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value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
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train | BigQueryOutputPlugin.WriteValuesToJSONFile | Write newline separated JSON dicts for each value.
We write each dict separately so we don't have to hold all of the output
streams in memory. We open and close the JSON array manually with [].
Args:
state: rdf_protodict.AttributedDict with the plugin's state.
values: RDF values to export. | grr/server/grr_response_server/output_plugins/bigquery_plugin.py | def WriteValuesToJSONFile(self, state, values):
"""Write newline separated JSON dicts for each value.
We write each dict separately so we don't have to hold all of the output
streams in memory. We open and close the JSON array manually with [].
Args:
state: rdf_protodict.AttributedDict with the ... | def WriteValuesToJSONFile(self, state, values):
"""Write newline separated JSON dicts for each value.
We write each dict separately so we don't have to hold all of the output
streams in memory. We open and close the JSON array manually with [].
Args:
state: rdf_protodict.AttributedDict with the ... | [
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train | FilterArgsFromSemanticProtobuf | Assign kwargs to the protobuf, and remove them from the kwargs dict. | grr/server/grr_response_server/flow.py | def FilterArgsFromSemanticProtobuf(protobuf, kwargs):
"""Assign kwargs to the protobuf, and remove them from the kwargs dict."""
for descriptor in protobuf.type_infos:
value = kwargs.pop(descriptor.name, None)
if value is not None:
setattr(protobuf, descriptor.name, value) | def FilterArgsFromSemanticProtobuf(protobuf, kwargs):
"""Assign kwargs to the protobuf, and remove them from the kwargs dict."""
for descriptor in protobuf.type_infos:
value = kwargs.pop(descriptor.name, None)
if value is not None:
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train | GetOutputPluginStates | Initializes state for a list of output plugins. | grr/server/grr_response_server/flow.py | def GetOutputPluginStates(output_plugins, source=None, token=None):
"""Initializes state for a list of output plugins."""
output_plugins_states = []
for plugin_descriptor in output_plugins:
plugin_class = plugin_descriptor.GetPluginClass()
try:
_, plugin_state = plugin_class.CreatePluginAndDefaultSt... | def GetOutputPluginStates(output_plugins, source=None, token=None):
"""Initializes state for a list of output plugins."""
output_plugins_states = []
for plugin_descriptor in output_plugins:
plugin_class = plugin_descriptor.GetPluginClass()
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train | StartAFF4Flow | The main factory function for creating and executing a new flow.
Args:
args: An arg protocol buffer which is an instance of the required flow's
args_type class attribute.
runner_args: an instance of FlowRunnerArgs() protocol buffer which is used
to initialize the runner for this flow.
parent_... | grr/server/grr_response_server/flow.py | def StartAFF4Flow(args=None,
runner_args=None,
parent_flow=None,
sync=True,
token=None,
**kwargs):
"""The main factory function for creating and executing a new flow.
Args:
args: An arg protocol buffer which is an instanc... | def StartAFF4Flow(args=None,
runner_args=None,
parent_flow=None,
sync=True,
token=None,
**kwargs):
"""The main factory function for creating and executing a new flow.
Args:
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train | StartFlow | The main factory function for creating and executing a new flow.
Args:
client_id: ID of the client this flow should run on.
cpu_limit: CPU limit in seconds for this flow.
creator: Username that requested this flow.
flow_args: An arg protocol buffer which is an instance of the required
flow's ar... | grr/server/grr_response_server/flow.py | def StartFlow(client_id=None,
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flow_args=None,
flow_cls=None,
network_bytes_limit=None,
original_flow=None,
output_plugins=None,
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parent_flow_obj=None,... | def StartFlow(client_id=None,
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creator=None,
flow_args=None,
flow_cls=None,
network_bytes_limit=None,
original_flow=None,
output_plugins=None,
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train | FlowBase.Flush | Flushes the flow/hunt and all its requests to the data_store. | grr/server/grr_response_server/flow.py | def Flush(self):
"""Flushes the flow/hunt and all its requests to the data_store."""
self._CheckLeaseAndFlush()
self.Load()
super(FlowBase, self).Flush()
# Writing the messages queued in the queue_manager of the runner always has
# to be the last thing that happens or we will have a race conditi... | def Flush(self):
"""Flushes the flow/hunt and all its requests to the data_store."""
self._CheckLeaseAndFlush()
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train | FlowBase.Close | Flushes the flow and all its requests to the data_store. | grr/server/grr_response_server/flow.py | def Close(self):
"""Flushes the flow and all its requests to the data_store."""
self._CheckLeaseAndFlush()
super(FlowBase, self).Close()
# Writing the messages queued in the queue_manager of the runner always has
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"""Flushes the flow and all its requests to the data_store."""
self._CheckLeaseAndFlush()
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train | GRRFlow.Initialize | The initialization method. | grr/server/grr_response_server/flow.py | def Initialize(self):
"""The initialization method."""
super(GRRFlow, self).Initialize()
self._client_version = None
self._client_os = None
self._client_knowledge_base = None
if "r" in self.mode:
state = self.Get(self.Schema.FLOW_STATE_DICT)
self.context = self.Get(self.Schema.FLOW_... | def Initialize(self):
"""The initialization method."""
super(GRRFlow, self).Initialize()
self._client_version = None
self._client_os = None
self._client_knowledge_base = None
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train | GRRFlow.CreateRunner | Make a new runner. | grr/server/grr_response_server/flow.py | def CreateRunner(self, **kw):
"""Make a new runner."""
self.runner = flow_runner.FlowRunner(self, token=self.token, **kw)
return self.runner | def CreateRunner(self, **kw):
"""Make a new runner."""
self.runner = flow_runner.FlowRunner(self, token=self.token, **kw)
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train | GRRFlow.NotifyAboutEnd | Send out a final notification about the end of this flow. | grr/server/grr_response_server/flow.py | def NotifyAboutEnd(self):
"""Send out a final notification about the end of this flow."""
flow_ref = None
if self.runner_args.client_id:
flow_ref = rdf_objects.FlowReference(
client_id=self.client_id, flow_id=self.urn.Basename())
num_results = len(self.ResultCollection())
notificati... | def NotifyAboutEnd(self):
"""Send out a final notification about the end of this flow."""
flow_ref = None
if self.runner_args.client_id:
flow_ref = rdf_objects.FlowReference(
client_id=self.client_id, flow_id=self.urn.Basename())
num_results = len(self.ResultCollection())
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train | GRRFlow.MarkForTermination | Mark the flow for termination as soon as any of its states are called. | grr/server/grr_response_server/flow.py | def MarkForTermination(cls, flow_urn, reason=None, mutation_pool=None):
"""Mark the flow for termination as soon as any of its states are called."""
# Doing a blind write here using low-level data store API. Accessing
# the flow via AFF4 is not really possible here, because it forces a state
# to be wri... | def MarkForTermination(cls, flow_urn, reason=None, mutation_pool=None):
"""Mark the flow for termination as soon as any of its states are called."""
# Doing a blind write here using low-level data store API. Accessing
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train | GRRFlow.TerminateAFF4Flow | Terminate a flow.
Args:
flow_id: The flow session_id to terminate.
reason: A reason to log.
status: Status code used in the generated status message.
token: The access token to be used for this request.
Raises:
FlowError: If the flow can not be found. | grr/server/grr_response_server/flow.py | def TerminateAFF4Flow(cls, flow_id, reason=None, status=None, token=None):
"""Terminate a flow.
Args:
flow_id: The flow session_id to terminate.
reason: A reason to log.
status: Status code used in the generated status message.
token: The access token to be used for this request.
R... | def TerminateAFF4Flow(cls, flow_id, reason=None, status=None, token=None):
"""Terminate a flow.
Args:
flow_id: The flow session_id to terminate.
reason: A reason to log.
status: Status code used in the generated status message.
token: The access token to be used for this request.
R... | [
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train | GRRFlow.ResultCollectionForFID | Returns the ResultCollection for the flow with a given flow_id.
Args:
flow_id: The id of the flow, a RDFURN of the form aff4:/flows/F:123456.
Returns:
The collection containing the results for the flow identified by the id. | grr/server/grr_response_server/flow.py | def ResultCollectionForFID(cls, flow_id):
"""Returns the ResultCollection for the flow with a given flow_id.
Args:
flow_id: The id of the flow, a RDFURN of the form aff4:/flows/F:123456.
Returns:
The collection containing the results for the flow identified by the id.
"""
# TODO: Disal... | def ResultCollectionForFID(cls, flow_id):
"""Returns the ResultCollection for the flow with a given flow_id.
Args:
flow_id: The id of the flow, a RDFURN of the form aff4:/flows/F:123456.
Returns:
The collection containing the results for the flow identified by the id.
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train | WellKnownFlow.GetAllWellKnownFlows | Get instances of all well known flows. | grr/server/grr_response_server/flow.py | def GetAllWellKnownFlows(cls, token=None):
"""Get instances of all well known flows."""
well_known_flows = {}
for cls in itervalues(registry.AFF4FlowRegistry.FLOW_REGISTRY):
if issubclass(cls, WellKnownFlow) and cls.well_known_session_id:
well_known_flow = cls(cls.well_known_session_id, mode="... | def GetAllWellKnownFlows(cls, token=None):
"""Get instances of all well known flows."""
well_known_flows = {}
for cls in itervalues(registry.AFF4FlowRegistry.FLOW_REGISTRY):
if issubclass(cls, WellKnownFlow) and cls.well_known_session_id:
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train | WellKnownFlow.FetchAndRemoveRequestsAndResponses | Removes WellKnownFlow messages from the queue and returns them. | grr/server/grr_response_server/flow.py | def FetchAndRemoveRequestsAndResponses(self, session_id):
"""Removes WellKnownFlow messages from the queue and returns them."""
messages = []
with queue_manager.WellKnownQueueManager(token=self.token) as manager:
for response in manager.FetchResponses(session_id):
messages.append(response)
... | def FetchAndRemoveRequestsAndResponses(self, session_id):
"""Removes WellKnownFlow messages from the queue and returns them."""
messages = []
with queue_manager.WellKnownQueueManager(token=self.token) as manager:
for response in manager.FetchResponses(session_id):
messages.append(response)
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train | WellKnownFlow.ProcessResponses | For WellKnownFlows we receive these messages directly. | grr/server/grr_response_server/flow.py | def ProcessResponses(self, responses, thread_pool):
"""For WellKnownFlows we receive these messages directly."""
for response in responses:
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train | NetworkAddress.AsIPAddr | Returns the IP as an `IPAddress` object (if packed bytes are defined). | grr/core/grr_response_core/lib/rdfvalues/client_network.py | def AsIPAddr(self):
"""Returns the IP as an `IPAddress` object (if packed bytes are defined)."""
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if self.address_type == NetworkAddress.Family.INET:
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train | Interface.GetIPAddresses | Return a list of IP addresses. | grr/core/grr_response_core/lib/rdfvalues/client_network.py | def GetIPAddresses(self):
"""Return a list of IP addresses."""
results = []
for address in self.addresses:
human_readable_address = address.human_readable_address
if human_readable_address is not None:
results.append(human_readable_address)
return results | def GetIPAddresses(self):
"""Return a list of IP addresses."""
results = []
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human_readable_address = address.human_readable_address
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results.append(human_readable_address)
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train | _CheckConditionsShortCircuit | Checks all `content_conditions` until one yields no matches. | grr/client/grr_response_client/client_actions/vfs_file_finder.py | def _CheckConditionsShortCircuit(content_conditions, pathspec):
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matches = []
for cond in content_conditions:
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matches.extend(cur_m... | def _CheckConditionsShortCircuit(content_conditions, pathspec):
"""Checks all `content_conditions` until one yields no matches."""
matches = []
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train | _GetExpandedPaths | Yields all possible expansions from given path patterns. | grr/client/grr_response_client/client_actions/vfs_file_finder.py | def _GetExpandedPaths(args):
"""Yields all possible expansions from given path patterns."""
opts = globbing.PathOpts(
follow_links=args.follow_links, pathtype=args.pathtype)
for path in args.paths:
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"""Yields all possible expansions from given path patterns."""
opts = globbing.PathOpts(
follow_links=args.follow_links, pathtype=args.pathtype)
for path in args.paths:
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yield expanded_path | [
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train | RegistryKeyFromClient | This function expands paths from the args and returns registry keys.
Args:
args: An `rdf_file_finder.FileFinderArgs` object.
Yields:
`rdf_client_fs.StatEntry` instances. | grr/client/grr_response_client/client_actions/vfs_file_finder.py | def RegistryKeyFromClient(args):
"""This function expands paths from the args and returns registry keys.
Args:
args: An `rdf_file_finder.FileFinderArgs` object.
Yields:
`rdf_client_fs.StatEntry` instances.
"""
for path in _GetExpandedPaths(args):
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path=path,... | def RegistryKeyFromClient(args):
"""This function expands paths from the args and returns registry keys.
Args:
args: An `rdf_file_finder.FileFinderArgs` object.
Yields:
`rdf_client_fs.StatEntry` instances.
"""
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train | GetClientVersion | Returns last known GRR version that the client used. | grr/server/grr_response_server/data_store_utils.py | def GetClientVersion(client_id, token=None):
"""Returns last known GRR version that the client used."""
if data_store.RelationalDBEnabled():
sinfo = data_store.REL_DB.ReadClientStartupInfo(client_id=client_id)
if sinfo is not None:
return sinfo.client_info.client_version
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"""Returns last known GRR version that the client used."""
if data_store.RelationalDBEnabled():
sinfo = data_store.REL_DB.ReadClientStartupInfo(client_id=client_id)
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train | GetClientOs | Returns last known operating system name that the client used. | grr/server/grr_response_server/data_store_utils.py | def GetClientOs(client_id, token=None):
"""Returns last known operating system name that the client used."""
if data_store.RelationalDBEnabled():
kb = data_store.REL_DB.ReadClientSnapshot(client_id).knowledge_base
else:
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kb = client.Get(client... | def GetClientOs(client_id, token=None):
"""Returns last known operating system name that the client used."""
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kb = data_store.REL_DB.ReadClientSnapshot(client_id).knowledge_base
else:
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train | GetFileHashEntry | Returns an `rdf_crypto.Hash` instance for given AFF4 file descriptor. | grr/server/grr_response_server/data_store_utils.py | def GetFileHashEntry(fd):
"""Returns an `rdf_crypto.Hash` instance for given AFF4 file descriptor."""
# Hash file store is not migrated to RELDB just yet, hence the first check.
if (not fd.urn.Path().startswith("/files/hash/generic") and
data_store.RelationalDBEnabled()):
return GetUrnHashEntry(fd.urn)
... | def GetFileHashEntry(fd):
"""Returns an `rdf_crypto.Hash` instance for given AFF4 file descriptor."""
# Hash file store is not migrated to RELDB just yet, hence the first check.
if (not fd.urn.Path().startswith("/files/hash/generic") and
data_store.RelationalDBEnabled()):
return GetUrnHashEntry(fd.urn)
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train | GetUrnHashEntry | Returns an `rdf_crypto.Hash` instance for given URN of an AFF4 file. | grr/server/grr_response_server/data_store_utils.py | def GetUrnHashEntry(urn, token=None):
"""Returns an `rdf_crypto.Hash` instance for given URN of an AFF4 file."""
if data_store.RelationalDBEnabled():
client_id, vfs_path = urn.Split(2)
path_type, components = rdf_objects.ParseCategorizedPath(vfs_path)
path_info = data_store.REL_DB.ReadPathInfo(client_i... | def GetUrnHashEntry(urn, token=None):
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client_id, vfs_path = urn.Split(2)
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train | EnumMissingModules | Enumerate all modules which match the patterns MODULE_PATTERNS.
PyInstaller often fails to locate all dlls which are required at
runtime. We import all the client modules here, we simply introspect
all the modules we have loaded in our current running process, and
all the ones matching the patterns are copied ... | grr/client_builder/grr_response_client_builder/builders/windows.py | def EnumMissingModules():
"""Enumerate all modules which match the patterns MODULE_PATTERNS.
PyInstaller often fails to locate all dlls which are required at
runtime. We import all the client modules here, we simply introspect
all the modules we have loaded in our current running process, and
all the ones ma... | def EnumMissingModules():
"""Enumerate all modules which match the patterns MODULE_PATTERNS.
PyInstaller often fails to locate all dlls which are required at
runtime. We import all the client modules here, we simply introspect
all the modules we have loaded in our current running process, and
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train | CopyFileInZip | Read a file from a ZipFile and write it to a new ZipFile. | grr/client_builder/grr_response_client_builder/builders/windows.py | def CopyFileInZip(from_zip, from_name, to_zip, to_name=None):
"""Read a file from a ZipFile and write it to a new ZipFile."""
data = from_zip.read(from_name)
if to_name is None:
to_name = from_name
to_zip.writestr(to_name, data) | def CopyFileInZip(from_zip, from_name, to_zip, to_name=None):
"""Read a file from a ZipFile and write it to a new ZipFile."""
data = from_zip.read(from_name)
if to_name is None:
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train | WindowsClientBuilder.BuildNanny | Use VS2010 to build the windows Nanny service. | grr/client_builder/grr_response_client_builder/builders/windows.py | def BuildNanny(self):
"""Use VS2010 to build the windows Nanny service."""
# When running under cygwin, the following environment variables are not set
# (since they contain invalid chars). Visual Studio requires these or it
# will fail.
os.environ["ProgramFiles(x86)"] = r"C:\Program Files (x86)"
... | def BuildNanny(self):
"""Use VS2010 to build the windows Nanny service."""
# When running under cygwin, the following environment variables are not set
# (since they contain invalid chars). Visual Studio requires these or it
# will fail.
os.environ["ProgramFiles(x86)"] = r"C:\Program Files (x86)"
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train | WindowsClientBuilder.MakeExecutableTemplate | Windows templates also include the nanny. | grr/client_builder/grr_response_client_builder/builders/windows.py | def MakeExecutableTemplate(self, output_file=None):
"""Windows templates also include the nanny."""
super(WindowsClientBuilder,
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self.MakeBuildDirectory()
self.BuildWithPyInstaller()
# Get any dll's that pyinstaller forgot:
for mod... | def MakeExecutableTemplate(self, output_file=None):
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train | CryptedPassword._CheckLegacyPassword | Check password with legacy crypt based method. | grr/server/grr_response_server/aff4_objects/users.py | def _CheckLegacyPassword(self, password):
"""Check password with legacy crypt based method."""
# This import will fail on Windows.
import crypt # pylint: disable=g-import-not-at-top
salt = self._value[:2]
return crypt.crypt(password, salt) == self._value | def _CheckLegacyPassword(self, password):
"""Check password with legacy crypt based method."""
# This import will fail on Windows.
import crypt # pylint: disable=g-import-not-at-top
salt = self._value[:2]
return crypt.crypt(password, salt) == self._value | [
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train | GRRUser.Notify | Send an AFF4-based notification to the user in the UI.
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message_type: One of aff4_grr.Notification.notification_types e.g.
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train | GRRUser.DeletePendingNotification | Deletes the pending notification with the given timestamp.
Args:
timestamp: The timestamp of the notification. Assumed to be unique.
Raises:
UniqueKeyError: Raised if multiple notifications have the timestamp. | grr/server/grr_response_server/aff4_objects/users.py | def DeletePendingNotification(self, timestamp):
"""Deletes the pending notification with the given timestamp.
Args:
timestamp: The timestamp of the notification. Assumed to be unique.
Raises:
UniqueKeyError: Raised if multiple notifications have the timestamp.
"""
shown_notifications =... | def DeletePendingNotification(self, timestamp):
"""Deletes the pending notification with the given timestamp.
Args:
timestamp: The timestamp of the notification. Assumed to be unique.
Raises:
UniqueKeyError: Raised if multiple notifications have the timestamp.
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train | GRRUser.ShowNotifications | A generator of current notifications. | grr/server/grr_response_server/aff4_objects/users.py | def ShowNotifications(self, reset=True):
"""A generator of current notifications."""
shown_notifications = self.Schema.SHOWN_NOTIFICATIONS()
# Pending notifications first
pending = self.Get(self.Schema.PENDING_NOTIFICATIONS, [])
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"""A generator of current notifications."""
shown_notifications = self.Schema.SHOWN_NOTIFICATIONS()
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train | GRRUser.Describe | Return a description of this user. | grr/server/grr_response_server/aff4_objects/users.py | def Describe(self):
"""Return a description of this user."""
result = ["\nUsername: %s" % self.urn.Basename()]
labels = [l.name for l in self.GetLabels()]
result.append("Labels: %s" % ",".join(labels))
if self.Get(self.Schema.PASSWORD) is None:
result.append("Password: not set")
else:
... | def Describe(self):
"""Return a description of this user."""
result = ["\nUsername: %s" % self.urn.Basename()]
labels = [l.name for l in self.GetLabels()]
result.append("Labels: %s" % ",".join(labels))
if self.Get(self.Schema.PASSWORD) is None:
result.append("Password: not set")
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train | _Metric.Get | Gets the metric value corresponding to the given field values. | grr/core/grr_response_core/stats/default_stats_collector.py | def Get(self, fields=None):
"""Gets the metric value corresponding to the given field values."""
if not self._field_defs and fields:
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train | _CounterMetric.Increment | Increments counter value by a given delta. | grr/core/grr_response_core/stats/default_stats_collector.py | def Increment(self, delta, fields=None):
"""Increments counter value by a given delta."""
if delta < 0:
raise ValueError(
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self._metric_values[_FieldsToKey(fields)] = self.Get(fields=fields) + delta | def Increment(self, delta, fields=None):
"""Increments counter value by a given delta."""
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raise ValueError(
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train | _EventMetric.Record | Records the given observation in a distribution. | grr/core/grr_response_core/stats/default_stats_collector.py | def Record(self, value, fields=None):
"""Records the given observation in a distribution."""
key = _FieldsToKey(fields)
metric_value = self._metric_values.get(key)
if metric_value is None:
metric_value = self._DefaultValue()
self._metric_values[key] = metric_value
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"""Records the given observation in a distribution."""
key = _FieldsToKey(fields)
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metric_value = self._DefaultValue()
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train | _GaugeMetric.Set | Sets the metric's current value. | grr/core/grr_response_core/stats/default_stats_collector.py | def Set(self, value, fields=None):
"""Sets the metric's current value."""
self._metric_values[_FieldsToKey(fields)] = self._value_type(value) | def Set(self, value, fields=None):
"""Sets the metric's current value."""
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train | _GaugeMetric.Get | Returns current metric's value (executing a callback if needed). | grr/core/grr_response_core/stats/default_stats_collector.py | def Get(self, fields=None):
"""Returns current metric's value (executing a callback if needed)."""
result = super(_GaugeMetric, self).Get(fields=fields)
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return result()
else:
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train | DefaultStatsCollector._InitializeMetric | See base class. | grr/core/grr_response_core/stats/default_stats_collector.py | def _InitializeMetric(self, metadata):
"""See base class."""
field_defs = stats_utils.FieldDefinitionTuplesFromProtos(
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train | DefaultStatsCollector.IncrementCounter | See base class. | grr/core/grr_response_core/stats/default_stats_collector.py | def IncrementCounter(self, metric_name, delta=1, fields=None):
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train | DefaultStatsCollector.RecordEvent | See base class. | grr/core/grr_response_core/stats/default_stats_collector.py | def RecordEvent(self, metric_name, value, fields=None):
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train | DefaultStatsCollector.SetGaugeValue | See base class. | grr/core/grr_response_core/stats/default_stats_collector.py | def SetGaugeValue(self, metric_name, value, fields=None):
"""See base class."""
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train | DefaultStatsCollector.SetGaugeCallback | See base class. | grr/core/grr_response_core/stats/default_stats_collector.py | def SetGaugeCallback(self, metric_name, callback, fields=None):
"""See base class."""
self._gauge_metrics[metric_name].SetCallback(callback, fields) | def SetGaugeCallback(self, metric_name, callback, fields=None):
"""See base class."""
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train | DefaultStatsCollector._GetMetric | Fetches the metric object corresponding to the given name. | grr/core/grr_response_core/stats/default_stats_collector.py | def _GetMetric(self, metric_name):
"""Fetches the metric object corresponding to the given name."""
if metric_name in self._counter_metrics:
return self._counter_metrics[metric_name]
elif metric_name in self._event_metrics:
return self._event_metrics[metric_name]
elif metric_name in self._ga... | def _GetMetric(self, metric_name):
"""Fetches the metric object corresponding to the given name."""
if metric_name in self._counter_metrics:
return self._counter_metrics[metric_name]
elif metric_name in self._event_metrics:
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train | YumListCmdParser.Parse | Parse the yum output. | grr/core/grr_response_core/lib/parsers/linux_cmd_parser.py | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
knowledge_base):
"""Parse the yum output."""
_ = stderr, time_taken, args, knowledge_base # Unused.
self.CheckReturn(cmd, return_val)
packages = []
for line in stdout.decode("utf-8").splitlines()[1:]: # Ignore first lin... | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
knowledge_base):
"""Parse the yum output."""
_ = stderr, time_taken, args, knowledge_base # Unused.
self.CheckReturn(cmd, return_val)
packages = []
for line in stdout.decode("utf-8").splitlines()[1:]: # Ignore first lin... | [
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train | YumRepolistCmdParser.Parse | Parse the yum repolist output. | grr/core/grr_response_core/lib/parsers/linux_cmd_parser.py | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
knowledge_base):
"""Parse the yum repolist output."""
_ = stderr, time_taken, args, knowledge_base # Unused.
self.CheckReturn(cmd, return_val)
output = iter(stdout.decode("utf-8").splitlines())
repo_regexes = {
... | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
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"""Parse the yum repolist output."""
_ = stderr, time_taken, args, knowledge_base # Unused.
self.CheckReturn(cmd, return_val)
output = iter(stdout.decode("utf-8").splitlines())
repo_regexes = {
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train | RpmCmdParser.Parse | Parse the rpm -qa output. | grr/core/grr_response_core/lib/parsers/linux_cmd_parser.py | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
knowledge_base):
"""Parse the rpm -qa output."""
_ = time_taken, args, knowledge_base # Unused.
rpm_re = re.compile(r"^(\w[-\w\+]+?)-(\d.*)$")
self.CheckReturn(cmd, return_val)
packages = []
for line in stdout.splitl... | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
knowledge_base):
"""Parse the rpm -qa output."""
_ = time_taken, args, knowledge_base # Unused.
rpm_re = re.compile(r"^(\w[-\w\+]+?)-(\d.*)$")
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packages = []
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train | DpkgCmdParser.Parse | Parse the dpkg output. | grr/core/grr_response_core/lib/parsers/linux_cmd_parser.py | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
knowledge_base):
"""Parse the dpkg output."""
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self.CheckReturn(cmd, return_val)
column_lengths = []
i = 0
for i, line in enumerate(stdout.decode("utf-8").splitli... | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
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self.CheckReturn(cmd, return_val)
column_lengths = []
i = 0
for i, line in enumerate(stdout.decode("utf-8").splitli... | [
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train | DmidecodeCmdParser.Parse | Parse the dmidecode output. All data is parsed into a dictionary. | grr/core/grr_response_core/lib/parsers/linux_cmd_parser.py | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
knowledge_base):
"""Parse the dmidecode output. All data is parsed into a dictionary."""
_ = stderr, time_taken, args, knowledge_base # Unused.
self.CheckReturn(cmd, return_val)
output = iter(stdout.decode("utf-8").splitline... | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
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"""Parse the dmidecode output. All data is parsed into a dictionary."""
_ = stderr, time_taken, args, knowledge_base # Unused.
self.CheckReturn(cmd, return_val)
output = iter(stdout.decode("utf-8").splitline... | [
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train | PsCmdParser.Parse | Parse the ps output.
Note that cmdline consumes every field up to the end of line
and as it is string, we can't perfectly see what the arguments
on the command line really were. We just assume a space is the arg
seperator. It's imperfect, but it's better than nothing.
Obviously, if cmd/cmdline is s... | grr/core/grr_response_core/lib/parsers/linux_cmd_parser.py | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
knowledge_base):
"""Parse the ps output.
Note that cmdline consumes every field up to the end of line
and as it is string, we can't perfectly see what the arguments
on the command line really were. We just assume a space is ... | def Parse(self, cmd, args, stdout, stderr, return_val, time_taken,
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"""Parse the ps output.
Note that cmdline consumes every field up to the end of line
and as it is string, we can't perfectly see what the arguments
on the command line really were. We just assume a space is ... | [
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train | ValidateIapJwtFromComputeEngine | Validates an IAP JWT for your (Compute|Container) Engine service.
Args:
iap_jwt: The contents of the X-Goog-IAP-JWT-Assertion header.
cloud_project_number: The project *number* for your Google Cloud project.
This is returned by 'gcloud projects describe $PROJECT_ID', or in the
Project Info card i... | grr/server/grr_response_server/gui/validate_iap.py | def ValidateIapJwtFromComputeEngine(iap_jwt, cloud_project_number,
backend_service_id):
"""Validates an IAP JWT for your (Compute|Container) Engine service.
Args:
iap_jwt: The contents of the X-Goog-IAP-JWT-Assertion header.
cloud_project_number: The project *number* for... | def ValidateIapJwtFromComputeEngine(iap_jwt, cloud_project_number,
backend_service_id):
"""Validates an IAP JWT for your (Compute|Container) Engine service.
Args:
iap_jwt: The contents of the X-Goog-IAP-JWT-Assertion header.
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train | ValidateIapJwt | Validates an IAP JWT. | grr/server/grr_response_server/gui/validate_iap.py | def ValidateIapJwt(iap_jwt, expected_audience):
"""Validates an IAP JWT."""
try:
key_id = jwt.get_unverified_header(iap_jwt).get("kid")
if not key_id:
raise IAPValidationFailedError("No key ID")
key = GetIapKey(key_id)
decoded_jwt = jwt.decode(
iap_jwt, key, algorithms=["ES256"], audi... | def ValidateIapJwt(iap_jwt, expected_audience):
"""Validates an IAP JWT."""
try:
key_id = jwt.get_unverified_header(iap_jwt).get("kid")
if not key_id:
raise IAPValidationFailedError("No key ID")
key = GetIapKey(key_id)
decoded_jwt = jwt.decode(
iap_jwt, key, algorithms=["ES256"], audi... | [
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train | GetIapKey | Retrieves a public key from the list published by Identity-Aware Proxy.
The key file is re-fetched if necessary.
Args:
key_id: Key id.
Returns:
String with a key.
Raises:
KeyNotFoundError: if the key is not found in the key file.
KeysCanNotBeFetchedError: if the key file can't be fetched. | grr/server/grr_response_server/gui/validate_iap.py | def GetIapKey(key_id):
"""Retrieves a public key from the list published by Identity-Aware Proxy.
The key file is re-fetched if necessary.
Args:
key_id: Key id.
Returns:
String with a key.
Raises:
KeyNotFoundError: if the key is not found in the key file.
KeysCanNotBeFetchedError: if the k... | def GetIapKey(key_id):
"""Retrieves a public key from the list published by Identity-Aware Proxy.
The key file is re-fetched if necessary.
Args:
key_id: Key id.
Returns:
String with a key.
Raises:
KeyNotFoundError: if the key is not found in the key file.
KeysCanNotBeFetchedError: if the k... | [
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train | InitHttp | Inits an GRR API object with a HTTP connector. | api_client/python/grr_api_client/api.py | def InitHttp(api_endpoint=None,
page_size=None,
auth=None,
proxies=None,
verify=None,
cert=None,
trust_env=True):
"""Inits an GRR API object with a HTTP connector."""
connector = http_connector.HttpConnector(
api_endpoint=api_endpo... | def InitHttp(api_endpoint=None,
page_size=None,
auth=None,
proxies=None,
verify=None,
cert=None,
trust_env=True):
"""Inits an GRR API object with a HTTP connector."""
connector = http_connector.HttpConnector(
api_endpoint=api_endpo... | [
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train | NetshStaticIp | Changes interface to a staticly set IP.
Sets IP configs to local if no paramaters passed.
Args:
interface: Name of the interface.
ip: IP address.
subnet: Subnet mask.
gw: IP address of the default gateway.
Returns:
A tuple of stdout, stderr, exit_status. | grr/core/executables/python_hacks/modify_network.py | def NetshStaticIp(interface,
ip=u'127.0.0.9',
subnet=u'255.255.255.255',
gw=u'127.0.0.1'):
"""Changes interface to a staticly set IP.
Sets IP configs to local if no paramaters passed.
Args:
interface: Name of the interface.
ip: IP address.
subnet... | def NetshStaticIp(interface,
ip=u'127.0.0.9',
subnet=u'255.255.255.255',
gw=u'127.0.0.1'):
"""Changes interface to a staticly set IP.
Sets IP configs to local if no paramaters passed.
Args:
interface: Name of the interface.
ip: IP address.
subnet... | [
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train | DisableInterfaces | Tries to disable an interface. Only works on Vista and 7.
Args:
interface: Name of the interface to disable.
Returns:
res which is a tuple of (stdout, stderr, exit_status, time_taken). | grr/core/executables/python_hacks/modify_network.py | def DisableInterfaces(interface):
"""Tries to disable an interface. Only works on Vista and 7.
Args:
interface: Name of the interface to disable.
Returns:
res which is a tuple of (stdout, stderr, exit_status, time_taken).
"""
set_tested_versions = ['vista', '2008']
set_args = ['/c', 'netsh', 'set... | def DisableInterfaces(interface):
"""Tries to disable an interface. Only works on Vista and 7.
Args:
interface: Name of the interface to disable.
Returns:
res which is a tuple of (stdout, stderr, exit_status, time_taken).
"""
set_tested_versions = ['vista', '2008']
set_args = ['/c', 'netsh', 'set... | [
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train | GetEnabledInterfaces | Gives a list of enabled interfaces. Should work on all windows versions.
Returns:
interfaces: Names of interfaces found enabled. | grr/core/executables/python_hacks/modify_network.py | def GetEnabledInterfaces():
"""Gives a list of enabled interfaces. Should work on all windows versions.
Returns:
interfaces: Names of interfaces found enabled.
"""
interfaces = []
show_args = ['/c', 'netsh', 'show', 'interface']
# pylint: disable=undefined-variable
res = client_utils_common.Execute(
... | def GetEnabledInterfaces():
"""Gives a list of enabled interfaces. Should work on all windows versions.
Returns:
interfaces: Names of interfaces found enabled.
"""
interfaces = []
show_args = ['/c', 'netsh', 'show', 'interface']
# pylint: disable=undefined-variable
res = client_utils_common.Execute(
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train | MsgUser | Sends a message to a user.
Args:
msg: Message to be displaied to user.
Returns:
res which is a tuple of (stdout, stderr, exit_status, time_taken). | grr/core/executables/python_hacks/modify_network.py | def MsgUser(msg):
"""Sends a message to a user.
Args:
msg: Message to be displaied to user.
Returns:
res which is a tuple of (stdout, stderr, exit_status, time_taken).
"""
msg_tested_versions = ['xp', 'vista', '2008', '2003']
msg_args = ['/c', '%SystemRoot%\\System32\\msg.exe', '*', '/TIME:0']
h... | def MsgUser(msg):
"""Sends a message to a user.
Args:
msg: Message to be displaied to user.
Returns:
res which is a tuple of (stdout, stderr, exit_status, time_taken).
"""
msg_tested_versions = ['xp', 'vista', '2008', '2003']
msg_args = ['/c', '%SystemRoot%\\System32\\msg.exe', '*', '/TIME:0']
h... | [
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] | google/grr | python | https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/core/executables/python_hacks/modify_network.py#L79-L101 | [
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train | RepackConfig.GetConfigFromTemplate | Apply build.yaml settings from the template. | grr/client_builder/grr_response_client_builder/repacking.py | def GetConfigFromTemplate(self, template_path):
"""Apply build.yaml settings from the template."""
with zipfile.ZipFile(template_path) as template_zip:
build_yaml = None
for name in template_zip.namelist():
if name.endswith("build.yaml"):
build_yaml = name
break
if ... | def GetConfigFromTemplate(self, template_path):
"""Apply build.yaml settings from the template."""
with zipfile.ZipFile(template_path) as template_zip:
build_yaml = None
for name in template_zip.namelist():
if name.endswith("build.yaml"):
build_yaml = name
break
if ... | [
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train | TemplateRepacker.GetRepacker | Get the appropriate client deployer based on the selected flags. | grr/client_builder/grr_response_client_builder/repacking.py | def GetRepacker(self, context, signer=None):
"""Get the appropriate client deployer based on the selected flags."""
if "Target:Darwin" in context:
deployer_class = build.DarwinClientRepacker
elif "Target:Windows" in context:
deployer_class = build.WindowsClientRepacker
elif "Target:LinuxDeb"... | def GetRepacker(self, context, signer=None):
"""Get the appropriate client deployer based on the selected flags."""
if "Target:Darwin" in context:
deployer_class = build.DarwinClientRepacker
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train | TemplateRepacker.RepackTemplate | Repack binaries based on the configuration.
We repack all templates in the templates directory. We expect to find only
functioning templates, all other files should be removed. Each template
contains a build.yaml that specifies how it was built and how it should be
repacked.
Args:
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token=None,
sign=False,
context=None,
signed_template=False):
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train | TemplateRepacker.RepackAllTemplates | Repack all the templates in ClientBuilder.template_dir. | grr/client_builder/grr_response_client_builder/repacking.py | def RepackAllTemplates(self, upload=False, token=None):
"""Repack all the templates in ClientBuilder.template_dir."""
for template in os.listdir(config.CONFIG["ClientBuilder.template_dir"]):
template_path = os.path.join(config.CONFIG["ClientBuilder.template_dir"],
templa... | def RepackAllTemplates(self, upload=False, token=None):
"""Repack all the templates in ClientBuilder.template_dir."""
for template in os.listdir(config.CONFIG["ClientBuilder.template_dir"]):
template_path = os.path.join(config.CONFIG["ClientBuilder.template_dir"],
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train | _MakeArgs | Build metadata requests list from collection maps. | grr/core/grr_response_core/lib/rdfvalues/cloud.py | def _MakeArgs(amazon_collection_map, google_collection_map):
"""Build metadata requests list from collection maps."""
request_list = []
for url, label in iteritems(amazon_collection_map):
request_list.append(
CloudMetadataRequest(
bios_version_regex=AMAZON_BIOS_REGEX,
service_n... | def _MakeArgs(amazon_collection_map, google_collection_map):
"""Build metadata requests list from collection maps."""
request_list = []
for url, label in iteritems(amazon_collection_map):
request_list.append(
CloudMetadataRequest(
bios_version_regex=AMAZON_BIOS_REGEX,
service_n... | [
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train | MakeGoogleUniqueID | Make the google unique ID of zone/project/id. | grr/core/grr_response_core/lib/rdfvalues/cloud.py | def MakeGoogleUniqueID(cloud_instance):
"""Make the google unique ID of zone/project/id."""
if not (cloud_instance.zone and cloud_instance.project_id and
cloud_instance.instance_id):
raise ValueError("Bad zone/project_id/id: '%s/%s/%s'" %
(cloud_instance.zone, cloud_instance.proje... | def MakeGoogleUniqueID(cloud_instance):
"""Make the google unique ID of zone/project/id."""
if not (cloud_instance.zone and cloud_instance.project_id and
cloud_instance.instance_id):
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train | BuildCloudMetadataRequests | Build the standard set of cloud metadata to collect during interrogate. | grr/core/grr_response_core/lib/rdfvalues/cloud.py | def BuildCloudMetadataRequests():
"""Build the standard set of cloud metadata to collect during interrogate."""
amazon_collection_map = {
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"""Build the standard set of cloud metadata to collect during interrogate."""
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train | ConvertCloudMetadataResponsesToCloudInstance | Convert CloudMetadataResponses to CloudInstance proto.
Ideally we'd just get the client to fill out a CloudInstance proto, but we
need to keep the flexibility of collecting new metadata and creating new
fields without a client push. So instead we bring back essentially a dict of
results and fill the proto on t... | grr/core/grr_response_core/lib/rdfvalues/cloud.py | def ConvertCloudMetadataResponsesToCloudInstance(metadata_responses):
"""Convert CloudMetadataResponses to CloudInstance proto.
Ideally we'd just get the client to fill out a CloudInstance proto, but we
need to keep the flexibility of collecting new metadata and creating new
fields without a client push. So in... | def ConvertCloudMetadataResponsesToCloudInstance(metadata_responses):
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Ideally we'd just get the client to fill out a CloudInstance proto, but we
need to keep the flexibility of collecting new metadata and creating new
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train | Distribution.Record | Records given value. | grr/core/grr_response_core/lib/rdfvalues/stats.py | def Record(self, value):
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self.sum += value
self.count += 1
pos = bisect.bisect(self.bins, value) - 1
if pos < 0:
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train | StatsHistogram.RegisterValue | Puts a given value into an appropriate bin. | grr/core/grr_response_core/lib/rdfvalues/stats.py | def RegisterValue(self, value):
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if self.bins:
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b.num += 1
return
self.bins[-1].num += 1 | def RegisterValue(self, value):
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train | ClientResourcesStats.RegisterResources | Update stats with info about resources consumed by a single client. | grr/core/grr_response_core/lib/rdfvalues/stats.py | def RegisterResources(self, client_resources):
"""Update stats with info about resources consumed by a single client."""
self.user_cpu_stats.RegisterValue(client_resources.cpu_usage.user_cpu_time)
self.system_cpu_stats.RegisterValue(
client_resources.cpu_usage.system_cpu_time)
self.network_bytes... | def RegisterResources(self, client_resources):
"""Update stats with info about resources consumed by a single client."""
self.user_cpu_stats.RegisterValue(client_resources.cpu_usage.user_cpu_time)
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train | EmbeddedRDFValue.payload | Extracts and returns the serialized object. | grr/core/grr_response_core/lib/rdfvalues/protodict.py | def payload(self):
"""Extracts and returns the serialized object."""
try:
rdf_cls = self.classes.get(self.name)
if rdf_cls:
value = rdf_cls.FromSerializedString(self.data)
value.age = self.embedded_age
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TypeError: if the value can't be serialized and raise_on_error is True | grr/core/grr_response_core/lib/rdfvalues/protodict.py | def SetValue(self, value, raise_on_error=True):
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value: value to set
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train | DataBlob.GetValue | Extracts and returns a single value from a DataBlob. | grr/core/grr_response_core/lib/rdfvalues/protodict.py | def GetValue(self, ignore_error=True):
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value: The new data to append to the array.
**kwarg: Create a new element from these keywords.
Returns:
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"""Add another member to the array.
Args:
value: The new data to append to the array.
**kwarg: Create a new element from these keywords.
Returns:
The value which was added. This can be modified further by the caller and
changes will be propag... | def Append(self, value=None, **kwarg):
"""Add another member to the array.
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value: The new data to append to the array.
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train | CpuSample.FromMany | Constructs a single sample that best represents a list of samples.
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samples: An iterable collection of `CpuSample` instances.
Returns:
A `CpuSample` instance representing `samples`.
Raises:
ValueError: If `samples` is empty. | grr/core/grr_response_core/lib/rdfvalues/client_stats.py | def FromMany(cls, samples):
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Args:
samples: An iterable collection of `CpuSample` instances.
Returns:
A `CpuSample` instance representing `samples`.
Raises:
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"""
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Args:
samples: An iterable collection of `CpuSample` instances.
Returns:
A `CpuSample` instance representing `samples`.
Raises:
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train | IOSample.FromMany | Constructs a single sample that best represents a list of samples.
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samples: An iterable collection of `IOSample` instances.
Returns:
An `IOSample` instance representing `samples`.
Raises:
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An `IOSample` instance representing `samples`.
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train | ClientStats.Downsampled | Constructs a copy of given stats but downsampled to given interval.
Args:
stats: A `ClientStats` instance.
interval: A downsampling interval.
Returns:
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stats: A `ClientStats` instance.
interval: A downsampling interval.
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A downsampled `ClientStats` instance.
"""
interval = interval or cls.DEFAULT_SAMPL... | def Downsampled(cls, stats, interval=None):
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stats: A `ClientStats` instance.
interval: A downsampling interval.
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A downsampled `ClientStats` instance.
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train | GetUserInfo | Get a User protobuf for a specific user.
Args:
knowledge_base: An rdf_client.KnowledgeBase object.
user: Username as string. May contain domain like DOMAIN\\user.
Returns:
A User rdfvalue or None | grr/server/grr_response_server/flow_utils.py | def GetUserInfo(knowledge_base, user):
# TODO: This docstring cannot be a raw literal because there are
# issues with raw unicode literals on Python 2. Once support for Python 2 is
# dropped, it can be made raw again.
# pylint: disable=g-docstring-has-escape
"""Get a User protobuf for a specific user.
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# TODO: This docstring cannot be a raw literal because there are
# issues with raw unicode literals on Python 2. Once support for Python 2 is
# dropped, it can be made raw again.
# pylint: disable=g-docstring-has-escape
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train | UpdateVFSFileAndWait | Waits for a file to be updated on the client.
Calls the UpdateVFSFile flow on a urn and waits for both it and the
ListDirectory flow it calls to finish.
Note that this is needed because any flows UpdateVFSFile calls via
VFS Update methods will not become child flows of UpdateVFSFile,
and therefore waiting f... | grr/server/grr_response_server/flow_utils.py | def UpdateVFSFileAndWait(client_id,
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token=None,
timeout=DEFAULT_TIMEOUT):
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Calls the UpdateVFSFile flow on a urn and waits for both it and the
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train | WaitForFlow | Waits for a flow to finish, polling while we wait.
Args:
flow_urn: The urn of the flow to wait for.
token: The datastore access token.
timeout: How long to wait before giving up, usually because the client has
gone away.
max_sleep_time: The initial and longest time to wait in between polls.
... | grr/server/grr_response_server/flow_utils.py | def WaitForFlow(flow_urn,
token=None,
timeout=DEFAULT_TIMEOUT,
max_sleep_time=1,
min_sleep_time=0.2,
dampening_multiplier=0.9):
"""Waits for a flow to finish, polling while we wait.
Args:
flow_urn: The urn of the flow to wait for.
... | def WaitForFlow(flow_urn,
token=None,
timeout=DEFAULT_TIMEOUT,
max_sleep_time=1,
min_sleep_time=0.2,
dampening_multiplier=0.9):
"""Waits for a flow to finish, polling while we wait.
Args:
flow_urn: The urn of the flow to wait for.
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train | StartFlowAndWait | Runs a flow and waits for it to finish.
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client_id: The client id of the client to run on.
token: The datastore access token.
timeout: How long to wait for a flow to complete, maximum.
**flow_args: Pass through to flow.
Returns:
The urn of the flow that was run. | grr/server/grr_response_server/flow_utils.py | def StartFlowAndWait(client_id,
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timeout=DEFAULT_TIMEOUT,
**flow_args):
"""Runs a flow and waits for it to finish.
Args:
client_id: The client id of the client to run on.
token: The datastore access token.
timeout: How long to wa... | def StartFlowAndWait(client_id,
token=None,
timeout=DEFAULT_TIMEOUT,
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"""Runs a flow and waits for it to finish.
Args:
client_id: The client id of the client to run on.
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train | InterpolatePath | Take a string as a path on a client and interpolate with client data.
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path: A single string/unicode to be interpolated.
knowledge_base: An rdf_client.KnowledgeBase object.
users: A list of string usernames, or None.
path_args: A dict of additional args to use in interpolation. These take
... | grr/server/grr_response_server/flow_utils.py | def InterpolatePath(path, knowledge_base, users=None, path_args=None, depth=0):
"""Take a string as a path on a client and interpolate with client data.
Args:
path: A single string/unicode to be interpolated.
knowledge_base: An rdf_client.KnowledgeBase object.
users: A list of string usernames, or None... | def InterpolatePath(path, knowledge_base, users=None, path_args=None, depth=0):
"""Take a string as a path on a client and interpolate with client data.
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path: A single string/unicode to be interpolated.
knowledge_base: An rdf_client.KnowledgeBase object.
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train | Find.ListDirectory | A recursive generator of files. | grr/client/grr_response_client/client_actions/searching.py | def ListDirectory(self, pathspec, depth=0):
"""A recursive generator of files."""
# Limit recursion depth
if depth >= self.request.max_depth:
return
try:
fd = vfs.VFSOpen(pathspec, progress_callback=self.Progress)
files = fd.ListFiles(ext_attrs=self.request.collect_ext_attrs)
exce... | def ListDirectory(self, pathspec, depth=0):
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# Limit recursion depth
if depth >= self.request.max_depth:
return
try:
fd = vfs.VFSOpen(pathspec, progress_callback=self.Progress)
files = fd.ListFiles(ext_attrs=self.request.collect_ext_attrs)
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train | Find.BuildChecks | Parses request and returns a list of filter callables.
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Args:
request: A FindSpec that describes the search.
Returns:
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Each callable will be called with the StatEntry and returns True if the
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Args:
request: A FindSpec that describes the search.
Returns:
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train | Find.Run | Runs the Find action. | grr/client/grr_response_client/client_actions/searching.py | def Run(self, request):
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self.request = request
filters = self.BuildChecks(request)
files_checked = 0
for f in self.ListDirectory(request.pathspec):
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"""Runs the Find action."""
self.request = request
filters = self.BuildChecks(request)
files_checked = 0
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train | Grep.FindRegex | Search the data for a hit. | grr/client/grr_response_client/client_actions/searching.py | def FindRegex(self, regex, data):
"""Search the data for a hit."""
for match in re.finditer(regex, data, flags=re.I | re.S | re.M):
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train | Grep.FindLiteral | Search the data for a hit. | grr/client/grr_response_client/client_actions/searching.py | def FindLiteral(self, pattern, data):
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# We assume here that data.find does not make a copy of pattern.
offset = data.find(pattern, offset)
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train | Grep.Run | Search the file for the pattern.
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different functions to search for matching patterns. In every
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This implements the grep algorithm used to scan files. It reads
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train | StopHuntIfCrashLimitExceeded | Stops the hunt if number of crashes exceeds the limit. | grr/server/grr_response_server/hunt.py | def StopHuntIfCrashLimitExceeded(hunt_id):
"""Stops the hunt if number of crashes exceeds the limit."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
# Do nothing if the hunt is already stopped.
if hunt_obj.hunt_state == rdf_hunt_objects.Hunt.HuntState.STOPPED:
return hunt_obj
if hunt_obj.crash_l... | def StopHuntIfCrashLimitExceeded(hunt_id):
"""Stops the hunt if number of crashes exceeds the limit."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
# Do nothing if the hunt is already stopped.
if hunt_obj.hunt_state == rdf_hunt_objects.Hunt.HuntState.STOPPED:
return hunt_obj
if hunt_obj.crash_l... | [
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] | google/grr | python | https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/server/grr_response_server/hunt.py#L94-L111 | [
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train | StopHuntIfCPUOrNetworkLimitsExceeded | Stops the hunt if average limites are exceeded. | grr/server/grr_response_server/hunt.py | def StopHuntIfCPUOrNetworkLimitsExceeded(hunt_id):
"""Stops the hunt if average limites are exceeded."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
# Do nothing if the hunt is already stopped.
if hunt_obj.hunt_state == rdf_hunt_objects.Hunt.HuntState.STOPPED:
return hunt_obj
hunt_counters = da... | def StopHuntIfCPUOrNetworkLimitsExceeded(hunt_id):
"""Stops the hunt if average limites are exceeded."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
# Do nothing if the hunt is already stopped.
if hunt_obj.hunt_state == rdf_hunt_objects.Hunt.HuntState.STOPPED:
return hunt_obj
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train | CompleteHuntIfExpirationTimeReached | Marks the hunt as complete if it's past its expiry time. | grr/server/grr_response_server/hunt.py | def CompleteHuntIfExpirationTimeReached(hunt_obj):
"""Marks the hunt as complete if it's past its expiry time."""
# TODO(hanuszczak): This should not set the hunt state to `COMPLETED` but we
# should have a sparate `EXPIRED` state instead and set that.
if (hunt_obj.hunt_state not in [
rdf_hunt_objects.Hun... | def CompleteHuntIfExpirationTimeReached(hunt_obj):
"""Marks the hunt as complete if it's past its expiry time."""
# TODO(hanuszczak): This should not set the hunt state to `COMPLETED` but we
# should have a sparate `EXPIRED` state instead and set that.
if (hunt_obj.hunt_state not in [
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] | google/grr | python | https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/server/grr_response_server/hunt.py#L180-L194 | [
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train | CreateHunt | Creates a hunt using a given hunt object. | grr/server/grr_response_server/hunt.py | def CreateHunt(hunt_obj):
"""Creates a hunt using a given hunt object."""
data_store.REL_DB.WriteHuntObject(hunt_obj)
if hunt_obj.HasField("output_plugins"):
output_plugins_states = flow.GetOutputPluginStates(
hunt_obj.output_plugins,
source="hunts/%s" % hunt_obj.hunt_id,
token=access... | def CreateHunt(hunt_obj):
"""Creates a hunt using a given hunt object."""
data_store.REL_DB.WriteHuntObject(hunt_obj)
if hunt_obj.HasField("output_plugins"):
output_plugins_states = flow.GetOutputPluginStates(
hunt_obj.output_plugins,
source="hunts/%s" % hunt_obj.hunt_id,
token=access... | [
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train | CreateAndStartHunt | Creates and starts a new hunt. | grr/server/grr_response_server/hunt.py | def CreateAndStartHunt(flow_name, flow_args, creator, **kwargs):
"""Creates and starts a new hunt."""
# This interface takes a time when the hunt expires. However, the legacy hunt
# starting interface took an rdfvalue.Duration object which was then added to
# the current time to get the expiry. This check exis... | def CreateAndStartHunt(flow_name, flow_args, creator, **kwargs):
"""Creates and starts a new hunt."""
# This interface takes a time when the hunt expires. However, the legacy hunt
# starting interface took an rdfvalue.Duration object which was then added to
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train | _ScheduleGenericHunt | Adds foreman rules for a generic hunt. | grr/server/grr_response_server/hunt.py | def _ScheduleGenericHunt(hunt_obj):
"""Adds foreman rules for a generic hunt."""
# TODO: Migrate foreman conditions to use relation expiration
# durations instead of absolute timestamps.
foreman_condition = foreman_rules.ForemanCondition(
creation_time=rdfvalue.RDFDatetime.Now(),
expiration_time=hun... | def _ScheduleGenericHunt(hunt_obj):
"""Adds foreman rules for a generic hunt."""
# TODO: Migrate foreman conditions to use relation expiration
# durations instead of absolute timestamps.
foreman_condition = foreman_rules.ForemanCondition(
creation_time=rdfvalue.RDFDatetime.Now(),
expiration_time=hun... | [
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] | google/grr | python | https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/server/grr_response_server/hunt.py#L237-L251 | [
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train | _ScheduleVariableHunt | Schedules flows for a variable hunt. | grr/server/grr_response_server/hunt.py | def _ScheduleVariableHunt(hunt_obj):
"""Schedules flows for a variable hunt."""
if hunt_obj.client_rate != 0:
raise VariableHuntCanNotHaveClientRateError(hunt_obj.hunt_id,
hunt_obj.client_rate)
seen_clients = set()
for flow_group in hunt_obj.args.variable.flo... | def _ScheduleVariableHunt(hunt_obj):
"""Schedules flows for a variable hunt."""
if hunt_obj.client_rate != 0:
raise VariableHuntCanNotHaveClientRateError(hunt_obj.hunt_id,
hunt_obj.client_rate)
seen_clients = set()
for flow_group in hunt_obj.args.variable.flo... | [
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] | google/grr | python | https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/server/grr_response_server/hunt.py#L254-L285 | [
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train | StartHunt | Starts a hunt with a given id. | grr/server/grr_response_server/hunt.py | def StartHunt(hunt_id):
"""Starts a hunt with a given id."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
num_hunt_clients = data_store.REL_DB.CountHuntFlows(hunt_id)
if hunt_obj.hunt_state != hunt_obj.HuntState.PAUSED:
raise OnlyPausedHuntCanBeStartedError(hunt_obj)
data_store.REL_DB.UpdateHun... | def StartHunt(hunt_id):
"""Starts a hunt with a given id."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
num_hunt_clients = data_store.REL_DB.CountHuntFlows(hunt_id)
if hunt_obj.hunt_state != hunt_obj.HuntState.PAUSED:
raise OnlyPausedHuntCanBeStartedError(hunt_obj)
data_store.REL_DB.UpdateHun... | [
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] | google/grr | python | https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/server/grr_response_server/hunt.py#L288-L313 | [
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train | PauseHunt | Pauses a hunt with a given id. | grr/server/grr_response_server/hunt.py | def PauseHunt(hunt_id, reason=None):
"""Pauses a hunt with a given id."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
if hunt_obj.hunt_state != hunt_obj.HuntState.STARTED:
raise OnlyStartedHuntCanBePausedError(hunt_obj)
data_store.REL_DB.UpdateHuntObject(
hunt_id, hunt_state=hunt_obj.HuntSt... | def PauseHunt(hunt_id, reason=None):
"""Pauses a hunt with a given id."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
if hunt_obj.hunt_state != hunt_obj.HuntState.STARTED:
raise OnlyStartedHuntCanBePausedError(hunt_obj)
data_store.REL_DB.UpdateHuntObject(
hunt_id, hunt_state=hunt_obj.HuntSt... | [
"Pauses",
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] | google/grr | python | https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/server/grr_response_server/hunt.py#L316-L327 | [
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train | StopHunt | Stops a hunt with a given id. | grr/server/grr_response_server/hunt.py | def StopHunt(hunt_id, reason=None):
"""Stops a hunt with a given id."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
if hunt_obj.hunt_state not in [
hunt_obj.HuntState.STARTED, hunt_obj.HuntState.PAUSED
]:
raise OnlyStartedOrPausedHuntCanBeStoppedError(hunt_obj)
data_store.REL_DB.UpdateHun... | def StopHunt(hunt_id, reason=None):
"""Stops a hunt with a given id."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
if hunt_obj.hunt_state not in [
hunt_obj.HuntState.STARTED, hunt_obj.HuntState.PAUSED
]:
raise OnlyStartedOrPausedHuntCanBeStoppedError(hunt_obj)
data_store.REL_DB.UpdateHun... | [
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] | google/grr | python | https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/server/grr_response_server/hunt.py#L330-L352 | [
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train | UpdateHunt | Updates a hunt (it must be paused to be updated). | grr/server/grr_response_server/hunt.py | def UpdateHunt(hunt_id, client_limit=None, client_rate=None, duration=None):
"""Updates a hunt (it must be paused to be updated)."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
if hunt_obj.hunt_state != hunt_obj.HuntState.PAUSED:
raise OnlyPausedHuntCanBeModifiedError(hunt_obj)
data_store.REL_DB.... | def UpdateHunt(hunt_id, client_limit=None, client_rate=None, duration=None):
"""Updates a hunt (it must be paused to be updated)."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
if hunt_obj.hunt_state != hunt_obj.HuntState.PAUSED:
raise OnlyPausedHuntCanBeModifiedError(hunt_obj)
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train | StartHuntFlowOnClient | Starts a flow corresponding to a given hunt on a given client. | grr/server/grr_response_server/hunt.py | def StartHuntFlowOnClient(client_id, hunt_id):
"""Starts a flow corresponding to a given hunt on a given client."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
hunt_obj = CompleteHuntIfExpirationTimeReached(hunt_obj)
# There may be a little race between foreman rules being removed and
# foreman sche... | def StartHuntFlowOnClient(client_id, hunt_id):
"""Starts a flow corresponding to a given hunt on a given client."""
hunt_obj = data_store.REL_DB.ReadHuntObject(hunt_id)
hunt_obj = CompleteHuntIfExpirationTimeReached(hunt_obj)
# There may be a little race between foreman rules being removed and
# foreman sche... | [
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] | google/grr | python | https://github.com/google/grr/blob/5cef4e8e2f0d5df43ea4877e9c798e0bf60bfe74/grr/server/grr_response_server/hunt.py#L378-L432 | [
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