Ayer no llegué a publicar el post de El lado del mal, pero no es porque no estuviera trabajando. Estuve trabajando y mucho desde muy temprano, que es cuando más disfruto yo de ciclos de computación de calidad en mi CPU, pero cuando pude acabar con el trabajo que me había puesto se me había hecho muy tarde, así que decidí dejar para hoy la publicación del post.
No llegué a tiempo a publicar el post, pero sí que hice el trabajo que me había propuesto, que no era otro que hacer una lista de "Las 50 mejores conferencias de Chema Alonso" en mi Canal Youtube, de esas que me gustan a mí y a mi mamá, y que dejé publicado.
Me he pasado el día seleccionando las 50 charlas que más me gustan de las que he dado... Algunas son muy viejas, pero las tengo mucho cariño. Por si queréis ver alguna, estas son para mí (y para mi mamá) las 50 mejores conferencias de Chema Alonso https://t.co/Sb4UifVGSy so far
No están todas las charlas, y alguna que he dejado fuera por ahora porque había decidido que solo fueran 40 los vídeos que tenían que estar, pero a lo mejor los cambio con el tiempo. Tampoco las he ordenado por ahora en un orden temático o especial, pero puede que lo haga en el futuro. Y también puede que luego haga una lista del Top 10, y lo mismo hago que esta lista de 50 acaba siendo de 10. Ya veremos.
Lo que sí es cierto es que ahora tienes esa lista con las 50 charlas que he elegido - y hay algunas de 3 minutos, otras de 5 minutos y otras de más de una hora -, pero si quieres verte "La Serie Completa", tienes temporada a temporada, todas las series ordenadas cronológicamente en listas. Los vídeos de charlas comienzan en el año 2007 - no he conseguido vídeos anteriores - donde está la primera charla de LDAP Injection & Blind LDAP Injectiony unWebcast de ISA Server 2006. Y así hasta2020con la charla deGremlin Botnetsy las que vaya a dar este año.
También tengo otras listas para entrevistas a cosas temáticas, y los vídeos que usamos en los artículos, y otros vídeos con explicaciones puntuales, pero subido al escenario dando charlas, tienes todo el material que he sido capaz de recuperar en esas listas, para que encuentres la charla que quieres ver.
El teletrabajo está demostrado que puedes ser más eficiente para las empresas de lo que la mayoría de las organizaciones pensaba hasta hace unos meses. Pero también puede traer consigo un incremento de "leaks" de información confidencial si no tenemos cuidado con la manera de implementarlo. Inspirándome en el post que escribí sobre el "Google Dorks & Low Hanging Fruit: Open Redirects" podría decirse que esta es una segunda parte, ya que vamos a usar dorks similares para encontrar "trufas" en una de las plataformas que más está dando que hablar últimamente en la comunidad: Github
Figura 1: GitHub Dorks: Buscando "Trufas" en GitHub usando TrufleHog & GitRob
Github es una plataforma para desarrolladores donde pueden compartir código en diferentes lenguajes de programación. En ella se permite editar simultáneamente un proyecto, lo que resulta de gran utilidad en escenarios de teletrabajo, pero si no se usa con cuidado, también presenta una gran amenaza a la seguridad de las empresas, ya que en este entorno es relativamente sencillo que a alguien se le termine escapando en el código que sube alguna KEY, algún TOKEN o contraseña…
Y ahí viene la gracia, es un entorno fantástico para aplicar todas las técnicas de Hacking con Buscadores, pero en este caso dentro de la plataforma de GitHub, así que vamos a ver cuáles son sus posibilidades. En esta plataforma cuenta con un buscador con multitud de comandos, entre los más útiles destacaría:
Figura 3: Comandos de búsqueda en GitHub
Como podéis ver, se pueden utilizar comandos bastante específicos para localizar cosas jugosas, así que ahora es el momento de ver qué tipos de GitHub Dorks podemos crear para sacar partido en un entorno de búsqueda de objetivos en un pentesting.
Github Dorks
Teniendo estos comandos claros, las posibilidades son infinitas. Podemos probar filtrando por la organización objetivo y campos como "password", "pwd", "token", "credential"….
Figura 4: Buscando "password" en GitHub
Con esta técnica podemos encontrarnos con auténticas bases de datos de usuarios y clientes volcadas en Github por descuido, así como credenciales de AWS (aws_secret), tokens calentitos que han sido recientemente indexados y que todavía no han expirado. Este tipo de técnicas son similares a las que se pueden ver en la charla de Chema Alonso de "Dorking & Pentesing with Tacyt", donde hacía dorks similares para buscar en el código fuente de las apps que el servicio de ElevenPaths tiene indexado, que es lo mismo que podemos hacer en GitHub.
Figura 5: Dorking & Pentesting con Tacyt por Chema Alonso
Aquí surge una segunda derivada, ya que si la organización cuenta con mecanismos de control contra leaks en Github, el riesgo no se mitiga por completo, ya que los trabajadores cuentan con su página personal en Github donde puede haber leaks fuera del radar de la organización. Veamos por ejemplo, Netflix, una compañía que si tiene un mecanismo de control de leaks en su repositorio oficial de Github:
Figura 6: Netflix Open Source Platform
Vemos que cuenta con 15 usuarios registrados en su repositorio oficial. Lo que podríamos hacer aquí es meternos en la página personal de cada uno de esos usuarios y buscar repositorios propios donde se suelen guardar notas o trozos de código que no están en el repositorio oficial y que son altamente peligrosos para la compañía.
Si nos fijamos en la dimensión de Netflix, suena raro que tan solo cuente con 15 empleados desarrollando código, y esto no es así, el problema es que muchos de los que trabajan en el repositorio no han vinculado su perfil al de Netflix, algo todavía más peligroso, ya que podríamos buscar "developer" en Linkedin y filtrando por la organización podríamos obtener usuarios de Github que sabemos que trabajan pero cuyo perfil no está vinculado al de Netflix.
Utilizar Linkedin como fuente de datos OSINT es algo habitual, y el libro que publicaban ayer sobre OSINT y la investigación en redes sociales dedica un capítulo enorme solo a este asunto, como puedes ver en el índice del libro. Estos usuarios que trabajan en una compañía y lo anuncian en Linkedin, y luego no están vinculados a los repositorios oficiales de la empresa en Github son estos los que, por norma general, guardan la mayor cantidad de Leaks. Por suerte, Netflix ("rara avis") también tiene a estos usuarios controlados, pero no es lo habitual.
Trapos sucios de las organizaciones en Github
Otra de las curiosidades que nos está dejando esta cuarentena es una gran cantidad de discusiones en repositorios, en las que parece que los usuarios implicados no recuerdan que su conversación es pública.
Figura 8: Issues & Discussions en GitHub
Para ello basta con buscar en las secciones "Issues" y "Discussions" donde los desarrolladores presentan un problema y discuten (no siempre de las mejores formas, poniendo en riesgo reputacional a la compañía) hasta conseguir solucionarlos.
Automatizando la búsqueda: TrufleHog & GitRob
Sería ideal que las organizaciones tuvieran alertas sobre posibles leaks en Github de sus empleados, para ello existen dos herramientas que permiten automatizar este proceso. La primera es TruffleHog que por supuesto está en GitHub y puedes ver en ejecución en la imagen siguiente en la que busca Keys de AWS que puedan estar fresquitas.
Figura 9: TruffleHog
Y la segunda que os dejo, que también está en GitHub, por supuesto, es Gitrob, que te animo a que pruebes un rato para ver qué es lo que eres capaz de encontrar. Recuerda que constantemente hay actualizaciones de código, así que siempre hay "trufas" frescas que localizar.
Hay que remarcar que las posibilidades son infinitas tanto para la parta atacante como para la atacada. Es especialmente importante que en entornos de teletrabajo seamos más cuidadosos que nunca y que trabajemos con la VPN de nuestra organización que nos permita tener una conexión segura. Estos escáneres también son susceptibles de ser usados por los "malignos" y no sería recomendable que ellos se enteraran antes que nosotros de que hemos tenido un "leak".
Por último, me gustaría recalcar que el equipo de seguridad de GitHub se preocupa mucho por este tipo de leaks y ayuda a la comunidad de developers constantemente con herramientas y seminarios de concienciación. Cuenta en su equipo con grandes profesionales y siempre que desde la comunidad de hackers se ha reportado algo a GitHub lo han corregido y mejorado. Son developers trabajando para developers, y eso se nota. Ha sido una alegría ver que Nico Waisman está en el equipo como Senior VP de Innovación en Seguridad de GitHub, así que os podéis hacer una idea de cómo de serio se toma la seguridad esta compañía.
This will be a Mini Course on Attacking Devices with RF from a hackers perspective
I wanted to learn about hacking devices using radio frequencies(RF) as their communication mechanism , so I looked around the Internet and only found a few scattered tutorials on random things which were either theoretical or narrowly focused. So I bought some hardware and some tools and decided to figure it out myself. The mission was to go from knowing nothing to owning whatever random devices I could find which offer up a good target with multiple avenues of attack and capability for learning. The devices and tools needed are posted below. As we attack more devices, we will post more info on those devices. You can follow us online at the following if your really bored: Twitter: @Ficti0n , GarrGhar
I brainstormed with a friend the following attack avenues for this device:
Ring the doorbell(Our Hello World)
Trigger the motion sensors
Remotely disable the motion sensors
Jam frequencies for Denial Of Service
This blog will cover all of the attacks performed, including code, data captures, so you can follow along even if you don't have all of the exact devices but want to play around with it yourself. These are the the topics covered so you can decide if you want to read further or watch the associated videos linked below.
Using HackRF for RF Replay attacks
Using Yardstick One for Replay attacks
Demodulating and decoding signals for use with RF attacks
Discovering and troubleshooting issues
Coding tools in python and RFCat
RF Jamming Attacks
Video Series PlayList Associated with this blog:
Initial Profiling of our Device:
What does our device do in normal operation?
Taking a look at all the components, there is a receiving station which sets off alarms based on opening doors, motion from a motion sensor and the pressing of a doorbell.
How do they Connect?
All of these devices are only connected to each other via wireless, they are not connected to any sort of local network or wires. So they are all communicating in an unknown frequency we need determine before we can start hacking them.
Determining the Frequency:
To profile our device for the frequency its transmitting on we can use the FCID located on the back of any of the transmitters. We can do this by going to https://fccid.io/ and typing in the FCID from the back of our device. This will provide data sheets, and test reports which contain the information needed to sniff our devices radio transmissions. This site also contains internal device pictures which are useful if you wanted to try hardware hacking. For example looking for Integrated Circuits(IC) numbers or debug interfaces. In this case we only care about the RF frequencies our device is using which happens to be the 315MHz as show below from the fccid website.
Replay attacks with HackRF To Trigger / Disable Sensors:
Armed with the frequency range only and no other information we decided to see if we can just blindly capture and replay a transmissions raw form to perform actions without the legitimate transmitters and without understanding anything.
Below is a photo of the HackRF One hardware used in the first attack and linked above.
Install HackRF Software:
Install on OS X for HackRF is as simple as using Brew install, on Linux use the package manager for your distro:
brew install hackrf
Plug in HackRF and type hackrf_info to confirm its working
Our Hello World attack is a simple replay attack of a raw capture to perform a normal operation initiated by HackRF instead of the device. We can perform this attack without understanding anything about the capture and decoding of signals.
With the HackRF device and 2 simple commands we will capture the transmission and then replay it as if it was from the initial device in its raw format.The following 2 commands are listed below.The -r is used to receive and the -t is used to transmit (RX, TX) you will also notice a -R on the transmit command which continuously repeats in TX mode denoted by "Input file end reached. Rewind to beginning" within the transmit output below. We use this in case the first transmission is not seen by the device. The other switches are for gain.
By using these commands we can capture the motion sensor transmission and replay it in raw format to create a false alarm, we can also capture the doorbell transmission and trigger an alarm.Output of the commands needed to do this are shown below. The video associated with this blog shows the audio and visual output from the alarm system as well as a video form of this blog.
While this is a good POC that we can communicate with the door alert system, this did not provide much of a learning opportunity nor did it drastically reduce the effectiveness of the security system. It only provides false alarms of standard functionality. Lets try doing this the more complicated way by profiling the device a bit more, capturing traffic, reducing the wave patterns to binary, converting to hex and then sending it over another device for a bit more precision and learning opportunity.This will also open up other attack vectors. This sounds complicated, but honestly its not complicated just a bit tedious to get right at first.
Further Profiling our Devices Functionality:
We are easily able to replay functionality when initiating actions ourselves with our HackRF, but what else is going on with the radio transmissions? In order to monitor the transmissions in a very simple way we can use tools such as GQRX with either our HackRF device or an inexpensive SDR Dongle and view the 315MHz radio frequency to see whats happening.
GQRX Install:
You can grab GQRX from the following location for OSX,on linux whatever package manager your distro uses should be sufficient for installing GQRX:
Plug in your SDR dongle of choice (HackRF or RTL-SDR, load up GQRX, and select your device, in this case a cheap 19 dollar RTL SDR:
Select OK and the interface will load up, I made the following changes.
I changed the mode under receiver options on the right hand side to AM for Amplitude modulation.
I changed the MHz at the top to 315000000 since that is what we saw on the fccid.io data sheets.
I then hit play and could view the 315 MHz frequency range.
When triggering any of the transmit devices I saw a spike in the frequency close to the 315 MHz range.I then held down the doorbell button since this transmit device would just keep replaying over and over while pressed. While this was repeating I dragged the bar to match the frequency exactly. Which was actually roughly 314.991.600 give or take.
I then triggered the motion sensor and saw a similar spike in frequency, but I also noticed the motion sensor transmitter sends a 2nd transmission after about 6 seconds to shut off the light on the receiver hub that no more motion is happening. A little testing showed thiswill disable the alarm from triggering during a limited time period.
Can we replay the Motion Sensor Turn off??
I tried to repeat the simple replay attack of turning off the motion sensor with HackRF, however unless your capture timing is perfect to reduce any extra data the sensor disable is rather spotty and still sometimes triggers an alarm. Even with a short capture the raw file was 40mb in size. If you were to try to breach a building and disable its sensors there is a 50% chance or so the motion sensor will be triggered.So this is not a sufficient method of disabling the motion sensor alarm. I only want a 100% chance of success if I was to try to bypass a security system.So we need another technique.I read online a bit and found something about decoding signal patterns into binary which sounded like a good way to reduce the extra data for a more reliable alarm bypass and decided to start with the simple doorbell as a test due to its ease of use, prior to working with less reliable transmissions based on motion and timing.
Decoding Signal Patterns for Sending With The YardStick One:
Below is a picture of the yard Stick tool used in the following attacks
Documented Process:
Based on my online research in order to capture a signal and retransmit using a yardstick we need to do the following:
Record the transmission with the SDR dongle and GQRX
Demodulate and Decode with Audacity into binary (1s & 0s)
Convert the Binary to Hex (0x)
Replay with YardStick in python and RFCat libraries
Troubleshooting Extra Steps:
However I found a few issues with this process and added a few more steps below. I am not trying to pretend everything worked perfectly. I ran into a few problems and these trouble shooting steps fixed the issues I ran into and I will list them below and explain them in this section as we walk through the process:
Record your YardStick Replay with GQRX and adjust the frequency again based on output
Compare your transmission waveform to that of the original transmitters waveform to insure your 1's & 0's were calculated properly
Add somepadding in form of \x00 to the end of your Hex to make it work.
Adjust the number of times you repeat your transmissions
Record Transmission with GQRX:
OK so first things first, load your GQRX application and this time hit the record button at the bottom right side prior to triggering the doorbell transmitter. This will save a Wav file you can open in audacity.
Install Audacity:
You can download audacity at the following link for OSX as well as other platforms. http://www.audacityteam.org/download/You should also be able to use your distro's package management to install this tool if it is not found on the site.
If you open up your wav file and zoom in a little with Command+1 or the zoom icon you should start to see a repeating pattern similar to this:
We need to decode one of these to trigger the doorbell. So we will need to zoom in a bit further to see a full representation of one of these patterns.Once we zoom in a bit more we see the following output which is wave form representation of your transmission. The high points are your 1's and the low points are your 0's:
Decode to binary:
So the main issue here is how many 1's and how many 0's are in each peak or valley?? Originally I was thinking that it was something like the following formatted in 8 bit bytes, but this left over an extra 1 which seemed odd so I added 7 0's to make it fit correctly.(Probably incorrect but hey it worked LOLs)
What the above binary means is that the first high peek was One 1 in length, the first low peek was One 0 in length and the larger low and high's were Three 111s in length. This seemed reasonable based on how it looks.
Try converting it yourself, does it look like my representation above?
Convert to Hex:
In order to send this to the receiver device we will need to convert it to hex. We can convert this to hex easily online at the following URL:
Or you can use radare2 and easily convert to hex by formatting your input into 8 bit byte segments followed by a "b" for binary as follows and it will spit out some hex values you can then use to reproduce the transmission with the yardstick:
In order to send this with the YardStick you will need to use a python library by the name of RFCat which interfaces with your Yardstick device and can send your Hex data to your receiver.We can easily do this with python. Even if you do not code it is very simple code to understand.In order to install RFCat you can do the following on OSX:(Linux procedures should be the same)
Plug in your device and run the following to verify:
rfcat -r
Setting up your python Replay Attack:
First convert our hex from 0xB8 format to \xB8 format and place it in the following code:
Hex Conversion for the python script:
\xb8\x8b\xb8\x88\x8b\xbb\x80
I provided a few notations under the code to help understanding but its mostly self explanatory:
#--------Ring the doorbell--------#:
from rflib import *
d = RfCat() #1
d.setFreq(315005000)#2
d.setMdmModulation(MOD_ASK_OOK) #3
d.setMdmDRate(4800) #4
print "Starting"
d.RFxmit("\xb8\x8b\xb8\x88\x8b\xbb\x80"*10) #5
print 'Transmission Complete'
#--------End Code --------#
#1 Creating a RfCat instance
#2 Setting your Frequency to the capture range from your GQRX output
#3 Setting the modulation type to ASK Amplitude shift keying
#4 Setting your capture rate to that of your GQRX capture settings
#5 Transmit your Hex 10 times
Ring Doorbell with Yardstick (First Attempt):
Plug your YardStick into the USB port and run the above code. This will send over your command to ring the doorbell.
Destroy:ficti0n$ python Door.py
Starting
Transmission Complete
However, this will fail and we have no indication as to why it failed. There are no program errors, or Rfcat errors. The only thing I could think is that that we sent the wrong data, meaning we incorrectly decoded the wave into binary. So I tried a bunch of different variations on the original for example the short lows having Two 1's instead of One and all of these failed when sending with the Yardstick.
Doorbell with Yardstick (TroubleShooting):
I needed a better way to figure out what was going on. One way to verify what you sent is to send it again with the Yardstick and capture it with your RTL-SDR device in GQRX. You can then compare the pattern we sent with the yardstick, to the original transmission pattern by the transmitter device.
The first thing you will notice when we capture a Yardstick transmission is the output is missing the nice spacing between each transmission as there was in the original transmission. This output is all mashed together:
If we keep zooming in we will see a repeating pattering like the following which is our 10 transmissions repeating over and over:
If we keep zooming in further we can compare the output from the original capture to the new capture and you will notice it pretty much looks the same other then its hard to get the zoom levels exactly the same in the GUI:
Hmmm ok so the pattern looks correct but the spacing between patterns is smashed together. After a bit of searching online I came across a piece of code which was unrelated to what I was trying to do but sending RF transmissions with \x00\x00\x00 padding at the end of the hex.This makes sense in the context of our visual representation above being all mashed up. So I tried this and it still failed.I then doubled it to 6 \x00's and the doorbell went off. So basically we just needed padding.
Also I should note that you can put as much padding as you want at the end.. I tried as much as 12 \x00 padding elements and the doorbell still went off. I also then tried a few variations of my binary decoding and some of those which were slightly off actually rang the doorbell. So some variance is tolerated at least with this device.Below is the working code :)
Our Hello World test is a SUCCESS. But now we need to move on to something that could bypass the security of the device and cause real world issues.
The following updated code will ring the doorbell using padding:
Ok so originally our simple HackRF replay had about a 50% success rate on turning off the motion sensor due to extraneous data in the transmission replay and timing issues. Lets see if we can get that to 100% with what we learned about decoding from the doorbell. We will instead decode the signal pattern sent from the transmitter to the receiver when shutting off the alert light, but without extra data. We will send it directly with a Yardstick over and over again and potentially use the devices own functionality to disable itself. This would allow us to walk past the motion sensors without setting off an alert.
The question is can we take the transmission from the Motion Sensor to the Receiver Hub which says motion has ended and use that to disable the Motion Sensor based on a slight delay between saying "there is no motion" and being ready to alert again and bypass the motion sensors security.Lets give it a try by capturing the "motion has ended" transmission with GQRX when the motion sensor sends its packet to the receiver 6 seconds after initial alert and decode the pattern..
Below is a screenshot of the "Motion has ended) transmission in audacity:
So this sequence was a bit different, there was an opening sequence followed by a repeating sequence.Lets decode both of these patterns and then determine what we need to send in order to affect the devices motion turnoff functionality.Below is the zoomed in version of the opening sequence and repeating sequence followed by an estimation of what I think the conversion is.
The opening sequence appears to have all the highs in single 1's format and most of the lows in 3 000's format, below is the exact conversion that I came up with adding some 0's at the end to make the correct byte length…
See what you can come up with,does it match what I have below?
Next up is our repeating pattern which has a similar but slightly different structure then the opening pattern. This one starts with a 101 instead of 1000 but still seems to have all of its 1's in single representations and most of its lows in sets of 3 000's. Below the screenshot is the the binary I came up with.. Write it out and see if you get the same thing?
Hex Conversion:(Used the online tool, R2 didn't like this binary for some reason)
\xA2\xA2\x88\xA2\x8A\x28\xA8\xA2\x8A\x28
Testing / Troubleshooting:
I first tried sending only the repeating sequence under the assumption the opening sequence was a fluke but that did not work.
I then tried sending only the opening sequence and that didn't work either.
I combined the first part with a repeating 2nd part for 10 iterations
The alert light immediately turned off on the device when testing from an alerting state, and from all states stopped alerting completely
Note(My light no longer turns off, I think I broke it or something LOL, or my setup at the time was different to current testing)
In order to send the first part and the second part we need to send it so that we have padding between each sequence and in a way that only the second part repeats, we can do that the following way:
Add the second patterns HEX values and add that with 6 \x00
Now multiply the second part by 10 since in the wave output this part was repeating
Below is the full code to do this, it is the same as the doorbell code with the new line from above and a While 1 loop that never stops so that the device is fully disabled using its own functionality against it :)
SUCCESS
As a quick test if you intentionally trip the sensor and immediately send this code the BEEP BEEP BEEP will be cut short to a single BEEP also the light may turn off depending how its configured. In all cases the motion sensor capability will be disabled. If you turn this script on at any time the sensor is completely disabled until you stop your transmission:
Bypassing the sensors worked, but then I got thinking, so what if the company puts out a new patch and I am no longer able to turn off the sensors by using the devices functionality against itself? Or what if I wanted to bypass the door alert when the door is opened and it breaks the connection?The door alert does not have a disable signal sent back to the receiver, it always alerts when separated.
RF Jamming and the FCC:
One way we can do this is with RF Jamming attacks. However, it should be noted that Jamming is technically ILLEGAL in the US on all frequencies. So in order to test this in a Legal way you will need a walk in Faraday cage to place your equipment and do some testing. This way you will not interfere with the operation of other devices on the frequency that you are jamming.
"We caution consumers that it is against the law to use a cell or GPS jammer or any other type of device that blocks, jams or interferes with authorized communications, as well as to import, advertise, sell, or ship such a device. The FCC Enforcement Bureau has a zero tolerance policy in this area and will take aggressive action against violators. "
Notes On the reality of Criminals:
It should also be noted that if a criminal is trying to break into your house or a building protected by an alert system that uses wireless technologies, he is probably not following FCC guidelines. So assume if you can attack your alarm system in the safety of a Faraday cage.Your alarm system is vulnerable to attack by any criminal. A fair assumption when penetration testing an alarm system your considering for install.You may want devices which are hardwired in as a backup.
There has always been Jammers for things like Cellphones, WiFi networks. With the introduction of affordable software defined radio devices an attacker can jam the 315 frequency to disable your alert system as a viable attack.A simple python script can kill a device in the 315 range and make it in-operable.
Jamming in Python:
I found the below script to be 100% effective while testing within a Faraday enclosure. Basicallythe device pauses in its current operational state, idle state or a alert light state, the device will remain in that state indefinitely until the jamming attack is stopped and the devices are manually reset.
Use a Faraday cage for your security testing:
If you use the below code make sure you use precautions such as Faraday cages to ensure the legal guidelines are met and you are not interfering with other devices in your area. You must assume that radios used by police, fire departments and other public safety activities could be blocked if you are not enclosing your signal. This code is purely for you to test your devices before installing them for the security of your assets.
I call the below program RF_EMP,not because its sending an electronic pulse but because similar to an EMP its disabling all devices in its range.Which is why you need to use a Faraday cage so as not to interfere with devices you do not own.
Below is a simple manually configurable version of this script.
#--------RF_Emp.py Simple Version --------#:
# For use within Faraday Enclosures only
from rflib import *
print "Start RF Jamming FTW"
d = RfCat()
d.setMdmModulation(MOD_ASK_OOK)
d.setFreq(315000000)
d.setMdmSyncMode(0)
d.setMdmDRate(4800)
d.setMdmChanSpc(24000)
d.setModeIDLE()
d.setPower(100)
d.makePktFLEN(0)
print "Starting JAM Session, Make sure your in your Faraday Enclosure..."
d.setModeTX() # start transmitting
raw_input("Unplug to stop jamming")
print 'done'
d.setModeIDLE() # This puts the YardStick in idle mode to stop jamming (Not convinced this works)
#--------End Code --------#
Notes on using Virtual Machines:
You can do your RF testing on a virtual machine with pre-installed tools but its kind of sketchy and you might want to throw your Yardstick against the wall in a fury of anger when you have to unplug it after every transmission. After a few fits of blind rage I decided to install it natively so my tools work every time without removing the dongle after each transmission.
Whats next:
This is it for the first blog.. Other topics will be discussed later, such as attacking devices in a blackbox assessment and configuring your own key fobs. Rolling code devices and bypassing their protections. Monitoring and attacking car components. If you have anything to add or would like to help out.. Feel free to comment and add to the discussion.
Ayer no llegué a publicar el post de El lado del mal, pero no es porque no estuviera trabajando. Estuve trabajando y mucho desde muy temprano, que es cuando más disfruto yo de ciclos de computación de calidad en mi CPU, pero cuando pude acabar con el trabajo que me había puesto se me había hecho muy tarde, así que decidí dejar para hoy la publicación del post.
No llegué a tiempo a publicar el post, pero sí que hice el trabajo que me había propuesto, que no era otro que hacer una lista de "Las 50 mejores conferencias de Chema Alonso" en mi Canal Youtube, de esas que me gustan a mí y a mi mamá, y que dejé publicado.
Me he pasado el día seleccionando las 50 charlas que más me gustan de las que he dado... Algunas son muy viejas, pero las tengo mucho cariño. Por si queréis ver alguna, estas son para mí (y para mi mamá) las 50 mejores conferencias de Chema Alonso https://t.co/Sb4UifVGSy so far
No están todas las charlas, y alguna que he dejado fuera por ahora porque había decidido que solo fueran 40 los vídeos que tenían que estar, pero a lo mejor los cambio con el tiempo. Tampoco las he ordenado por ahora en un orden temático o especial, pero puede que lo haga en el futuro. Y también puede que luego haga una lista del Top 10, y lo mismo hago que esta lista de 50 acaba siendo de 10. Ya veremos.
Lo que sí es cierto es que ahora tienes esa lista con las 50 charlas que he elegido - y hay algunas de 3 minutos, otras de 5 minutos y otras de más de una hora -, pero si quieres verte "La Serie Completa", tienes temporada a temporada, todas las series ordenadas cronológicamente en listas. Los vídeos de charlas comienzan en el año 2007 - no he conseguido vídeos anteriores - donde está la primera charla de LDAP Injection & Blind LDAP Injectiony unWebcast de ISA Server 2006. Y así hasta2020con la charla deGremlin Botnetsy las que vaya a dar este año.
También tengo otras listas para entrevistas a cosas temáticas, y los vídeos que usamos en los artículos, y otros vídeos con explicaciones puntuales, pero subido al escenario dando charlas, tienes todo el material que he sido capaz de recuperar en esas listas, para que encuentres la charla que quieres ver.
