493 lines
19 KiB
Python
493 lines
19 KiB
Python
"""Python STIX2 Environment API."""
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import copy
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import logging
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import math
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from .core import parse as _parse
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from .datastore import CompositeDataSource, DataStoreMixin
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logger = logging.getLogger(__name__)
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class ObjectFactory(object):
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"""Easily create STIX objects with default values for certain properties.
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Args:
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created_by_ref (optional): Default created_by_ref value to apply to all
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objects created by this factory.
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created (optional): Default created value to apply to all
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objects created by this factory.
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external_references (optional): Default `external_references` value to apply
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to all objects created by this factory.
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object_marking_refs (optional): Default `object_marking_refs` value to apply
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to all objects created by this factory.
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list_append (bool, optional): When a default is set for a list property like
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`external_references` or `object_marking_refs` and a value for
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that property is passed into `create()`, if this is set to True,
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that value will be added to the list alongside the default. If
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this is set to False, the passed in value will replace the
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default. Defaults to True.
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"""
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def __init__(
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self, created_by_ref=None, created=None,
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external_references=None, object_marking_refs=None,
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list_append=True,
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):
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self._defaults = {}
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if created_by_ref:
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self.set_default_creator(created_by_ref)
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if created:
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self.set_default_created(created)
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if external_references:
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self.set_default_external_refs(external_references)
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if object_marking_refs:
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self.set_default_object_marking_refs(object_marking_refs)
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self._list_append = list_append
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self._list_properties = ['external_references', 'object_marking_refs']
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def set_default_creator(self, creator=None):
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"""Set default value for the `created_by_ref` property.
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"""
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self._defaults['created_by_ref'] = creator
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def set_default_created(self, created=None):
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"""Set default value for the `created` property.
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"""
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self._defaults['created'] = created
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# If the user provides a default "created" time, we also want to use
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# that as the modified time.
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self._defaults['modified'] = created
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def set_default_external_refs(self, external_references=None):
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"""Set default external references.
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"""
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self._defaults['external_references'] = external_references
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def set_default_object_marking_refs(self, object_marking_refs=None):
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"""Set default object markings.
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"""
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self._defaults['object_marking_refs'] = object_marking_refs
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def create(self, cls, **kwargs):
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"""Create a STIX object using object factory defaults.
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Args:
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cls: the python-stix2 class of the object to be created (eg. Indicator)
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**kwargs: The property/value pairs of the STIX object to be created
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"""
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# Use self.defaults as the base, but update with any explicit args
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# provided by the user.
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properties = copy.deepcopy(self._defaults)
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if kwargs:
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if self._list_append:
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# Append provided items to list properties instead of replacing them
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for list_prop in set(self._list_properties).intersection(kwargs.keys(), properties.keys()):
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kwarg_prop = kwargs.pop(list_prop)
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if kwarg_prop is None:
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del properties[list_prop]
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continue
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if not isinstance(properties[list_prop], list):
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properties[list_prop] = [properties[list_prop]]
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if isinstance(kwarg_prop, list):
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properties[list_prop].extend(kwarg_prop)
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else:
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properties[list_prop].append(kwarg_prop)
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properties.update(**kwargs)
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return cls(**properties)
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class Environment(DataStoreMixin):
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"""Abstract away some of the nasty details of working with STIX content.
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Args:
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factory (ObjectFactory, optional): Factory for creating objects with common
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defaults for certain properties.
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store (DataStore, optional): Data store providing the source and sink for the
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environment.
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source (DataSource, optional): Source for retrieving STIX objects.
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sink (DataSink, optional): Destination for saving STIX objects.
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Invalid if `store` is also provided.
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.. automethod:: get
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.. automethod:: all_versions
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.. automethod:: query
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.. automethod:: creator_of
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.. automethod:: relationships
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.. automethod:: related_to
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.. automethod:: add
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"""
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def __init__(self, factory=ObjectFactory(), store=None, source=None, sink=None):
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self.factory = factory
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self.source = CompositeDataSource()
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if store:
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self.source.add_data_source(store.source)
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self.sink = store.sink
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if source:
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self.source.add_data_source(source)
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if sink:
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if store:
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raise ValueError("Data store already provided! Environment may only have one data sink.")
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self.sink = sink
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def create(self, *args, **kwargs):
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return self.factory.create(*args, **kwargs)
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create.__doc__ = ObjectFactory.create.__doc__
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def set_default_creator(self, *args, **kwargs):
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return self.factory.set_default_creator(*args, **kwargs)
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set_default_creator.__doc__ = ObjectFactory.set_default_creator.__doc__
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def set_default_created(self, *args, **kwargs):
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return self.factory.set_default_created(*args, **kwargs)
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set_default_created.__doc__ = ObjectFactory.set_default_created.__doc__
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def set_default_external_refs(self, *args, **kwargs):
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return self.factory.set_default_external_refs(*args, **kwargs)
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set_default_external_refs.__doc__ = ObjectFactory.set_default_external_refs.__doc__
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def set_default_object_marking_refs(self, *args, **kwargs):
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return self.factory.set_default_object_marking_refs(*args, **kwargs)
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set_default_object_marking_refs.__doc__ = ObjectFactory.set_default_object_marking_refs.__doc__
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def add_filters(self, *args, **kwargs):
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return self.source.filters.add(*args, **kwargs)
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def add_filter(self, *args, **kwargs):
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return self.source.filters.add(*args, **kwargs)
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def parse(self, *args, **kwargs):
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return _parse(*args, **kwargs)
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parse.__doc__ = _parse.__doc__
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def creator_of(self, obj):
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"""Retrieve the Identity refered to by the object's `created_by_ref`.
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Args:
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obj: The STIX object whose `created_by_ref` property will be looked
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up.
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Returns:
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str: The STIX object's creator, or None, if the object contains no
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`created_by_ref` property or the object's creator cannot be
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found.
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"""
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creator_id = obj.get('created_by_ref', '')
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if creator_id:
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return self.get(creator_id)
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else:
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return None
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@staticmethod
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def semantically_equivalent(obj1, obj2, **weight_dict):
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"""This method is meant to verify if two objects of the same type are
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semantically equivalent.
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Args:
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obj1: A stix2 object instance
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obj2: A stix2 object instance
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weight_dict: A dictionary that can be used to override settings
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in the semantic equivalence process
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Returns:
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float: A number between 0.0 and 100.0 as a measurement of equivalence.
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Warnings:
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Not all objects are supported.
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Notes:
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This implementation follows the Committee Note on semantic equivalence.
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see `the Committee Note <link here>`__.
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"""
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# default weights used for the semantic equivalence process
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weigths = {
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"attack-pattern": {
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"name": 30,
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"external_references": 70,
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},
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"campaign": {
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"name": 60,
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"aliases": 40,
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},
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"identity": {
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"name": 60,
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"identity_class": 20,
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"sectors": 20,
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},
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"indicator": {
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"indicator_types": 15,
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"pattern": 80,
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"valid_from": 5,
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},
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"location": {
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"longitude_latitude": 34,
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"region": 33,
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"country": 33,
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},
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"malware": {
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"malware_types": 20,
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"name": 80,
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},
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"threat-actor": {
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"name": 60,
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"threat_actor_types": 20,
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"aliases": 20,
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},
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"tool": {
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"tool_types": 20,
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"name": 80,
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},
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"vulnerability": {
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"name": 30,
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"external_references": 70,
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},
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"_internal": {
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"tdelta": 1, # One day interval
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},
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}
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if weight_dict:
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weigths.update(weight_dict)
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matching_score = 0.0
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sum_weights = 0.0
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type1, type2 = obj1["type"], obj2["type"]
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if type1 != type2:
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raise ValueError('The objects to compare must be of the same type!')
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if obj1.get("spec_version", "2.0") != obj2.get("spec_version", "2.0"):
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raise ValueError('The objects to compare must be of the same spec version!')
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if type1 == "attack-pattern":
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if _check_property_present("name", obj1, obj2):
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w = weigths["attack-pattern"]["name"]
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sum_weights += w
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matching_score += w * _partial_string_based(obj1["name"], obj2["name"])
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if _check_property_present("external_references", obj1, obj2):
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w = weigths["attack-pattern"]["external_references"]
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sum_weights += w
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matching_score += (
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w *
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_partial_external_reference_based(obj1["external_references"], obj2["external_references"])
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)
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elif type1 == "campaign":
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if _check_property_present("name", obj1, obj2):
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w = weigths["campaign"]["name"]
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sum_weights += w
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matching_score += w * _partial_string_based(obj1["name"], obj2["name"])
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if _check_property_present("aliases", obj1, obj2):
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w = weigths["campaign"]["aliases"]
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sum_weights += w
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matching_score += w * _partial_list_based(obj1["aliases"], obj2["aliases"])
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elif type1 == "course-of-action":
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logger.warning("%s type has no semantic equivalence implementation", type1)
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return 0
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elif type1 == "identity":
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if _check_property_present("name", obj1, obj2):
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w = weigths["identity"]["name"]
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sum_weights += w
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matching_score += w * _exact_match(obj1["name"], obj2["name"])
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if _check_property_present("identity_class", obj1, obj2):
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w = weigths["identity"]["identity_class"]
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sum_weights += w
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matching_score += w * _exact_match(obj1["identity_class"], obj2["identity_class"])
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if _check_property_present("sectors", obj1, obj2):
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w = weigths["identity"]["sectors"]
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sum_weights += w
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matching_score += w * _partial_list_based(obj1["sectors"], obj2["sectors"])
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elif type1 == "indicator":
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if _check_property_present("indicator_types", obj1, obj2):
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w = weigths["indicator"]["indicator_types"]
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sum_weights += w
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matching_score += w * _partial_list_based(obj1["indicator_types"], obj2["indicator_types"])
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if _check_property_present("pattern", obj1, obj2):
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w = weigths["indicator"]["pattern"]
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sum_weights += w
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matching_score += w * _custom_pattern_based(obj1["pattern"], obj2["pattern"])
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if _check_property_present("valid_from", obj1, obj2):
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w = weigths["indicator"]["valid_from"]
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sum_weights += w
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matching_score += (
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w *
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_partial_timestamp_based(obj1["valid_from"], obj2["valid_from"], weigths["_internal"]["tdelta"])
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)
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elif type1 == "intrusion-set":
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logger.warning("%s type has no semantic equivalence implementation", type1)
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return 0
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elif type1 == "location":
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if _check_property_present("latitude", obj1, obj2) and _check_property_present("longitude", obj1, obj2):
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w = weigths["location"]["longitude_latitude"]
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sum_weights += w
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matching_score += (
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w *
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_partial_location_distance(obj1["latitude"], obj1["longitude"], obj2["latitude"], obj2["longitude"])
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)
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if _check_property_present("region", obj1, obj2):
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w = weigths["location"]["region"]
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sum_weights += w
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matching_score += w * _exact_match(obj1["region"], obj2["region"])
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if _check_property_present("country", obj1, obj2):
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w = weigths["location"]["country"]
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sum_weights += w
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matching_score += w * _exact_match(obj1["country"], obj2["country"])
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elif type1 == "malware":
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if _check_property_present("malware_types", obj1, obj2):
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w = weigths["malware"]["malware_types"]
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sum_weights += w
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matching_score += w * _partial_list_based(obj1["malware_types"], obj2["malware_types"])
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if _check_property_present("name", obj1, obj2):
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w = weigths["malware"]["name"]
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sum_weights += w
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matching_score += w * _partial_string_based(obj1["name"], obj2["name"])
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elif type1 == "observed-data":
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logger.warning("%s type has no semantic equivalence implementation", type1)
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return 0
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elif type1 == "report":
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logger.warning("%s type has no semantic equivalence implementation", type1)
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return 0
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elif type1 == "threat-actor":
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if _check_property_present("name", obj1, obj2):
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w = weigths["threat-actor"]["name"]
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sum_weights += w
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matching_score += w * _partial_string_based(obj1["name"], obj2["name"])
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if _check_property_present("threat_actor_types", obj1, obj2):
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w = weigths["threat-actor"]["threat_actor_types"]
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sum_weights += w
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matching_score += w * _partial_list_based(obj1["threat_actor_types"], obj2["threat_actor_types"])
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if _check_property_present("aliases", obj1, obj2):
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w = weigths["threat-actor"]["aliases"]
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sum_weights += w
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matching_score += w * _partial_list_based(obj1["aliases"], obj2["aliases"])
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elif type1 == "tool":
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if _check_property_present("tool_types", obj1, obj2):
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w = weigths["tool"]["tool_types"]
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sum_weights += w
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matching_score += w * _partial_list_based(obj1["tool_types"], obj2["tool_types"])
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if _check_property_present("name", obj1, obj2):
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w = weigths["tool"]["name"]
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sum_weights += w
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matching_score += w * _partial_string_based(obj1["name"], obj2["name"])
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elif type1 == "vulnerability":
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if _check_property_present("name", obj1, obj2):
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w = weigths["vulnerability"]["name"]
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sum_weights += w
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matching_score += w * _partial_string_based(obj1["name"], obj2["name"])
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if _check_property_present("external_references", obj1, obj2):
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w = weigths["vulnerability"]["external_references"]
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sum_weights += w
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matching_score += w * _partial_external_reference_based(obj1["external_references"], obj2["external_references"])
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if sum_weights <= 0:
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return 0
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equivalence_score = (matching_score / sum_weights) * 100.0
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return equivalence_score
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def _check_property_present(prop, obj1, obj2):
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if prop in obj1 and prop in obj2:
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return True
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return False
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def _partial_timestamp_based(t1, t2, tdelta):
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from .utils import parse_into_datetime
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stix_t1, stix_t2 = parse_into_datetime(t1), parse_into_datetime(t2)
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return 1 - min(abs(stix_t1.timestamp() - stix_t2.timestamp()) / (86400 * tdelta), 1)
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def _partial_list_based(l1, l2):
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l1_set, l2_set = set(l1), set(l2)
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return len(l1_set.intersection(l2_set)) / max(len(l1), len(l2))
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def _exact_match(val1, val2):
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if val1 == val2:
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return 1.0
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return 0.0
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def _partial_string_based(str1, str2):
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from pyjarowinkler import distance
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return distance.get_jaro_distance(str1, str2)
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def _custom_pattern_based(pattern1, pattern2):
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logger.warning("Checking for Indicator pattern equivalence is currently not implemented!")
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return 0 # TODO: Needs to be implemented
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def _partial_external_reference_based(refs1, refs2):
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allowed = set(("veris", "cve", "capec", "mitre-attack"))
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matches = 0
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if len(refs1) >= len(refs2):
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l1 = refs1
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l2 = refs2
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else:
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l1 = refs2
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l2 = refs1
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for ext_ref1 in l1:
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for ext_ref2 in l2:
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sn_match = False
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ei_match = False
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url_match = False
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source_name = None
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if _check_property_present("source_name", ext_ref1, ext_ref2):
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if ext_ref1["source_name"] == ext_ref2["source_name"]:
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source_name = ext_ref1["source_name"]
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sn_match = True
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if _check_property_present("external_id", ext_ref1, ext_ref2):
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if ext_ref1["external_id"] == ext_ref2["external_id"]:
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ei_match = True
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if _check_property_present("url", ext_ref1, ext_ref2):
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if ext_ref1["url"] == ext_ref2["url"]:
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url_match = True
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# Special case: if source_name is a STIX defined name and either
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# external_id or url match then its a perfect match and other entries
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# can be ignored.
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if sn_match and (ei_match or url_match) and source_name in allowed:
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return 1.0
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# Regular check. If the source_name (not STIX-defined) or external_id or
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# url matches then we consider the entry a match.
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if (sn_match or ei_match or url_match) and source_name not in allowed:
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matches += 1
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return matches / max(len(refs1), len(refs2))
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def _partial_location_distance(lat1, long1, lat2, long2):
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distance = math.sqrt(((lat2 - lat1) ** 2) + ((long2 - long1) ** 2))
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return 1 - (distance / 1000.0)
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