522 lines
19 KiB
Python
522 lines
19 KiB
Python
"""Python STIX2 Environment API."""
|
|
|
|
import copy
|
|
import logging
|
|
import time
|
|
|
|
from .core import parse as _parse
|
|
from .datastore import CompositeDataSource, DataStoreMixin
|
|
from .utils import STIXdatetime, parse_into_datetime
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
class ObjectFactory(object):
|
|
"""Easily create STIX objects with default values for certain properties.
|
|
|
|
Args:
|
|
created_by_ref (optional): Default created_by_ref value to apply to all
|
|
objects created by this factory.
|
|
created (optional): Default created value to apply to all
|
|
objects created by this factory.
|
|
external_references (optional): Default `external_references` value to apply
|
|
to all objects created by this factory.
|
|
object_marking_refs (optional): Default `object_marking_refs` value to apply
|
|
to all objects created by this factory.
|
|
list_append (bool, optional): When a default is set for a list property like
|
|
`external_references` or `object_marking_refs` and a value for
|
|
that property is passed into `create()`, if this is set to True,
|
|
that value will be added to the list alongside the default. If
|
|
this is set to False, the passed in value will replace the
|
|
default. Defaults to True.
|
|
"""
|
|
|
|
def __init__(
|
|
self, created_by_ref=None, created=None,
|
|
external_references=None, object_marking_refs=None,
|
|
list_append=True,
|
|
):
|
|
|
|
self._defaults = {}
|
|
if created_by_ref:
|
|
self.set_default_creator(created_by_ref)
|
|
if created:
|
|
self.set_default_created(created)
|
|
if external_references:
|
|
self.set_default_external_refs(external_references)
|
|
if object_marking_refs:
|
|
self.set_default_object_marking_refs(object_marking_refs)
|
|
self._list_append = list_append
|
|
self._list_properties = ['external_references', 'object_marking_refs']
|
|
|
|
def set_default_creator(self, creator=None):
|
|
"""Set default value for the `created_by_ref` property.
|
|
|
|
"""
|
|
self._defaults['created_by_ref'] = creator
|
|
|
|
def set_default_created(self, created=None):
|
|
"""Set default value for the `created` property.
|
|
|
|
"""
|
|
self._defaults['created'] = created
|
|
# If the user provides a default "created" time, we also want to use
|
|
# that as the modified time.
|
|
self._defaults['modified'] = created
|
|
|
|
def set_default_external_refs(self, external_references=None):
|
|
"""Set default external references.
|
|
|
|
"""
|
|
self._defaults['external_references'] = external_references
|
|
|
|
def set_default_object_marking_refs(self, object_marking_refs=None):
|
|
"""Set default object markings.
|
|
|
|
"""
|
|
self._defaults['object_marking_refs'] = object_marking_refs
|
|
|
|
def create(self, cls, **kwargs):
|
|
"""Create a STIX object using object factory defaults.
|
|
|
|
Args:
|
|
cls: the python-stix2 class of the object to be created (eg. Indicator)
|
|
**kwargs: The property/value pairs of the STIX object to be created
|
|
"""
|
|
|
|
# Use self.defaults as the base, but update with any explicit args
|
|
# provided by the user.
|
|
properties = copy.deepcopy(self._defaults)
|
|
if kwargs:
|
|
if self._list_append:
|
|
# Append provided items to list properties instead of replacing them
|
|
for list_prop in set(self._list_properties).intersection(kwargs.keys(), properties.keys()):
|
|
kwarg_prop = kwargs.pop(list_prop)
|
|
if kwarg_prop is None:
|
|
del properties[list_prop]
|
|
continue
|
|
if not isinstance(properties[list_prop], list):
|
|
properties[list_prop] = [properties[list_prop]]
|
|
|
|
if isinstance(kwarg_prop, list):
|
|
properties[list_prop].extend(kwarg_prop)
|
|
else:
|
|
properties[list_prop].append(kwarg_prop)
|
|
|
|
properties.update(**kwargs)
|
|
|
|
return cls(**properties)
|
|
|
|
|
|
class Environment(DataStoreMixin):
|
|
"""Abstract away some of the nasty details of working with STIX content.
|
|
|
|
Args:
|
|
factory (ObjectFactory, optional): Factory for creating objects with common
|
|
defaults for certain properties.
|
|
store (DataStore, optional): Data store providing the source and sink for the
|
|
environment.
|
|
source (DataSource, optional): Source for retrieving STIX objects.
|
|
sink (DataSink, optional): Destination for saving STIX objects.
|
|
Invalid if `store` is also provided.
|
|
|
|
.. automethod:: get
|
|
.. automethod:: all_versions
|
|
.. automethod:: query
|
|
.. automethod:: creator_of
|
|
.. automethod:: relationships
|
|
.. automethod:: related_to
|
|
.. automethod:: add
|
|
|
|
"""
|
|
|
|
def __init__(self, factory=ObjectFactory(), store=None, source=None, sink=None):
|
|
self.factory = factory
|
|
self.source = CompositeDataSource()
|
|
if store:
|
|
self.source.add_data_source(store.source)
|
|
self.sink = store.sink
|
|
if source:
|
|
self.source.add_data_source(source)
|
|
if sink:
|
|
if store:
|
|
raise ValueError("Data store already provided! Environment may only have one data sink.")
|
|
self.sink = sink
|
|
|
|
def create(self, *args, **kwargs):
|
|
return self.factory.create(*args, **kwargs)
|
|
create.__doc__ = ObjectFactory.create.__doc__
|
|
|
|
def set_default_creator(self, *args, **kwargs):
|
|
return self.factory.set_default_creator(*args, **kwargs)
|
|
set_default_creator.__doc__ = ObjectFactory.set_default_creator.__doc__
|
|
|
|
def set_default_created(self, *args, **kwargs):
|
|
return self.factory.set_default_created(*args, **kwargs)
|
|
set_default_created.__doc__ = ObjectFactory.set_default_created.__doc__
|
|
|
|
def set_default_external_refs(self, *args, **kwargs):
|
|
return self.factory.set_default_external_refs(*args, **kwargs)
|
|
set_default_external_refs.__doc__ = ObjectFactory.set_default_external_refs.__doc__
|
|
|
|
def set_default_object_marking_refs(self, *args, **kwargs):
|
|
return self.factory.set_default_object_marking_refs(*args, **kwargs)
|
|
set_default_object_marking_refs.__doc__ = ObjectFactory.set_default_object_marking_refs.__doc__
|
|
|
|
def add_filters(self, *args, **kwargs):
|
|
return self.source.filters.add(*args, **kwargs)
|
|
|
|
def add_filter(self, *args, **kwargs):
|
|
return self.source.filters.add(*args, **kwargs)
|
|
|
|
def parse(self, *args, **kwargs):
|
|
return _parse(*args, **kwargs)
|
|
parse.__doc__ = _parse.__doc__
|
|
|
|
def creator_of(self, obj):
|
|
"""Retrieve the Identity refered to by the object's `created_by_ref`.
|
|
|
|
Args:
|
|
obj: The STIX object whose `created_by_ref` property will be looked
|
|
up.
|
|
|
|
Returns:
|
|
str: The STIX object's creator, or None, if the object contains no
|
|
`created_by_ref` property or the object's creator cannot be
|
|
found.
|
|
|
|
"""
|
|
creator_id = obj.get('created_by_ref', '')
|
|
if creator_id:
|
|
return self.get(creator_id)
|
|
else:
|
|
return None
|
|
|
|
@staticmethod
|
|
def semantically_equivalent(obj1, obj2, prop_scores={}, **weight_dict):
|
|
"""This method is meant to verify if two objects of the same type are
|
|
semantically equivalent.
|
|
|
|
Args:
|
|
obj1: A stix2 object instance
|
|
obj2: A stix2 object instance
|
|
weight_dict: A dictionary that can be used to override settings
|
|
in the semantic equivalence process
|
|
|
|
Returns:
|
|
float: A number between 0.0 and 100.0 as a measurement of equivalence.
|
|
|
|
Warning:
|
|
Course of Action, Intrusion-Set, Observed-Data, Report are not supported
|
|
by this implementation. Indicator pattern check is also limited.
|
|
|
|
Note:
|
|
Default weights_dict:
|
|
|
|
.. include:: ../default_sem_eq_weights.rst
|
|
|
|
Note:
|
|
This implementation follows the Committee Note on semantic equivalence.
|
|
see `the Committee Note <link here>`__.
|
|
|
|
"""
|
|
weights = WEIGHTS.copy()
|
|
|
|
if weight_dict:
|
|
weights.update(weight_dict)
|
|
|
|
type1, type2 = obj1["type"], obj2["type"]
|
|
ignore_spec_version = weights["_internal"]["ignore_spec_version"]
|
|
|
|
if type1 != type2:
|
|
raise ValueError('The objects to compare must be of the same type!')
|
|
|
|
if ignore_spec_version is False and obj1.get("spec_version", "2.0") != obj2.get("spec_version", "2.0"):
|
|
raise ValueError('The objects to compare must be of the same spec version!')
|
|
|
|
try:
|
|
weights[type1]
|
|
except KeyError:
|
|
logger.warning("'%s' type has no 'weights' dict specified & thus no semantic equivalence method to call!", type1)
|
|
sum_weights = matching_score = 0
|
|
else:
|
|
try:
|
|
method = weights[type1]["method"]
|
|
except KeyError:
|
|
logger.debug("Starting semantic equivalence process between: '%s' and '%s'", obj1["id"], obj2["id"])
|
|
matching_score = 0.0
|
|
sum_weights = 0.0
|
|
|
|
for prop in weights[type1]:
|
|
if check_property_present(prop, obj1, obj2) or prop == "longitude_latitude":
|
|
w = weights[type1][prop][0]
|
|
comp_funct = weights[type1][prop][1]
|
|
|
|
if comp_funct == partial_timestamp_based:
|
|
contributing_score = w * comp_funct(obj1[prop], obj2[prop], weights[type1]["tdelta"])
|
|
elif comp_funct == partial_location_distance:
|
|
threshold = weights[type1]["threshold"]
|
|
contributing_score = w * comp_funct(obj1["latitude"], obj1["longitude"], obj2["latitude"], obj2["longitude"], threshold)
|
|
else:
|
|
contributing_score = w * comp_funct(obj1[prop], obj2[prop])
|
|
|
|
sum_weights += w
|
|
matching_score += contributing_score
|
|
|
|
prop_scores[prop] = {
|
|
"weight": w,
|
|
"contributing_score": contributing_score,
|
|
}
|
|
logger.debug("'%s' check -- weight: %s, contributing score: %s", prop, w, contributing_score)
|
|
|
|
prop_scores["matching_score"] = matching_score
|
|
prop_scores["sum_weights"] = sum_weights
|
|
logger.debug("Matching Score: %s, Sum of Weights: %s", matching_score, sum_weights)
|
|
else:
|
|
logger.debug("Starting semantic equivalence process between: '%s' and '%s'", obj1["id"], obj2["id"])
|
|
try:
|
|
matching_score, sum_weights = method(obj1, obj2, prop_scores, **weights[type1])
|
|
except TypeError:
|
|
# method doesn't support detailed output with prop_scores
|
|
matching_score, sum_weights = method(obj1, obj2, **weights[type1])
|
|
logger.debug("Matching Score: %s, Sum of Weights: %s", matching_score, sum_weights)
|
|
|
|
if sum_weights <= 0:
|
|
return 0
|
|
equivalence_score = (matching_score / sum_weights) * 100.0
|
|
return equivalence_score
|
|
|
|
|
|
def check_property_present(prop, obj1, obj2):
|
|
"""Helper method checks if a property is present on both objects."""
|
|
if prop in obj1 and prop in obj2:
|
|
return True
|
|
return False
|
|
|
|
|
|
def partial_timestamp_based(t1, t2, tdelta):
|
|
"""Performs a timestamp-based matching via checking how close one timestamp is to another.
|
|
|
|
Args:
|
|
t1: A datetime string or STIXdatetime object.
|
|
t2: A datetime string or STIXdatetime object.
|
|
tdelta (float): A given time delta. This number is multiplied by 86400 (1 day) to
|
|
extend or shrink your time change tolerance.
|
|
|
|
Returns:
|
|
float: Number between 0.0 and 1.0 depending on match criteria.
|
|
|
|
"""
|
|
if not isinstance(t1, STIXdatetime):
|
|
t1 = parse_into_datetime(t1)
|
|
if not isinstance(t2, STIXdatetime):
|
|
t2 = parse_into_datetime(t2)
|
|
t1, t2 = time.mktime(t1.timetuple()), time.mktime(t2.timetuple())
|
|
result = 1 - min(abs(t1 - t2) / (86400 * tdelta), 1)
|
|
logger.debug("--\t\tpartial_timestamp_based '%s' '%s' tdelta: '%s'\tresult: '%s'", t1, t2, tdelta, result)
|
|
return result
|
|
|
|
|
|
def partial_list_based(l1, l2):
|
|
"""Performs a partial list matching via finding the intersection between common values.
|
|
|
|
Args:
|
|
l1: A list of values.
|
|
l2: A list of values.
|
|
|
|
Returns:
|
|
float: 1.0 if the value matches exactly, 0.0 otherwise.
|
|
|
|
"""
|
|
l1_set, l2_set = set(l1), set(l2)
|
|
result = len(l1_set.intersection(l2_set)) / max(len(l1), len(l2))
|
|
logger.debug("--\t\tpartial_list_based '%s' '%s'\tresult: '%s'", l1, l2, result)
|
|
return result
|
|
|
|
|
|
def exact_match(val1, val2):
|
|
"""Performs an exact value match based on two values
|
|
|
|
Args:
|
|
val1: A value suitable for an equality test.
|
|
val2: A value suitable for an equality test.
|
|
|
|
Returns:
|
|
float: 1.0 if the value matches exactly, 0.0 otherwise.
|
|
|
|
"""
|
|
result = 0.0
|
|
if val1 == val2:
|
|
result = 1.0
|
|
logger.debug("--\t\texact_match '%s' '%s'\tresult: '%s'", val1, val2, result)
|
|
return result
|
|
|
|
|
|
def partial_string_based(str1, str2):
|
|
"""Performs a partial string match using the Jaro-Winkler distance algorithm.
|
|
|
|
Args:
|
|
str1: A string value to check.
|
|
str2: A string value to check.
|
|
|
|
Returns:
|
|
float: Number between 0.0 and 1.0 depending on match criteria.
|
|
|
|
"""
|
|
from fuzzywuzzy import fuzz
|
|
result = fuzz.token_sort_ratio(str1, str2, force_ascii=False)
|
|
logger.debug("--\t\tpartial_string_based '%s' '%s'\tresult: '%s'", str1, str2, result)
|
|
return result / 100.0
|
|
|
|
|
|
def custom_pattern_based(pattern1, pattern2):
|
|
"""Performs a matching on Indicator Patterns.
|
|
|
|
Args:
|
|
pattern1: An Indicator pattern
|
|
pattern2: An Indicator pattern
|
|
|
|
Returns:
|
|
float: Number between 0.0 and 1.0 depending on match criteria.
|
|
|
|
"""
|
|
logger.warning("Indicator pattern equivalence is not fully defined; will default to zero if not completely identical")
|
|
return exact_match(pattern1, pattern2) # TODO: Implement pattern based equivalence
|
|
|
|
|
|
def partial_external_reference_based(refs1, refs2):
|
|
"""Performs a matching on External References.
|
|
|
|
Args:
|
|
refs1: A list of external references.
|
|
refs2: A list of external references.
|
|
|
|
Returns:
|
|
float: Number between 0.0 and 1.0 depending on matches.
|
|
|
|
"""
|
|
allowed = set(("veris", "cve", "capec", "mitre-attack"))
|
|
matches = 0
|
|
|
|
if len(refs1) >= len(refs2):
|
|
l1 = refs1
|
|
l2 = refs2
|
|
else:
|
|
l1 = refs2
|
|
l2 = refs1
|
|
|
|
for ext_ref1 in l1:
|
|
for ext_ref2 in l2:
|
|
sn_match = False
|
|
ei_match = False
|
|
url_match = False
|
|
source_name = None
|
|
|
|
if check_property_present("source_name", ext_ref1, ext_ref2):
|
|
if ext_ref1["source_name"] == ext_ref2["source_name"]:
|
|
source_name = ext_ref1["source_name"]
|
|
sn_match = True
|
|
if check_property_present("external_id", ext_ref1, ext_ref2):
|
|
if ext_ref1["external_id"] == ext_ref2["external_id"]:
|
|
ei_match = True
|
|
if check_property_present("url", ext_ref1, ext_ref2):
|
|
if ext_ref1["url"] == ext_ref2["url"]:
|
|
url_match = True
|
|
|
|
# Special case: if source_name is a STIX defined name and either
|
|
# external_id or url match then its a perfect match and other entries
|
|
# can be ignored.
|
|
if sn_match and (ei_match or url_match) and source_name in allowed:
|
|
result = 1.0
|
|
logger.debug(
|
|
"--\t\tpartial_external_reference_based '%s' '%s'\tresult: '%s'",
|
|
refs1, refs2, result,
|
|
)
|
|
return result
|
|
|
|
# Regular check. If the source_name (not STIX-defined) or external_id or
|
|
# url matches then we consider the entry a match.
|
|
if (sn_match or ei_match or url_match) and source_name not in allowed:
|
|
matches += 1
|
|
|
|
result = matches / max(len(refs1), len(refs2))
|
|
logger.debug(
|
|
"--\t\tpartial_external_reference_based '%s' '%s'\tresult: '%s'",
|
|
refs1, refs2, result,
|
|
)
|
|
return result
|
|
|
|
|
|
def partial_location_distance(lat1, long1, lat2, long2, threshold):
|
|
"""Given two coordinates perform a matching based on its distance using the Haversine Formula.
|
|
|
|
Args:
|
|
lat1: Latitude value for first coordinate point.
|
|
lat2: Latitude value for second coordinate point.
|
|
long1: Longitude value for first coordinate point.
|
|
long2: Longitude value for second coordinate point.
|
|
threshold (float): A kilometer measurement for the threshold distance between these two points.
|
|
|
|
Returns:
|
|
float: Number between 0.0 and 1.0 depending on match.
|
|
|
|
"""
|
|
from haversine import haversine, Unit
|
|
distance = haversine((lat1, long1), (lat2, long2), unit=Unit.KILOMETERS)
|
|
result = 1 - (distance / threshold)
|
|
logger.debug(
|
|
"--\t\tpartial_location_distance '%s' '%s' threshold: '%s'\tresult: '%s'",
|
|
(lat1, long1), (lat2, long2), threshold, result,
|
|
)
|
|
return result
|
|
|
|
|
|
# default weights used for the semantic equivalence process
|
|
WEIGHTS = {
|
|
"attack-pattern": {
|
|
"name": (30, partial_string_based),
|
|
"external_references": (70, partial_external_reference_based),
|
|
},
|
|
"campaign": {
|
|
"name": (60, partial_string_based),
|
|
"aliases": (40, partial_list_based),
|
|
},
|
|
"identity": {
|
|
"name": (60, partial_string_based),
|
|
"identity_class": (20, exact_match),
|
|
"sectors": (20, partial_list_based),
|
|
},
|
|
"indicator": {
|
|
"indicator_types": (15, partial_list_based),
|
|
"pattern": (80, custom_pattern_based),
|
|
"valid_from": (5, partial_timestamp_based),
|
|
"tdelta": 1, # One day interval
|
|
},
|
|
"location": {
|
|
"longitude_latitude": (34, partial_location_distance),
|
|
"region": (33, exact_match),
|
|
"country": (33, exact_match),
|
|
"threshold": 1000.0,
|
|
},
|
|
"malware": {
|
|
"malware_types": (20, partial_list_based),
|
|
"name": (80, partial_string_based),
|
|
},
|
|
"threat-actor": {
|
|
"name": (60, partial_string_based),
|
|
"threat_actor_types": (20, partial_list_based),
|
|
"aliases": (20, partial_list_based),
|
|
},
|
|
"tool": {
|
|
"tool_types": (20, partial_list_based),
|
|
"name": (80, partial_string_based),
|
|
},
|
|
"vulnerability": {
|
|
"name": (30, partial_string_based),
|
|
"external_references": (70, partial_external_reference_based),
|
|
},
|
|
"_internal": {
|
|
"ignore_spec_version": False,
|
|
},
|
|
} #: :autodoc-skip:
|