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

Various Universal Cloning Remote Control Duplicator Multi Frequency Wireless ISM Band 280 315 390 418 433 868 Mhz and others

Various Universal Cloning Remote Control Duplicator Multi Frequency Wireless ISM Band 280 315 390 418 433 868 Mhz and others


A short list of universal multi-frequency radio controls to have fun and study with SDR software and others


Tag:

  • Key Fob
  • Keyfob
  • Garage Door Gate Opener
  • Auto Scan
  • Alarm
  • Universal Cloning Remote Control Duplicator


Image:











Link:









domenica 10 marzo 2019

Various radio signal identification guides online and software

 Various radio signal identification guides



WAVECOM Decoder Online Help 10.0.0

http://www.wavecom.ch/content/ext/DecoderOnlineHelp/default.htm


Sigidwiki: Signal Identification Guide

https://www.sigidwiki.com/wiki/Signal_Identification_Guide


ARTEMIS: Free Signal Identification Software

http://markslab.tk/project-artemis/


Signal Identification

https://www.hfunderground.com/wiki/Signal_Identification


Identify the growing number of new & unusual sounds they might hear when monitoring outside the amateur bands:

http://www.w2sjw.com/radio_sounds.html