLUME+PETROL

https://www.shodan.io/search?query=Oil+Terminals
https://www.zoomeye.org/searchResult?q=Oil+Terminals

https://www.shodan.io/search?query=TANK+PORT
https://www.zoomeye.org/searchResult?q=TANK+PORT

https://www.shodan.io/search?query=Diesel+Kero
https://www.zoomeye.org/searchResult?q=Diesel+Kero

https://www.shodan.io/search?query=US+Oil
https://www.zoomeye.org/searchResult?q=US+Oil

https://www.shodan.io/search?query=I20100
https://www.zoomeye.org/searchResult?q=I20100





mercoledì 13 marzo 2019

How to catch IoT NB-IOT Network online Device, Client, Server, API, Gateway , Simulator, Platform developer like Sigfox Lora LoraWAN with search engine like Shodan

How to catch IoT NB-IOT Network online Device, Client, Server, API, Gateway , Simulator, Platform developer  like Sigfox Lora LoraWAN with search engine like Shodan


Example link of search engines:

www.shodan.io
www.zoomeye.org


Example code to search:

  • lora smart -GIT
  • IoT Device Simulator
  • iot gateway
  • sigfox
  • lora
  • lorawan
  • lora gateway
  • lorawan server
  • NB-IOT
  • gateway IOT network
  • IoT Network Gateway
  • ESP8266


Fast search:

https://www.shodan.io/search?query=lora+smart+-GIT
https://www.zoomeye.org/searchResult?q=lora+smart+-GIT

https://www.shodan.io/search?query=IoT+Device+Simulator
https://www.zoomeye.org/searchResult?q=IoT+Device+Simulator

https://www.shodan.io/search?query=iot+gateway
https://www.zoomeye.org/searchResult?q=iot+gateway

https://www.shodan.io/search?query=sigfox
https://www.zoomeye.org/searchResult?q=sigfox

https://www.shodan.io/search?query=lora
https://www.zoomeye.org/searchResult?q=lora

https://www.shodan.io/search?query=lorawan
https://www.zoomeye.org/searchResult?q=lorawan

https://www.shodan.io/search?query=lora+gateway
https://www.zoomeye.org/searchResult?q=lora+gateway

https://www.shodan.io/search?query=lorawan+server
https://www.zoomeye.org/searchResult?q=lorawan+server

https://www.shodan.io/search?query=NB-IOT
https://www.zoomeye.org/searchResult?q=NB-IOT

https://www.shodan.io/search?query=gateway+IOT+network
https://www.zoomeye.org/searchResult?q=gateway+IOT+network

https://www.shodan.io/search?query=IoT+Network+Gateway
https://www.zoomeye.org/searchResult?q=IoT+Network+Gateway

https://www.shodan.io/search?query=ESP8266
https://www.zoomeye.org/searchResult?q=ESP8266

Various NB-Iot network:

  • LPWAN
  • 6LoWPAN
  • Sigfox
  • LoRa / LoRaWAN
  • NB-Fi
  • Weightless
  • DASH7
  • LTE User Equipment Categories
  • Multefire
  • LTE sidelink
  • NB-IOT


Link:

https://en.wikipedia.org/wiki/Narrowband_IoT