Title: Deadly Premonition 2: A Blessing In Disguise Developer: Toybox Publisher: Rising Star Games Genre: Adventure, Action Price: $49.99
To argue that the release of Deadly Premonition 2: A Blessing In Disguise on the Nintendo Switch comes as a surprise would be an understatement, and not just because it's a full decade since the original first hit store shelves. Deadly Premonition was an unusual survival horror title that played around with perspectives a la David Lynch, and the technical issues that plagued it on both the Sony PlayStation 3 and Xbox 360 didn't help. Evidently, it wound up gaining enough of a cult following to enable director Hidetaka Suehiro to follow through on his vision of blending humor, pop culture, and no small measure of the supernatural via a follow-up title for the current-generation hybrid console.
The result, perhaps not surprisingly, is dependent on initial expectations. Deadly Premonition 2: A Blessing In Disguise should be right up the alley of those who viewed its predecessor as transcendent. They're certainly buoyed by their experience, because it wastes no time introducing series protagonist Francis Morgan, who's now much older and battling not just an illness, but likewise a faulty memory, particularly as it relates to his investigation of a murder in rural Le Carré, Louisiana 14 years prior. Meanwhile, those without any knowledge of the source material will find themselves struggling to kee their interest in more ways than one.
Which, in a nutshell, is unfortunate, because Deadly Premonition 2: A Blessing In Disguise rewards the effort put into completing its 20-odd hours of gameplay. To be sure, not inconsiderable patience is required; even with the patches, it suffers from issues that belie its $49.99 price tag. Loading takes a while on occasion, and frame rates drop to near-insurmountable levels when the screen gets too busy for comfort. The wonder is that it shouldn't suffer from the aforesaid concerns since its video and audio presentations hardly push the envelope.
Through all these, though, Deadly Premonition 2: A Blessing In Disguise manages to earn its keep because of its refusal to be anything but true to itself. Its B-movie predilections are, if nothing else, deliberate, in a clear nod to everything that made Deadly Premonition work. Gamers out to play safe and tread the beaten path should stay away. Meanwhile, the more adventurous and willing to dab into a heady mix of noir and the surreal steeped in character development will find it worth their while.
THE GOOD
Stays true to its roots
Laced with offbeat humor and pop culture references
Heady mix of noir and the surreal
Outstanding character development
THE BAD
Still not big-free even after patches
Outdated graphics
Significant frame drops
Long load times
Calendar-based trigger events lead to occasional bouts with ennui
It's that time again, the monthly video update on the goings on at Yarkshire Gamer, still no gaming and the Govt announcements today mean it will be another 2 weeks at least.
So tune in and drop out !
5 new units this month, the 28mm Artisan WW1 Arab Revolt Cavalry in the top pic. The Kingdom of Jerusalem Knights.
Some WW1 Turkish Cavalry
Some Crusades Command Bases
And some Carthaginians
I'm losing hope of getting any gaming in for a long time so back to the paints it is.
Before they were absorbed by Sony, Psygnosis were responsible for publishing some interesting games. Attack of the Saucerman, the sole release from Fube Industries Ltd, was an attempt at morphing the sci-fi stylings of a 1950s B-movie with an action-heavy mascot platformer. With Mars Attacks and Men in Black hitting cinemas, the late 90s had something of a renaissance of flying saucer schlock, the latter of which appears to be a heavy inspiration here. With its 2000 release (a year after the PlayStation original), did it miss the B-movie boat?
Linux is a free and open-source software operating systems built around the Linux kernel. It typically packaged in a form known as a Linux distribution for both desktop and server use. It is a great development environment for programmers and developers. However, without the development tools, that would be impossible. Fortunately, plenty of Linux tools are available. Here are the top 5 most useful Linux tools for programmers. Also Read;- How To Clone One Android To Another
5 Most Useful Linux tools for Programmers
1. VIM
VIM is a free and open source software written by Bram Moolenaar in 1991. It is designed for use both from a command-line interface and as a standalone application in a graphical user interface. It comes standard with almost every Linux distribution and is also known as "the programmer's editor". VIM is great for coding and can also be used for editing things like configuration files and XML documents.
Vim has been developed to be a cross-platform that supports many other platforms. In 2006, it was voted as the most popular editor amongst Linux Journal readers. In 2015, Stack Overflow developer survey found it to be the third most popular text editor while in 2016, the Stack Overflow developer survey found it to be the fourth most popular development environment.
Zsh is written in C and initially released in 1990. It is a Unix shell that can be used as an interactive login shell and as a powerful command interpreter for shell scripting. Zsh is an extended version of Bourne shell (BASH) with a large number of improvements, including some features of Bash, ksh, and tcsh. Zsh gives a user-friendly experience on the command line. It also gives better auto-completion, Vim key bindings, and smart guesses when you write a command wrong.
Its features include (but not limited to):
Programmable command-line completion,
Sharing of command history among all running shells
Extended file globbing
Improved variable/array handling
Editing of multi-line commands in a single buffer
Spelling correction
Various compatibility modes,
Themeable prompts, and
Loadable modules.
3. Byobu
It was initially released in 2009 written in Sh and Python. Byobu can be used to provide on-screen notification or status and tabbed multi-window management. Thus, it is intended to improve terminal sessions when users connect to remote servers with an operating system Linux and Unix-like. It is is an enhancement for the GNU Screen terminal multiplexer or tmux used with the GNU/Linux computer operating system.
4. GIT
Git was initially released on April 7, 2005. It is a version control system to track changes in computer files and to coordinate work on those files among multiple people. It is primarily used for source code management in software development and can be used to keep track of changes in any set of files available in the English language. It is aimed at speed, data integrity, and support for distributed, non-linear workflows. It is free and open source software distributed under the terms of the GNU General Public License version 2.
Moreover, Linus Torvalds was the creator of GIT for the development of the Linux kernel. On the other hand, its current maintainer since then is Junio Hamano. Thus, every Git directory on every computer is a full-fledged repository with complete history and full version tracking abilities, independent of network access or a central server.
Written by Solomon Hykes in 2013, it is a computer program that performs operating-system-level virtualization, the containerization, which is developed by Docker, Inc. Primarily, Docker was developed for Linux to use as the resource isolation features of the Linux kernel. It is a tool that can package an application and its dependencies in a virtual container that can run on any Linux server. This helps enable the flexibility and portability on where the application can run, whether on premises, public cloud, private cloud, bare metal, etc. Moreover, it accesses the Linux kernel's virtualization features either directly using the libcontainer library.
YardStick One Unleashed, Automating RF Attacks In Python - An RFCat Primer
I decided to dive into our current device a bit more before moving on to a new device, and really ramp up the skillsets with RFCat and the Yardstick.So for this blog you will need our previous Target and a Yardstick One. We will be hacking everyting using only the Yardstick and Python.
So last time we scanned for signals with GQRX and a Software Defined Radio device. We took the demodulated wave forms in Audacity and discerned what the binary representation of our wave forms were by decoding them manually. We then transferred those into a hex format that our yardstick understood.However there is a way to do everything with our Yardstick. It will require a bit more understanding of the RFCat library, and a bit of python.
This blog will be your RFCAT primer and coding tutorial, but don't be scared with the word "Programming" I will be using simple code, nothing complicated.So if your a programmer, tune out any coding explanation and understand RFCat, if your not a coder, then use this as a jumping point to start making some quick python scripts for hacking.
Video Series PlayList Associated with this blog:
The first thing we did in our last blog after looking up the frequency was to open up GQRX and check if we can see our devices signals. As it turns out you can actually do this in python with RFCat. Which is really convenient if you left your Software Defined Radio dongle at home but happen to have access to a Yardstick.
RFCat as a Spectrum Analyzer:
In order to use RFCat as a spectrum analyzer we need to make sure we have RFcat installed and a few prerequisites such as python and PySide modules.I actually did this inside of an Ubuntu VMware because Pyside was giving me issues on OSX and I didn't feel like trying to fix it. So If you spin up an ubuntu vm you can do the following to get things up and running..
Install Spectrum Analyzer PreReqs:
sudo pip install PySide
sudo apt-get install ipython
Plug in your adapter and type in the following:
rfcat -r
d.specan(315000000)
You will then see the below output of RFCat Specan running in the 315 MHz range.
Click our doorbell, or trip the motion sensor and you will see a frequency spike as shown in the second picture.
This is similar to what you saw in GQRX but all with your Yardstick and the Python RFCat library.
So everything seems to be working and we can see our devices transmitting on the 315MHz frequency.Unfortunately we have no record button on Spescan. This leaves us to dive a little deeper into RFCat. We will see what RFCat can do for us in the recording and sniffing capacity.
Sniffing RF Data With The YardStick and Python:
In RFCat there is a simple listening command in our interactive session which will give us an idea of what is being transmitted and in what type of data format we are recieving. When using GQRX we received a WAV file, but what does RFCat give us?One thing I have realized over the years is programming is all about dealing with data in various formats and figuring out how to parse and use it in various implementations. So the first thing we have to figure out is what kind of data we are dealing with.
Lets hop back into RFCat and set a few parameters so the yardstick knows to listen on 315MHz and to use ASK modulation.The settings below should all be familiar from our last blog with an exception of "lowball" which configures the radio to use the lowest level of filtering. We basically want to see everything but may experience some noise by not filtering it out.. For example before you hit your doorbell button you may see random FF FF FF FF data outputted to the screen.
Below is the cmdline input needed and some example output. After all of our settings are in place we can use RF.listen() to start listening for everything in the 315000000 frequency range and have it output to the screen.
After you set it up, you can press the button on your doorbell and you will receive the following output. We have lots of zeros and what might be some hex output.
Destroy ficti0n$rfcat -r
>>> d.setFreq(315000000)
>>> d.setMdmModulation(MOD_ASK_OOK)
>>> d.setMdmDRate(4800)
>>> d.setMaxPower()
>>> d.lowball()
>>> d.RFlisten()
Entering RFlisten mode...packets arriving will be displayed on the screen
If you hit "ENTER" in your terminal you will stop receiving packets and drop back into a python interactive terminal. If we take a look at the repeating pattern in the above output, it looks like some random patterns and then a repeating pattern of, 84e708421084e738.If we convert that to binary we can compare with what we decoded WAV from our previous blog.
Since we are already in a python terminal you can type the following to see the binary representation:
Lets break that up into 8 bit bytes and compare it to our previous blogs binary, hmm its lot different then what we originally decoded the signal to be:
If we take the above capture data and format it correctly for RFcat with the replay code from the last blog. When we send it over, it does indeed ring the doorbell, thats interesting. A completely different value in both hex and in binary and still we get a doorbell to ring. So the variance we talked about last time extends a bit more. Below is the code with the new hex from the capture data:
I will also take a minute to note something before we continue. I had a little trouble at first when using a telescopic antenna in RFcat and the YardStick.So I will list those issues below as notes for you to play with if you run into random looking captures when pressing your doorbell button.
When using a telescopic antenna closed I had almost repeating output with some random bits flipped
When extending the antenna it went crazy output with random noise
I then used a small rubber ducky antenna and got the repeating output shown above.
What we have done so far:
So above, we managed to figure out the following all in RFCat
Verify the frequency with RFCat
How can I listen for it and capture a transmission with RFCat
How can I send this transmission with RFCat
We have basically eliminated the immediate need for the graphical tools that we were using in the last blog. Not to say that they are not useful. They absolutely are, and we should use them often and know how to work with all kinds of formats and understand everything.. However, if we are living in a reality that all we have is a Yardstick and no other tools. We are not helpless and we can still kick some serious RF butt.
Now we are going to take this a bit further so we can learn some more about RFCat, Python and mistakesI made when trying to automate this stuff. I found some interesting quirks I had to work through and I would like to save others some time who are also in the learning process as I am.
Using RFrecv() for Listening:
Ok first thing I learned is that RFListen() is not all that useful when it comes to automating this stuff. I tried to set its output to a variable but that did not seem to work.. So instead we will be working with another feature that lets us listen and that is RFrecv().If we fire up our RFCat in the terminal again we can give that a try:
Destroy:~ ficti0n$ rfcat -r
>>> d.setFreq(315000000)
>>> d.setMdmModulation(MOD_ASK_OOK)
>>> d.setMdmDRate(4800)
>>> d.setMaxPower()
>>> d.lowball()
>>> d.RFrecv()
Traceback (most recent call last):
File "", line 1, in
File "/Library/Python/2.7/site-packages/rflib/chipcon_nic.py", line 1376, in RFrecv
data = self.recv(APP_NIC, NIC_RECV, timeout)
File "/Library/Python/2.7/site-packages/rflib/chipcon_usb.py", line 664, in recv
raise(ChipconUsbTimeoutException())
ChipconUsbTimeoutException: Timeout waiting for USB response.
OK thats not cool we are getting a weird error if we don't get a signal right away regarding ChipconUsbTimeoutException.
No problem since we are in a python terminal we can just capture this exception and pass it, then continue with sniffing.This is done with a Try/Except block.
try:
... d.RFrecv()
... except ChipconUsbTimeoutException:
... pass
...
That looks a little better, I am no longer receiving errors, but lets put this in a loop so we are continuously listening with RFrecv() and press our doorbell so we can capture our doorbell signal.Below is the output of a random signal that came in followed by our doorbell.. but its all kinds of crazy looking and a bit hard to read:
try:
... d.RFrecv()
... except ChipconUsbTimeoutException:
... pass
...
while True:
... try:
... d.RFrecv()
... except ChipconUsbTimeoutException:
... pass
Lets try to fix the output a little and make it more readable by encoding it before we view it. Open up your text editor and use the following code.What we are doing here is simply setting up our listener as we did before and then setting it to a variable we can use.
Line 12: Setting our RFrecv() output to the variable y and z. The y variable is the output that we want
Line 13: We will wrap the y variable with an encode function to encode it with a HEX encoding.
Line 14: After that we just print it out.
When we run this script from the command line we will get a much nicer output shown below, much like we did with the RFlisten function above. The big difference being that our data is now set to the variable "capture"on line 13 and we can do what we want with that data. For example we can directly replay that data rather then manually performing the actions.
Parsing and replaying data:
This actually took me a bit of time to figure out, so we need to do a few things to get this to work:
We need to parse out the data from the surrounding 0s
We need to convert it to a format we can send (tricker then it sounds)
We need to add padding and send that data over (We know how to do this already)
Parsing Data:
So with this I first tried all kinds of regular expressions, but for some reason the inverse of more then 3 zeros in a row does not seem to work. I am no regex master but that seemed like it should be working. I then tried a few creative solutions reducing repeating zeros down to pairs that I could split on with string functions. This actually worked well but then my buddy showed me this which was more efficient:
re.split ('0000*', capture)
All this is doing is using the regex library to parse on a set of 4 or more zerosand return whats left in a list of useable hex data for sending.So lets add that into our code and give it a try to see what we get back. I made the following code changes:
Line 2: Import the Regex library
Line 11: We defined the capture variable so we can access it outside of the Try Block and the loop
Line 21: We created a payloads variable and created a list from the capture file of non 0000 blocks
Line 22: We print out our list of useable payloads which can been seen in the below output
Data Format Woes:
So we have data in a list we can pull from, thats awesome but I ran into a few issues. I first tried to parse this data into the \x format we normally used when sending our attack payloads manually, but that actually does not work. Reason being that if I use a code snippet like the following to convert this data into the right format everything looks ok and something like this \x84\xe7\x08\x42\x10\x84\xe7.But it won't actually work when I send it with RFCat. For some reason when you paste in your own hex its in a different format then if you programmatically create hex like below. You don't really need to understand the code below, just know it takes our payload and creates the hex in a visual format to what we used in the last blog:
DON'T USE THIS.. IT WONT WORK!!!
for payload in payloads:
formatted = ""
if (len(payload) > 6) and (len(payload) % 2 == 0):
print "Currently being formatted: " + payload
iterator = iter(payload)
for i in iterator:
formatted += ('\\x'+i + next(iterator))
else:
continue
Formatted Hex Vs Manually Pasted Hex
So lets compare the outputs of our manually created Hex String versus what we get when we format with the above code
Below is the output of the following:
Your encoded capture
Your parsed payloads in a nice list
Your payload being processed into hex.
But this is where things go wrong, you then have :
Your nicely formatted Hex created by your code above (Yay for us)
Then you have your manually pasted in hex from your original attack payloads as unprintable characters(What?)
You can clearly see there is a major difference between when we manually paste in our hex like we did in the last blog and when we create it from our capture file.This led to another sleepless night of researching whats going on. I did a bunch of troubleshooting until I found some code on the RFcat site and saw it using the BitString library and something called BitArray.The examples for this library were using binary data instead of hex and then converting it.
BitString BitArray Formating FTW:
If you remember above we created binary input with some python, so lets use that code in our current program template and then feed it into byteArray and see what happens. We can install bitstring with the following:
Install Bitstring:
sudo pip install bitstring
Our New code using BitString:
Line 2: I imported bitstring
Line 25: I added a for loop to go through our payload list one by one
Line 27: I convert our current payload to binary
Line 28: I take that binary and I feed it into bitstring to fix the formatting issues
Lines 29-30:Print out our binary and our new data that match our manually pasted data format, shown below
With these conversions the data above looks like its correct to attack our target devices. I know this seems like a lot of steps, but honestly this is only 50 lines of code in all to automate our replay attacks in a simple way.It is also very easy if you know what your doing and don't spend all of your time figuring it out like I did. You just need to understand how to work with the types of data each component understands.
With this latest code update we are ready to send our code with a simple modification to our RFxmit line from the last blog. We will now change RXxmit to take our formatted variable and then append our padding:
Below is our full code to automate this attack, with a few changeups, but not many.. Really all I did was add some conditional statements to limit our data to longer payloads that are divisible by 2 since our hex takes 2 string characters for example \x41 is the string character 4 and 1.I originally did this for the iterator code which required the proper amount of characters but decided to leave it since it makes sense anyway.I also set it so that if there is a capture it breaks out of the loop. This way we are not continuously attacking every transmission we see. Instead for our testing we can hit our doorbell, replay all the values before our script finishes and exits.
Note: I sent similar code to a friend and had him run it against a black box real world target. He had permission to attack this target via the owner of a facility and it worked flawlessly. So although a doorbell is a trivial target. This same research applies to garages, gates, and any other signal not using protection mechanism such as rolling code, multiple frequencies at once etc.
Also note that when you run this, almost all of the payloads in your list will ring the doorbell which is why I put a timing variable before the sending command. This way your doorbell isn't overburdened. I already broke a few of these devices during testing LOL.
I have since modified this code to be more effective, and have additional features and more niceties, I will release that code when its ready.. For now enjoy the below code and hit me up with any questions or comments.
I hope this blog is helpful in demystifying RFCat in order to successfully perform/automate attacks with only Python and your Yardstick One. This is essentially a few nights of my research posted here for everyone to learn from. Because it was a pain to find useful information, and I would like to save other people a lot of sleepless nights. I am by no means the master of RF or RFCat, there is tons more to learn. Up next I will get back on track with a real world attack against a device and creating our own keyfobs to replay our attacks in the future.
