Is there any portable way or library to check if Python script is running on a virtualized OS and also which virtualization platform it's running on.
This Detect virtualized OS from an application? questions discusses a c version.
I think you call linux command virt-what in python.
The descriptio of virt-what is here: http://people.redhat.com/~rjones/virt-what/
To my knowledge, there is no nice, portable way to figure this out from Python. Most of the time, the way people try to figure out if they're being virtualized or not is looking for clues left by the VM -- either some instruction isn't quite right, or some behavior is off.
However, all might not be lost if you're willing to go off box. When you're in a VM, you will almost never have perfect native performance. Thus, if you make enough measurements against a server you trust, then it might be possible to detect if you're in a VM. This is especially the case if you're running on a machine with multiple machines. Check your own time, how much time you're getting scheduled, and how much wall time has past (based on an external measurement because you can't trust the local machine). You'll probably have better luck if you can watch how much time has passed on the local machine rather than just inside one process.
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I have been working on some python code that does heavy calculations, and it's finally finished. I am now running the code as much as possible, but because it uses a constant +- 70% processor and 1,5Gb ram it uses a lot of power. For this reason i only run the script when i am charging my laptop, but i often forget.
What i want to do to solve this problem is making it automatic, of course. My plan is to always have the script running, but when my laptop is not charging it will be idle.
The main problem with this is that i have to detect that my laptop is being charged. I have looked around for information on this, but i can't find any that suits my problem. I have seen people use the ctypes library, but i can't seem to find a function that tells me if my laptop is being charged.
I am looking for a python function that tells me if my laptop is being charged.
edit: My operating system is windows 10.
I'm about to start working on a project where a Python script is able to remote into a Windows Server and read a bunch of text files in a certain directory. I was planning on using a module called WMI as that is the only way I have been able to successfully remotely access a windows server using Python, But upon further research I'm not sure i am going to be using this module.
The only problem is that, these text files are constantly updating about every 2 seconds and I'm afraid that the script will crash if it comes into an MutEx error where it tries to open the file while it is being rewritten. The only thing I can think of is creating a new directory, copying all the files (via script) into this directory in the state that they are in and reading them from there; and just constantly overwriting these ones with the new ones once it finishes checking all of the old ones. Unfortunately I don't know how to execute this correctly, or efficiently.
How can I go about doing this? Which python module would be best for this execution?
There is Windows support in Ansible these days. It uses winrm. There are plenty of Python libraries that utilize winrm, just google it, but Ansible is very versatile.
http://docs.ansible.com/intro_windows.html
https://msdn.microsoft.com/en-us/library/aa384426%28v=vs.85%29.aspx
I've done some work with WMI before (though not from Python) and I would not try to use it for a project like this. As you said WMI tends to be obscure and my experience says such things are hard to support long-term.
I would either work at the Windows API level, or possibly design a service that performs the desired actions access this service as needed. Of course, you will need to install this service on each machine you need to control. Both approaches have merit. The WinAPI approach pretty much guarantees you don't invent any new security holes and is simpler initially. The service approach should make the application faster and required less network traffic. I am sure you can think of others easily.
You still have to have the necessary permissions, network ports, etc. regardless of the approach. E.g., WMI is usually blocked by firewalls and you still run as some NT process.
Sorry, not really an answer as such -- meant as a long comment.
ADDED
Re: API programming, though you have no Windows API experience, I expect you find it familiar for tasks such as you describe, i.e., reading and writing files, scanning directories are nothing unique to Windows. You only need to learn about the parts of the API that interest you.
Once you create the appropriate security contexts and start your client process, there is nothing service-oriented in the, i.e., your can simply open and close files, etc., ignoring that fact that the files are remote, other than server name being included in the UNC name of the file/folder location.
I currently has an executable that when running uses all the cores on my server. I want to add another server, and have the jobs split between the two machines, but still each job using all the cores on the machine it is running. If both machines are busy I need the next job to queue until one of the two machines become free.
I thought this might be controlled by python, however I am a novice and not sure which python package would be the best for this problem.
I liked the "heapq" package for the queuing of the jobs, however it looked like it is designed for a single server use. I then looked into Ipython.parallel, but it seemed more designed for creating a separate smaller job for every core (on either one or more servers).
I saw a huge list of different options here (https://wiki.python.org/moin/ParallelProcessing) but I could do with some guidance as which way to go for a problem like this.
Can anyone suggest a package that may help with this problem, or a different way of approaching it?
Celery does exactly what you want - make it easy to distribute a task queue across multiple (many) machines.
See the Celery tutorial to get started.
Alternatively, IPython has its own multiprocessing library built in, based on ZeroMQ; see the introduction. I have not used this before, but it looks pretty straight-forward.
We all know situations when you cannot go open source and freely distribute software - and I am in one of these situations.
I have an app that consists of a number of binaries (compiled from C sources) and Python code that wraps it all into a system. This app used to work as a cloud solution so users had access to app functions via network but no chance to touch the actual server where binaries and code are stored.
Now we want to deliver the "local" version of our system. The app will be running on PCs that our users will physically own. We know that everything could be broken, but at least want to protect the app from possible copying and reverse-engineering as much as possible.
I know that Docker is a wonderful deployment tool so I wonder: is it possible to create encrypted Docker containers where no one can see any data stored in the container's filesystem? Is there a known solution to this problem?
Also, maybe there are well known solutions not based on Docker?
The root user on the host machine (where the docker daemon runs) has full access to all the processes running on the host. That means the person who controls the host machine can always get access to the RAM of the application as well as the file system. That makes it impossible to hide a key for decrypting the file system or protecting RAM from debugging.
Using obfuscation on a standard Linux box, you can make it harder to read the file system and RAM, but you can't make it impossible or the container cannot run.
If you can control the hardware running the operating system, then you might want to look at the Trusted Platform Module which starts system verification as soon as the system boots. You could then theoretically do things before the root user has access to the system to hide keys and strongly encrypt file systems. Even then, given physical access to the machine, a determined attacker can always get the decrypted data.
What you are asking about is called obfuscation. It has nothing to do with Docker and is a very language-specific problem; for data you can always do whatever mangling you want, but while you can hope to discourage the attacker it will never be secure. Even state-of-the-art encryption schemes can't help since the program (which you provide) has to contain the key.
C is usually hard enough to reverse engineer, for Python you can try pyobfuscate and similar.
For data, I found this question (keywords: encrypting files game).
If you want a completely secure solution, you're searching for the 'holy grail' of confidentiality: homomorphous encryption. In short, you want to encrypt your application and data, send them to a PC, and have this PC run them without its owner, OS, or anyone else being able to scoop at the data.
Doing so without a massive performance penalty is an active research project. There has been at least one project having managed this, but it still has limitations:
It's windows-only
The CPU has access to the key (ie, you have to trust Intel)
It's optimised for cloud scenarios. If you want to install this to multiple PCs, you need to provide the key in a secure way (ie just go there and type it yourself) to one of the PCs you're going to install your application, and this PC should be able to securely propagate the key to the other PCs.
Andy's suggestion on using the TPM has similar implications to points 2 and 3.
Sounds like Docker is not the right tool, because it was never intended to be used as a full-blown sandbox (at least based on what I've been reading). Why aren't you using a more full-blown VirtualBox approach? At least then you're able to lock up the virtual machine behind logins (as much as a physical installation on someone else's computer can be locked up) and run it isolated, encrypted filesystems and the whole nine yards.
You can either go lightweight and open, or fat and closed. I don't know that there's a "lightweight and closed" option.
I have exactly the same problem. Currently what I was able to discover is bellow.
A. Asylo(https://asylo.dev)
Asylo requires programs/algorithms to be written in C++.
Asylo library is integrated in docker and it seems to be feаsable to create custom dоcker image based on Asylo .
Asylo depends on many not so popular technologies like "proto buffers" and "bazel" etc. To me it seems that learning curve will be steep i.e. the person who is creating docker images/(programs) will need a lot of time to understand how to do it.
Asylo is free of charge
Asylo is bright new with all the advantages and disadvantages of being that.
Asylo is produced by Google but it is NOT an officially supported Google product according to the disclaimer on its page.
Asylo promises that data in trusted environment could be saved even from user with root privileges. However, there is lack of documentation and currently it is not clear how this could be implemented.
B. Scone(https://sconedocs.github.io)
It is binded to INTEL SGX technology but also there is Simulation mode(for development).
It is not free. It has just a small set of functionalities which are not paid.
Seems to support a lot of security functionalities.
Easy for use.
They seems to have more documentation and instructions how to build your own docker image with their technology.
For the Python part, you might consider using Pyinstaller, with appropriate options, it can pack your whole python app in a single executable file, which will not require python installation to be run by end users. It effectively runs a python interpreter on the packaged code, but it has a cipher option, which allows you to encrypt the bytecode.
Yes, the key will be somewhere around the executable, and a very savvy costumer might have the means to extract it, thus unraveling a not so readable code. It's up to you to know if your code contains some big secret you need to hide at all costs. I would probably not do it if I wanted to charge big money for any bug solving in the deployed product. I could use it if client has good compliance standards and is not a potential competitor, nor is expected to pay for more licenses.
While I've done this once, I honestly would avoid doing it again.
Regarding the C code, if you can compile it into executables and/or shared libraries can be included in the executable generated by Pyinstaller.
Suppose I have a script written in Python or Ruby, or a program written in C. How do I ensure that the script has no access to network capabilities?
You more or less gave a generic answer yourself by tagging it with "sandbox" because that's what you need, some kind of sandbox. Things that come to mind are: using JPython or JRuby that run on the JVM. Within the JVM you can create a sandbox using a policy file so no code in the JVM can do thing you don't allow.
For C code, it's more difficult. The brute force answer could be to run your C code in a virtual machine with no networking capabilities. I really don't have a more elegant answer right now for that one. :)
Unless you're using a sandboxed version of Python (using PyPy for example), there is no reliable way to switch-off network access from within the script itself. Of course, you could run under a VM with the network access shut off.
Firewalls can block specific applications or processes from accessing the network. ZoneAlarms is a good one that I have used to do exactly what you want in the past. So it can be done programatically, but I don't know near enough about OS programming to offer any advice on how to go about doing it.