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Python Library Reference |  |
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Python Library Reference | |
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Most of the security issues surrounding the pickle and cPickle module involve unpickling. There are no known security vulnerabilities related to pickling because you (the programmer) control the objects that pickle will interact with, and all it produces is a string.
However, for unpickling, it is never a good idea to unpickle an untrusted string whose origins are dubious, for example, strings read from a socket. This is because unpickling can create unexpected objects and even potentially run methods of those objects, such as their class constructor or destructor3.11.
You can defend against this by customizing your unpickler so that you can control exactly what gets unpickled and what gets called. Unfortunately, exactly how you do this is different depending on whether you're using pickle or cPickle.
One common feature that both modules implement is the
__safe_for_unpickling__ attribute. Before calling a callable
which is not a class, the unpickler will check to make sure that the
callable has either been registered as a safe callable via the
copy_reg module, or that it has an
attribute __safe_for_unpickling__ with a true value. This
prevents the unpickling environment from being tricked into doing
evil things like call os.unlink() with an arbitrary file name.
See section 3.14.5 for more details.
For safely unpickling class instances, you need to control exactly which classes will get created. Be aware that a class's constructor could be called (if the pickler found a __getinitargs__() method) and the the class's destructor (i.e. its __del__() method) might get called when the object is garbage collected. Depending on the class, it isn't very heard to trick either method into doing bad things, such as removing a file. The way to control the classes that are safe to instantiate differs in pickle and cPickle3.12.
In the pickle module, you need to derive a subclass from Unpickler, overriding the load_global() method. load_global() should read two lines from the pickle data stream where the first line will the the name of the module containing the class and the second line will be the name of the instance's class. It then look up the class, possibly importing the module and digging out the attribute, then it appends what it finds to the unpickler's stack. Later on, this class will be assigned to the __class__ attribute of an empty class, as a way of magically creating an instance without calling its class's __init__(). You job (should you choose to accept it), would be to have load_global() push onto the unpickler's stack, a known safe version of any class you deem safe to unpickle. It is up to you to produce such a class. Or you could raise an error if you want to disallow all unpickling of instances. If this sounds like a hack, you're right. UTSL.
Things are a little cleaner with cPickle, but not by much.
To control what gets unpickled, you can set the unpickler's
find_global attribute to a function or None. If it is
None then any attempts to unpickle instances will raise an
UnpicklingError. If it is a function,
then it should accept a module name and a class name, and return the
corresponding class object. It is responsible for looking up the
class, again performing any necessary imports, and it may raise an
error to prevent instances of the class from being unpickled.
The moral of the story is that you should be really careful about the source of the strings your application unpickles.
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Python Library Reference | |
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