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dta.py
# Copyright 2014-2015, Tresys Technology, LLC # # This file is part of SETools. # # SETools is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as # published by the Free Software Foundation, either version 2.1 of # the License, or (at your option) any later version. # # SETools is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with SETools. If not, see # <http://www.gnu.org/licenses/>. # # pylint: disable=unsubscriptable-object import itertools import logging from collections import defaultdict, namedtuple from contextlib import suppress import networkx as nx from networkx.exception import NetworkXError, NetworkXNoPath from .descriptors import EdgeAttrDict, EdgeAttrList from .policyrep import TERuletype __all__ = ['DomainTransitionAnalysis'] # Return values for the analysis # are in the following tuple formats: step_output = namedtuple("step", ["source", "target", "transition", "entrypoints", "setexec", "dyntransition", "setcurrent"]) entrypoint_output = namedtuple("entrypoints", ["name", "entrypoint", "execute", "type_transition"]) class DomainTransitionAnalysis: """Domain transition analysis.""" def __init__(self, policy, reverse=False, exclude=None): """ Parameter: policy The policy to analyze. """ self.log = logging.getLogger(__name__) self.policy = policy self.exclude = exclude self.reverse = reverse self.rebuildgraph = True self.rebuildsubgraph = True self.G = nx.DiGraph() self.subG = None @property def reverse(self): return self._reverse @reverse.setter def reverse(self, direction): self._reverse = bool(direction) self.rebuildsubgraph = True @property def exclude(self): return self._exclude @exclude.setter def exclude(self, types): if types: self._exclude = [self.policy.lookup_type(t) for t in types] else: self._exclude = [] self.rebuildsubgraph = True def shortest_path(self, source, target): """ Generator which yields one shortest domain transition path between the source and target types (there may be more). Parameters: source The source type. target The target type. Yield: generator(steps) steps A generator that returns the tuple of source, target, and rules for each domain transition. """ s = self.policy.lookup_type(source) t = self.policy.lookup_type(target) if self.rebuildsubgraph: self._build_subgraph() self.log.info("Generating one domain transition path from {0} to {1}...".format(s, t)) with suppress(NetworkXNoPath): # NodeNotFound: the type is valid but not in graph, e.g. excluded # NetworkXNoPath: no paths or the target type is # not in the graph yield self.__generate_steps(nx.shortest_path(self.subG, s, t)) def all_paths(self, source, target, maxlen=2): """ Generator which yields all domain transition paths between the source and target up to the specified maximum path length. Parameters: source The source type. target The target type. maxlen Maximum length of paths. Yield: generator(steps) steps A generator that returns the tuple of source, target, and rules for each domain transition. """ if maxlen < 1: raise ValueError("Maximum path length must be positive.") s = self.policy.lookup_type(source) t = self.policy.lookup_type(target) if self.rebuildsubgraph: self._build_subgraph() self.log.info("Generating all domain transition paths from {0} to {1}, max length {2}...". format(s, t, maxlen)) with suppress(NetworkXNoPath): # NodeNotFound: the type is valid but not in graph, e.g. excluded # NetworkXNoPath: no paths or the target type is # not in the graph for path in nx.all_simple_paths(self.subG, s, t, maxlen): yield self.__generate_steps(path) def all_shortest_paths(self, source, target): """ Generator which yields all shortest domain transition paths between the source and target types. Parameters: source The source type. target The target type. Yield: generator(steps) steps A generator that returns the tuple of source, target, and rules for each domain transition. """ s = self.policy.lookup_type(source) t = self.policy.lookup_type(target) if self.rebuildsubgraph: self._build_subgraph() self.log.info("Generating all shortest domain transition paths from {0} to {1}...". format(s, t)) with suppress(NetworkXNoPath): # NodeNotFound: the type is valid but not in graph, e.g. excluded # NetworkXNoPath: no paths or the target type is # not in the graph for path in nx.all_shortest_paths(self.subG, s, t): yield self.__generate_steps(path) def transitions(self, type_): """ Generator which yields all domain transitions out of a specified source type. Parameters: type_ The starting type. Yield: generator(steps) steps A generator that returns the tuple of source, target, and rules for each domain transition. """ s = self.policy.lookup_type(type_) if self.rebuildsubgraph: self._build_subgraph() self.log.info("Generating all domain transitions {1} {0}". format(s, "in to" if self.reverse else "out from")) with suppress(NetworkXError): # NetworkXError: the type is valid but not in graph, e.g. excluded for source, target in self.subG.out_edges(s): edge = Edge(self.subG, source, target) if self.reverse: real_source, real_target = target, source else: real_source, real_target = source, target yield step_output(real_source, real_target, edge.transition, self.__generate_entrypoints(edge), edge.setexec, edge.dyntransition, edge.setcurrent) def get_stats(self): # pragma: no cover """ Get the domain transition graph statistics. Return: str """ if self.rebuildgraph: self._build_graph() return nx.info(self.G) # # Internal functions follow # @staticmethod def __generate_entrypoints(edge): """ Creates a list of entrypoint, execute, and type_transition rules for each entrypoint. Parameter: data The dictionary of entrypoints. Return: list of tuple(type, entry, exec, trans) type The entrypoint type. entry The list of entrypoint rules. exec The list of execute rules. trans The list of type_transition rules. """ return [entrypoint_output(e, edge.entrypoint[e], edge.execute[e], edge.type_transition[e]) for e in edge.entrypoint] def __generate_steps(self, path): """ Generator which yields the source, target, and associated rules for each domain transition. Parameter: path A list of graph node names representing an information flow path. Yield: tuple(source, target, transition, entrypoints, setexec, dyntransition, setcurrent) source The source type for this step of the domain transition. target The target type for this step of the domain transition. transition The list of transition rules. entrypoints Generator which yields entrypoint-related rules. setexec The list of setexec rules. dyntranstion The list of dynamic transition rules. setcurrent The list of setcurrent rules. """ for s in range(1, len(path)): source = path[s - 1] target = path[s] edge = Edge(self.subG, source, target) # Yield the actual source and target. # The above perspective is reversed # if the graph has been reversed. if self.reverse: real_source, real_target = target, source else: real_source, real_target = source, target yield step_output(real_source, real_target, edge.transition, self.__generate_entrypoints(edge), edge.setexec, edge.dyntransition, edge.setcurrent) # # Graph building functions # # Domain transition requirements: # # Standard transitions a->b: # allow a b:process transition; # allow a b_exec:file execute; # allow b b_exec:file entrypoint; # # and at least one of: # allow a self:process setexec; # type_transition a b_exec:process b; # # Dynamic transition x->y: # allow x y:process dyntransition; # allow x self:process setcurrent; # # Algorithm summary: # 1. iterate over all rules # 1. skip non allow/type_transition rules # 2. if process transition or dyntransition, create edge, # initialize rule lists, add the (dyn)transition rule # 3. if process setexec or setcurrent, add to appropriate dict # keyed on the subject # 4. if file exec, entrypoint, or type_transition:process, # add to appropriate dict keyed on subject,object. # 2. Iterate over all graph edges: # 1. if there is a transition rule (else add to invalid # transition list): # 1. use set intersection to find matching exec # and entrypoint rules. If none, add to invalid # transition list. # 2. for each valid entrypoint, add rules to the # edge's lists if there is either a # type_transition for it or the source process # has setexec permissions. # 3. If there are neither type_transitions nor # setexec permissions, add to the invalid # transition list # 2. if there is a dyntransition rule (else add to invalid # dyntrans list): # 1. If the source has a setcurrent rule, add it # to the edge's list, else add to invalid # dyntransition list. # 3. Iterate over all graph edges: # 1. if the edge has an invalid trans and dyntrans, delete # the edge. # 2. if the edge has an invalid trans, clear the related # lists on the edge. # 3. if the edge has an invalid dyntrans, clear the related # lists on the edge. # def _build_graph(self): self.G.clear() self.G.name = "Domain transition graph for {0}.".format(self.policy) self.log.info("Building domain transition graph from {0}...".format(self.policy)) # hash tables keyed on domain type setexec = defaultdict(list) setcurrent = defaultdict(list) # hash tables keyed on (domain, entrypoint file type) # the parameter for defaultdict has to be callable # hence the lambda for the nested defaultdict execute = defaultdict(lambda: defaultdict(list)) entrypoint = defaultdict(lambda: defaultdict(list)) # hash table keyed on (domain, entrypoint, target domain) type_trans = defaultdict(lambda: defaultdict(lambda: defaultdict(list))) for rule in self.policy.terules(): if rule.ruletype == TERuletype.allow: if rule.tclass not in ["process", "file"]: continue perms = rule.perms if rule.tclass == "process": if "transition" in perms: for s, t in itertools.product(rule.source.expand(), rule.target.expand()): # only add edges if they actually # transition to a new type if s != t: edge = Edge(self.G, s, t, create=True) edge.transition.append(rule) if "dyntransition" in perms: for s, t in itertools.product(rule.source.expand(), rule.target.expand()): # only add edges if they actually # transition to a new type if s != t: e = Edge(self.G, s, t, create=True) e.dyntransition.append(rule) if "setexec" in perms: for s in rule.source.expand(): setexec[s].append(rule) if "setcurrent" in perms: for s in rule.source.expand(): setcurrent[s].append(rule) else: if "execute" in perms: for s, t in itertools.product( rule.source.expand(), rule.target.expand()): execute[s][t].append(rule) if "entrypoint" in perms: for s, t in itertools.product(rule.source.expand(), rule.target.expand()): entrypoint[s][t].append(rule) elif rule.ruletype == TERuletype.type_transition: if rule.tclass != "process": continue d = rule.default for s, t in itertools.product(rule.source.expand(), rule.target.expand()): type_trans[s][t][d].append(rule) invalid_edge = [] clear_transition = [] clear_dyntransition = [] for s, t in self.G.edges(): edge = Edge(self.G, s, t) invalid_trans = False invalid_dyntrans = False if edge.transition: # get matching domain exec w/entrypoint type entry = set(entrypoint[t].keys()) exe = set(execute[s].keys()) match = entry.intersection(exe) if not match: # there are no valid entrypoints invalid_trans = True else: # TODO try to improve the # efficiency in this loop for m in match: # pylint: disable=unsupported-assignment-operation if s in setexec or type_trans[s][m]: # add key for each entrypoint edge.entrypoint[m] += entrypoint[t][m] edge.execute[m] += execute[s][m] if type_trans[s][m][t]: edge.type_transition[m] += type_trans[s][m][t] if s in setexec: edge.setexec.extend(setexec[s]) if not edge.setexec and not edge.type_transition: invalid_trans = True else: invalid_trans = True if edge.dyntransition: if s in setcurrent: edge.setcurrent.extend(setcurrent[s]) else: invalid_dyntrans = True else: invalid_dyntrans = True # cannot change the edges while iterating over them, # so keep appropriate lists if invalid_trans and invalid_dyntrans: invalid_edge.append(edge) elif invalid_trans: clear_transition.append(edge) elif invalid_dyntrans: clear_dyntransition.append(edge) # Remove invalid transitions self.G.remove_edges_from(invalid_edge) for edge in clear_transition: # if only the regular transition is invalid, # clear the relevant lists del edge.transition del edge.execute del edge.entrypoint del edge.type_transition del edge.setexec for edge in clear_dyntransition: # if only the dynamic transition is invalid, # clear the relevant lists del edge.dyntransition del edge.setcurrent self.rebuildgraph = False self.rebuildsubgraph = True self.log.info("Completed building domain transition graph.") self.log.debug("Graph stats: nodes: {0}, edges: {1}.".format( nx.number_of_nodes(self.G), nx.number_of_edges(self.G))) def __remove_excluded_entrypoints(self): invalid_edges = [] for source, target in self.subG.edges(): edge = Edge(self.subG, source, target) entrypoints = set(edge.entrypoint) entrypoints.intersection_update(self.exclude) if not entrypoints: # short circuit if there are no # excluded entrypoint types on # this edge. continue for e in entrypoints: # clear the entrypoint data # pylint: disable=unsupported-delete-operation del edge.entrypoint[e] del edge.execute[e] with suppress(KeyError): # setexec del edge.type_transition[e] # cannot delete the edges while iterating over them if not edge.entrypoint and not edge.dyntransition: invalid_edges.append(edge) self.subG.remove_edges_from(invalid_edges) def _build_subgraph(self): if self.rebuildgraph: self._build_graph() self.log.info("Building domain transition subgraph.") self.log.debug("Excluding {0}".format(self.exclude)) self.log.debug("Reverse {0}".format(self.reverse)) # reverse graph for reverse DTA if self.reverse: self.subG = self.G.reverse(copy=True) else: self.subG = self.G.copy() if self.exclude: # delete excluded domains from subgraph self.subG.remove_nodes_from(self.exclude) # delete excluded entrypoints from subgraph self.__remove_excluded_entrypoints() self.rebuildsubgraph = False self.log.info("Completed building domain transition subgraph.") self.log.debug("Subgraph stats: nodes: {0}, edges: {1}.".format( nx.number_of_nodes(self.subG), nx.number_of_edges(self.subG))) class Edge: """ A graph edge. Also used for returning domain transition steps. Parameters: graph The NetworkX graph. source The source type of the edge. target The target tyep of the edge. Keyword Parameters: create (T/F) create the edge if it does not exist. The default is False. """ transition = EdgeAttrList('transition') setexec = EdgeAttrList('setexec') dyntransition = EdgeAttrList('dyntransition') setcurrent = EdgeAttrList('setcurrent') entrypoint = EdgeAttrDict('entrypoint') execute = EdgeAttrDict('execute') type_transition = EdgeAttrDict('type_transition') def __init__(self, graph, source, target, create=False): self.G = graph self.source = source self.target = target if not self.G.has_edge(source, target): if not create: raise ValueError("Edge does not exist in graph") else: self.G.add_edge(source, target) self.transition = None self.entrypoint = None self.execute = None self.type_transition = None self.setexec = None self.dyntransition = None self.setcurrent = None def __getitem__(self, key): # This is implemented so this object can be used in NetworkX # functions that operate on (source, target) tuples if isinstance(key, slice): return [self._index_to_item(i) for i in range(* key.indices(2))] else: return self._index_to_item(key) def _index_to_item(self, index): """Return source or target based on index.""" if index == 0: return self.source elif index == 1: return self.target else: raise IndexError("Invalid index (edges only have 2 items): {0}".format(index))
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