Porting a CHIP-8 emulator to Rust

I’ve been meaning to learn the Rust language for quite some years and found only now the time to start this endeavor. I must say it has probably been for the best, as the language has clearly matured a lot since the last time I looked into it.

As a first project to try out Rust I ported Laurence Muller’s CHIP-8 emulator to it. It’s a simple C++ project and it took me only a day to port it to Rust.

You can download my port from GitHub.

There’s not much to write about the project itself apart that the original code used GLUT and the port uses SDL2. I also implemented basic audio support, but didn’t work on providing a realistic clock speed.

I can’t yet write something exhaustive about Rust, because I’m still learning it. What I can say up until now is that, apart some minor things which I dislike (snake-case: ugh), it seems fun to program in it. The amount of rules make the programming a bit more challenging, but it pays off in satisfaction once everything builds without complaints.

The only thing I can say is that I can’t clearly see a use-case for Rust. Yes, it’s a solid and secure language which is fun to use. But will it be used in the real world? I can see many use-cases for Go, not so many for Rust. What I hope is for Rust to mature some more and then to become stable, without going down the path to insanity like modern C++.

Batch image manipulation using Python and GIMP

Not a very common topic for me, but I thought it could be neat to mention some tips & tricks. I won’t go into the details of the Python GIMP SDK, most of it can be figured out from the GIMP documentation. I spent a total of one hour researching this topic, so I’m not an expert and I could have made mistakes, but perhaps I can save some effort to others which want to achieve the same results. You can jump to the end of the tutorial to find a nice skeleton batch script if you’re not interested in reading the theory.

To those wondering why GIMP, it’s because I created a new icon for Profiler and wanted to automatize some operations on it in order to have it in all sizes and flavors I need. One of the produced images had to be semi-transparent. So I thought, why not using a GIMP batch command, since anyway GIMP is installed on most Linux systems by default?

Just to mention, GIMP supports also a Lisp syntax to write scripts, but it caused my eyes to bleed profusely, so I didn’t even take into it consideration and focused directly on Python.

Of course, I could’ve tried other solutions like PIL (Python Imaging Library) which I have used in the past. But GIMP is actually nice, you can do many complex UI operations from code and you also have an interactive Python shell to test your code live on an image.

For example, open an image in GIMP, then open the Python console from Filters -> Python-Fu -> Console and execute the following code:

And you’ll see that the image is now halfway transparent. What the code does is to take the first image from the list of open images and sets the opacity of the first layer to 50%.

This is the nice thing about GIMP scripting: it lets you manipulate layers just like in the UI. This allows for very powerful scripting capabilities.

The first small issue I’ve encountered in my attempt to write a batch script, is that GIMP only accepts Python code as command line argument, not the path to a script on disk. According to the official documentation:

GIMP Python All this means that you could easily invoke a GIMP Python plug-in such as the one above directly from your shell using the (plug-in-script- fu-eval …) evaluator:

gimp –no-interface –batch ‘(python-fu-console-echo RUN-NONINTERACTIVE “another string” 777 3.1416 (list 1 0 0))’ ‘(gimp-quit 1)’

The idea behind it is that you create a GIMP plugin script, put it in the GIMP plugin directory, register methods like in the following small example script:

And then invoke the registered method from the command line as explained above.

I noticed many threads on stackoverflow.com where people were trying to figure out how to execute a batch script from the command line. Now, the obvious solution which came to my mind is to execute Python code from the command line which prepends the current path to the sys.path and then to import the batch script. So I searched and found that solution suggested by the user xenoid in this stackoverflow thread.

So the final code for my case would be:


What took me most to understand was to call the method merge_visible_layers before saving the image. Initially, I was trying to do it without calling it and the saved image was not transparent at all. So I thought the opacity was not correctly set and tried to do it with other methods like calling gimp_layer_set_opacity, but without success.

I then tried in the console and noticed that the opacity is actually set correctly, but that that information is lost when saving the image to disk. I then found the image method flatten and noticed that the transparency was retained, but unfortunately the saved PNG background was now white and no longer transparent. So I figured that there had to be a method to obtain a similar result but without losing the transparent background. Looking a bit among the methods in the SDK I found merge_visible_layers. I think it’s important to point this out, in case you experience the same issue and can’t find a working solution just like it happened to me.

Now we have a working solution, but let’s create a more elegant one, which allows use to use GIMP from within the same script, without any external invocation.

We can now call our function simply like this:

Which looks very pretty to me.

I could go on showing other nice examples of image manipulation, but the gist of the tutorial was just this. However, GIMP has a rich SDK which allows to automatize very complex operations.

Ctor conflicts

Perhaps the content of this post is trivial and widely known(?), but I just spent some time fixing a bug related to the following C++ behavior.

Let’s take a look at this code snippet:

The output of the code above is:

Whether we compile it with VC++ or g++, the result is the same.

The problem is that although the struct or class is declared locally the name of the constructor is considered a global symbol. So while the allocation size of the struct or class is correct, the constructor being invoked is always the first one encountered by the compiler, which in this case is the one which prints ‘apple’.

The problem here is that the compiler doesn’t warn the user in any way that the wrong constructor is being called and in a large project with hundreds of files it may very well be that two constructors collide.

Since namespaces are part of the name of the symbol, the code above can be fixed by adding a namespace:

Now the correct constructor will be called.

I wrote a small (dumb) Python script to detect possible ctor conflicts. It just looks for struct or class declarations and reports duplicate symbol names. It’s far from perfect.

In my opinion this could be handled better on the compiler side, at least by giving a warning.

ADDENDUM: Myria ‏(@Myriachan) explained the compiler internals on this one on twitter:

I’m just surprised that it doesn’t cause a “duplicate symbol” linker error. Symbol flagged “weak” from being inline, maybe? […] Member functions defined inside classes like that are automatically “inline” by C++ standard. […] The “inline” keyword has two meanings: hint to compiler that inlining machine code may be wise, and making symbol weak. […] Regardless of whether the compiler chooses to inline machine code within calling functions, the weak symbol part still applies. […] It is as if all inline functions (including functions defined inside classes) have __declspec(selectany) on them, in MSVC terms. […] Without this behavior, if you ever had a class in a header with functions defined, the compiler would either have to always inline the machine code, or you’d have to use #ifdef nonsense to avoid more than one .cpp defining the function.

The explanation is the correct one. And yes, if we define the ctor outside of the class the compiler does generate an error.

The logic mismatch here is that local structures in C do exist, local ctors in C++ don’t. So, the correct struct is allocated but the wrong ctor is being called. Also, while the symbol is weak for the reasons explained by Myria, the compiler could still give an error if the ctor code doesn’t match across files.

So the rule here could be: if you have local classes, avoid defining the ctor inside the class. If you already have a conflict as I did and don’t want to change the code, you can fix it with a namespace as shown above.

Software Theft FAIL

… Or why stealing software is stupid (and wrong). A small guide to detect software theft for those who are not reverse engineers.

Under my previous post the user Xylitol reported a web-page (hxyp://martik-scorp.blogspot.com/2010/12/show-me-loaded-drivers.html) by someone called “Martik Panosian” claiming that my driver list utility was his own.

Now, the utility is very small and anybody who can write a bit of code can write a similar one in an hour. Still, stealing is not nice. 🙂

Since I can’t let this ignominious theft go unpunished :P, I’ll try at least to make this post stretch beyond the specific case and show to people who don’t know much about these sort things how they can easily recognize if a software of theirs has been stolen.

In this specific case, the stolen software has been changed in its basic appearance (title, icon, version information). It can easily be explored with a software such as the CFF Explorer. In this case the CFF Explorer also identifies the stolen software as packed with PE Compact. If the CFF Explorer fails to recognize the signature, it’s a good idea to use a more up-to-date identification program like PEiD.

However, packing an application to conceal its code is a very dumb idea. Why? Because packers are not meant to really conceal the code, but to bind themselves to the application. What is usually difficult to recover in a packed application is its entry-point, the IAT and other things. But the great majority of the code is usually recoverable through a simple memory dump.
Just select the running application with an utility such as Task Explorer, right click to display the context menu and click on “Dump PE”.

Now the code can be compared. There are many ways to compare the code of two binaries. One of the easiest is to open it with IDA Pro and to use a binary diffing utility such as PatchDiff2. If the reader is doing this for hobby and can’t afford a commercial license of IDA Pro, then the freeware version will do as well.

Just disassemble both files with IDA Pro and save one of the idbs. Then click on “Edit->Plugins->PatchDiff2” and select the saved idb.

Let’s look at a screenshot of the results:

Click to enlarge

As it is possible to see, not only were the great majority of functions matched, but they also match at the same address, which proves beyond doubt that they are, in fact, the same application.

It’s important to remember that a limited number of matches is normal, because library functions or some basic ones may match among different applications.

A comparison of two applications can even be performed manually with IDA Pro, just by looking at the code, but using a diffing utility is in most cases the easiest solution.

Qt’s GUI Thread

If you’re a Qt developer, you surely are aware of the fact that you can only display GUI elements and access them from the main thread. This limitation as far as I know is mostly bound to the limitations of X and it isn’t to exclude that multithreading support for GUIs will be added soon.

This limitation never caused me any trouble, since the signal & slots mechanism is thread-safe and communicating between threads and GUI elements can be achieved through it. However, yesterday I needed to show a messagebox in a method and, in case the code is not executing in the main thread, show a native win32 MessageBox instead of a QMessageBox (of course, only on Windows can I do that, on other platforms when I’m not in the main thread, I won’t show anything).

Anyway, here’s a simple method to establish if we’re running the GUI thread:

As you can see this is a pointer comparision, but can we rely on the value returned by currentThread? Yes, we can since the pointer is associated with the thread itself as we can see from the code of the method:

qt_create_tls just calls once for every thread TlsAlloc and if the data for the current thread hasn’t been set yet, it is set with TlsSetValue. So, we can rely on a pointer comparision.