def create_random_rule(self, log_atom):
"""Create a random existing path rule or value match rule."""
parser_match = log_atom.parser_match
sub_rules = []
all_keys = list(parser_match.get_match_dictionary().keys())
attribute_count = get_log_int(self.max_rule_attributes) + 1
while attribute_count > 0:
key_pos = random.randint(0, len(all_keys) - 1)
key_name = all_keys[key_pos]
all_keys = all_keys[:key_pos] + all_keys[key_pos + 1:]
key_value = parser_match.get_match_dictionary().get(key_name).match_object
# Not much sense handling parsed date values in this implementation, so just ignore this attribute.
if (isinstance(key_value, tuple)) and (isinstance(key_value[0], datetime)):
if not all_keys:
break
continue
attribute_count -= 1
rule_type = random.randint(0, 1)
if rule_type == 0:
sub_rules.append(Rules.PathExistsMatchRule(key_name))
elif rule_type == 1:
sub_rules.append(Rules.ValueMatchRule(key_name, key_value))
else:
raise Exception('Invalid rule type')
if not all_keys:
break
if len(sub_rules) > 1:
return Rules.AndMatchRule(sub_rules)
if len(sub_rules) > 0:
return sub_rules[0]
return None
def setUp(self):
TestBase.setUp(self)
self.correlation_rule = CorrelationRule('Correlation', 1, 1.2, max_artefacts_a_for_single_b=1, artefact_match_parameters=[
('/model/sequence1/Value2Value', '/model/sequence2/Value3Value')])
self.a_class_selector = EventClassSelector('Selector1', [self.correlation_rule], None)
self.b_class_selector = EventClassSelector('Selector2', None, [self.correlation_rule])
self.rules = []
self.rules.append(Rules.PathExistsMatchRule('/model/sequence1/Value2Key', self.a_class_selector))
self.rules.append(Rules.PathExistsMatchRule('/model/sequence2/Value3Key', self.b_class_selector))
def create_random_rule(self, log_atom):
"""Create a random existing path rule or value match rule."""
parser_match = log_atom.parser_match
sub_rules = []
all_keys = list(parser_match.get_match_dictionary().keys())
attribute_count = self.min_rule_attributes + get_log_int(
self.max_rule_attributes - self.min_rule_attributes)
while attribute_count > 0:
key_pos = random.randint(0, len(all_keys) - 1)
key_name = all_keys[key_pos]
all_keys = all_keys[:key_pos] + all_keys[key_pos + 1:]
key_value = parser_match.get_match_dictionary().get(
key_name).match_object
# Not much sense handling parsed date values in this implementation, so just ignore this attribute.
if (isinstance(key_value, tuple)) and (isinstance(
key_value[0], datetime)):
if not all_keys:
break
continue
attribute_count -= 1
rule_type = 1 # default is value_match only if none specified
if self.use_path_match and not self.use_value_match:
rule_type = 0
if not self.use_path_match and self.use_value_match:
rule_type = 1
if self.use_path_match and self.use_value_match:
rule_type = random.randint(0, 1)
if rule_type == 0:
sub_rules.append(Rules.PathExistsMatchRule(key_name))
elif rule_type == 1:
sub_rules.append(Rules.ValueMatchRule(key_name, key_value))
else:
msg = 'Invalid rule type'
logging.getLogger(DEBUG_LOG_NAME).error(msg)
raise Exception(msg)
if not all_keys:
break
if len(sub_rules) > 1:
return Rules.AndMatchRule(sub_rules)
if len(sub_rules) > 0:
return sub_rules[0]
return None
def build_analysis_pipeline(analysis_context):
"""
Define the function to create pipeline for parsing the log data.
It has also to define an AtomizerFactory to instruct aminer how to process incoming data streams to create log atoms from them.
"""
# Build the parsing model:
service_children_disk_report = [
FixedDataModelElement(
'Space',
b' Current Disk Data is: Filesystem Type Size Used Avail Use%'
),
DelimitedDataModelElement('Data', b'%'),
AnyByteDataModelElement('Rest')
]
service_children_login_details = [
FixedDataModelElement('User', b'User '),
DelimitedDataModelElement('Username', b' '),
FixedWordlistDataModelElement('Status',
[b' logged in', b' logged out']),
OptionalMatchModelElement(
'PastTime',
SequenceModelElement('Time', [
FixedDataModelElement('Blank', b' '),
DecimalIntegerValueModelElement('Minutes'),
FixedDataModelElement('Ago', b' minutes ago.')
]))
]
service_children_cron_job = [
DateTimeModelElement('DTM', b'%Y-%m-%d %H:%M:%S'),
FixedDataModelElement('UNameSpace1', b' '),
DelimitedDataModelElement('UName', b' '),
FixedDataModelElement('UNameSpace2', b' '),
DelimitedDataModelElement('User', b' '),
FixedDataModelElement('Cron', b' cron['),
DecimalIntegerValueModelElement('JobNumber'),
FixedDataModelElement('Details', b']: Job `cron.daily` started.')
]
service_children_random_time = [
FixedDataModelElement('Space', b'Random: '),
DecimalIntegerValueModelElement('Random')
]
service_children_sensors = [
SequenceModelElement('CPUTemp', [
FixedDataModelElement('FixedTemp', b'CPU Temp: '),
DecimalIntegerValueModelElement('Temp'),
FixedDataModelElement('Degrees', b'\xc2\xb0C')
]),
FixedDataModelElement('Space1', b', '),
SequenceModelElement('CPUWorkload', [
FixedDataModelElement('FixedWorkload', b'CPUWorkload: '),
DecimalIntegerValueModelElement('Workload'),
FixedDataModelElement('Percent', b'%')
]),
FixedDataModelElement('Space2', b', '),
DateTimeModelElement('DTM', b'%Y-%m-%d %H:%M:%S')
]
service_children_user_ip_address = [
FixedDataModelElement('User', b'User '),
DelimitedDataModelElement('Username', b' '),
FixedDataModelElement('Action', b' changed IP address to '),
IpAddressDataModelElement('IP')
]
service_children_cron_job_announcement = [
DateTimeModelElement('DTM', b'%Y-%m-%d %H:%M:%S'),
FixedDataModelElement('Space', b' '),
DelimitedDataModelElement('UName', b' '),
FixedDataModelElement('Cron', b' cron['),
DecimalIntegerValueModelElement('JobNumber'),
FixedDataModelElement('Run', b']: Will run job `'),
FixedWordlistDataModelElement(
'CronType',
[b'cron.daily', b'cron.hourly', b'cron.monthly', b'cron.weekly']),
FixedDataModelElement('StartTime', b'\' in 5 min.')
]
service_children_cron_job_execution = [
DateTimeModelElement('DTM', b'%Y-%m-%d %H:%M:%S'),
FixedDataModelElement('Space1', b' '),
DelimitedDataModelElement('UName', b' '),
FixedDataModelElement('Cron', b' cron['),
DecimalIntegerValueModelElement('JobNumber'),
FixedDataModelElement('Job', b']: Job `'),
FixedWordlistDataModelElement(
'CronType',
[b'cron.daily', b'cron.hourly', b'cron.monthly', b'cron.weekly']),
FixedDataModelElement('Started', b'\' started')
]
parsing_model = FirstMatchModelElement('model', [
SequenceModelElement('CronAnnouncement',
service_children_cron_job_announcement),
SequenceModelElement('CronExecution',
service_children_cron_job_execution),
SequenceModelElement('DailyCron', service_children_cron_job),
SequenceModelElement('DiskReport', service_children_disk_report),
SequenceModelElement('LoginDetails', service_children_login_details),
DecimalIntegerValueModelElement('Random'),
SequenceModelElement('RandomTime', service_children_random_time),
SequenceModelElement('Sensors', service_children_sensors),
SequenceModelElement('IPAddresses', service_children_user_ip_address)
])
# Some generic imports.
from aminer.analysis import AtomFilters
# Create all global handler lists here and append the real handlers later on.
# Use this filter to distribute all atoms to the analysis handlers.
atom_filters = AtomFilters.SubhandlerFilter(None)
analysis_context.register_component(atom_filters,
component_name="AtomFilter")
from aminer.analysis.TimestampCorrectionFilters import SimpleMonotonicTimestampAdjust
simple_monotonic_timestamp_adjust = SimpleMonotonicTimestampAdjust(
[atom_filters])
analysis_context.register_component(
simple_monotonic_timestamp_adjust,
component_name="SimpleMonotonicTimestampAdjust")
from aminer.events.StreamPrinterEventHandler import StreamPrinterEventHandler
stream_printer_event_handler = StreamPrinterEventHandler(
analysis_context) # skipcq: BAN-B108
from aminer.events.Utils import VolatileLogarithmicBackoffEventHistory
volatile_logarithmic_backoff_event_history = VolatileLogarithmicBackoffEventHistory(
100)
anomaly_event_handlers = [
stream_printer_event_handler,
volatile_logarithmic_backoff_event_history
]
analysis_context.register_component(
volatile_logarithmic_backoff_event_history,
component_name="VolatileLogarithmicBackoffEventHistory")
# Now define the AtomizerFactory using the model. A simple line based one is usually sufficient.
from aminer.input.SimpleByteStreamLineAtomizerFactory import SimpleByteStreamLineAtomizerFactory
analysis_context.atomizer_factory = SimpleByteStreamLineAtomizerFactory(
parsing_model, [simple_monotonic_timestamp_adjust],
anomaly_event_handlers)
# Just report all unparsed atoms to the event handlers.
from aminer.analysis.UnparsedAtomHandlers import SimpleUnparsedAtomHandler
simple_unparsed_atom_handler = SimpleUnparsedAtomHandler(
anomaly_event_handlers)
atom_filters.add_handler(simple_unparsed_atom_handler,
stop_when_handled_flag=True)
analysis_context.register_component(simple_unparsed_atom_handler,
component_name="UnparsedHandler")
from aminer.analysis.TimestampsUnsortedDetector import TimestampsUnsortedDetector
timestamps_unsorted_detector = TimestampsUnsortedDetector(
analysis_context.aminer_config, anomaly_event_handlers)
atom_filters.add_handler(timestamps_unsorted_detector)
analysis_context.register_component(
timestamps_unsorted_detector,
component_name="TimestampsUnsortedDetector")
from aminer.analysis import Rules
from aminer.analysis.AllowlistViolationDetector import AllowlistViolationDetector
allowlist_rules = [
Rules.OrMatchRule([
Rules.AndMatchRule([
Rules.PathExistsMatchRule(
'/model/LoginDetails/PastTime/Time/Minutes'),
Rules.NegationMatchRule(
Rules.ValueMatchRule('/model/LoginDetails/Username',
b'root'))
]),
Rules.AndMatchRule([
Rules.NegationMatchRule(
Rules.PathExistsMatchRule(
'/model/LoginDetails/PastTime/Time/Minutes')),
Rules.PathExistsMatchRule('/model/LoginDetails')
]),
Rules.NegationMatchRule(
Rules.PathExistsMatchRule('/model/LoginDetails'))
])
]
# This rule list should trigger, when the line does not look like: User root (logged in, logged out)
# or User 'username' (logged in, logged out) x minutes ago.
allowlist_violation_detector = AllowlistViolationDetector(
analysis_context.aminer_config, allowlist_rules,
anomaly_event_handlers)
analysis_context.register_component(allowlist_violation_detector,
component_name="Allowlist")
atom_filters.add_handler(allowlist_violation_detector)
from aminer.analysis.ParserCount import ParserCount
parser_count = ParserCount(analysis_context.aminer_config, None,
anomaly_event_handlers, 10)
analysis_context.register_component(parser_count,
component_name="ParserCount")
atom_filters.add_handler(parser_count)
from aminer.analysis.EventCorrelationDetector import EventCorrelationDetector
ecd = EventCorrelationDetector(analysis_context.aminer_config,
anomaly_event_handlers,
check_rules_flag=True,
hypothesis_max_delta_time=1.0,
auto_include_flag=True)
analysis_context.register_component(
ecd, component_name="EventCorrelationDetector")
atom_filters.add_handler(ecd)
from aminer.analysis.NewMatchPathDetector import NewMatchPathDetector
new_match_path_detector = NewMatchPathDetector(
analysis_context.aminer_config,
anomaly_event_handlers,
auto_include_flag=True)
analysis_context.register_component(new_match_path_detector,
component_name="NewMatchPath")
atom_filters.add_handler(new_match_path_detector)
def tuple_transformation_function(match_value_list):
"""Only allow output of the EnhancedNewMatchPathValueComboDetector after every 10000th element."""
extra_data = enhanced_new_match_path_value_combo_detector.known_values_dict.get(
tuple(match_value_list))
if extra_data is not None:
mod = 10000
if (extra_data[2] + 1) % mod == 0:
enhanced_new_match_path_value_combo_detector.auto_include_flag = False
else:
enhanced_new_match_path_value_combo_detector.auto_include_flag = True
return match_value_list
from aminer.analysis.EnhancedNewMatchPathValueComboDetector import EnhancedNewMatchPathValueComboDetector
enhanced_new_match_path_value_combo_detector = EnhancedNewMatchPathValueComboDetector(
analysis_context.aminer_config,
['/model/DailyCron/UName', '/model/DailyCron/JobNumber'],
anomaly_event_handlers,
auto_include_flag=False,
tuple_transformation_function=tuple_transformation_function)
analysis_context.register_component(
enhanced_new_match_path_value_combo_detector,
component_name="EnhancedNewValueCombo")
atom_filters.add_handler(enhanced_new_match_path_value_combo_detector)
from aminer.analysis.HistogramAnalysis import HistogramAnalysis, LinearNumericBinDefinition, ModuloTimeBinDefinition, \
PathDependentHistogramAnalysis
modulo_time_bin_definition = ModuloTimeBinDefinition(
86400, 3600, 0, 1, 24, True)
linear_numeric_bin_definition = LinearNumericBinDefinition(50, 5, 20, True)
histogram_analysis = HistogramAnalysis(
analysis_context.aminer_config,
[('/model/RandomTime/Random', modulo_time_bin_definition),
('/model/Random', linear_numeric_bin_definition)], 10,
anomaly_event_handlers)
analysis_context.register_component(histogram_analysis,
component_name="HistogramAnalysis")
atom_filters.add_handler(histogram_analysis)
path_dependent_histogram_analysis = PathDependentHistogramAnalysis(
analysis_context.aminer_config, '/model/RandomTime',
modulo_time_bin_definition, 10, anomaly_event_handlers)
analysis_context.register_component(
path_dependent_histogram_analysis,
component_name="PathDependentHistogramAnalysis")
atom_filters.add_handler(path_dependent_histogram_analysis)
from aminer.analysis.MatchValueAverageChangeDetector import MatchValueAverageChangeDetector
match_value_average_change_detector = MatchValueAverageChangeDetector(
analysis_context.aminer_config, anomaly_event_handlers, None,
['/model/Random'], 100, 10)
analysis_context.register_component(
match_value_average_change_detector,
component_name="MatchValueAverageChange")
atom_filters.add_handler(match_value_average_change_detector)
import sys
from aminer.analysis.MatchValueStreamWriter import MatchValueStreamWriter
match_value_stream_writer = MatchValueStreamWriter(sys.stdout, [
'/model/Sensors/CPUTemp', '/model/Sensors/CPUWorkload',
'/model/Sensors/DTM'
], b';', b'')
analysis_context.register_component(
match_value_stream_writer, component_name="MatchValueStreamWriter")
atom_filters.add_handler(match_value_stream_writer)
from aminer.analysis.NewMatchPathValueComboDetector import NewMatchPathValueComboDetector
new_match_path_value_combo_detector = NewMatchPathValueComboDetector(
analysis_context.aminer_config,
['/model/IPAddresses/Username', '/model/IPAddresses/IP'],
anomaly_event_handlers,
auto_include_flag=False)
analysis_context.register_component(
new_match_path_value_combo_detector,
component_name="NewMatchPathValueCombo")
atom_filters.add_handler(new_match_path_value_combo_detector)
from aminer.analysis.NewMatchIdValueComboDetector import NewMatchIdValueComboDetector
new_match_id_value_combo_detector = NewMatchIdValueComboDetector(
analysis_context.aminer_config,
['/model/type/path/name', '/model/type/syscall/syscall'],
anomaly_event_handlers,
id_path_list=['/model/type/path/id', '/model/type/syscall/id'],
min_allowed_time_diff=5,
auto_include_flag=True,
allow_missing_values_flag=True,
output_log_line=True)
analysis_context.register_component(
new_match_id_value_combo_detector,
component_name="NewMatchIdValueComboDetector")
atom_filters.add_handler(new_match_id_value_combo_detector)
from aminer.analysis.NewMatchPathValueDetector import NewMatchPathValueDetector
new_match_path_value_detector = NewMatchPathValueDetector(
analysis_context.aminer_config,
['/model/DailyCron/Job Number', '/model/IPAddresses/Username'],
anomaly_event_handlers,
auto_include_flag=False)
analysis_context.register_component(new_match_path_value_detector,
component_name="NewMatchPathValue")
atom_filters.add_handler(new_match_path_value_detector)
from aminer.analysis.MissingMatchPathValueDetector import MissingMatchPathValueDetector
missing_match_path_value_detector = MissingMatchPathValueDetector(
analysis_context.aminer_config, ['/model/DiskReport/Space'],
anomaly_event_handlers,
auto_include_flag=False,
default_interval=2,
realert_interval=5)
analysis_context.register_component(missing_match_path_value_detector,
component_name="MissingMatch")
atom_filters.add_handler(missing_match_path_value_detector)
from aminer.analysis.TimeCorrelationDetector import TimeCorrelationDetector
time_correlation_detector = TimeCorrelationDetector(
analysis_context.aminer_config,
anomaly_event_handlers,
2,
min_rule_attributes=1,
max_rule_attributes=5,
record_count_before_event=70000,
output_log_line=True)
analysis_context.register_component(
time_correlation_detector, component_name="TimeCorrelationDetector")
atom_filters.add_handler(time_correlation_detector)
from aminer.analysis.TimeCorrelationViolationDetector import TimeCorrelationViolationDetector, CorrelationRule, EventClassSelector
cron_job_announcement = CorrelationRule(
'CronJobAnnouncement',
5,
6,
max_artefacts_a_for_single_b=1,
artefact_match_parameters=[('/model/CronAnnouncement/JobNumber',
'/model/CronExecution/JobNumber')])
a_class_selector = EventClassSelector('Announcement',
[cron_job_announcement], None)
b_class_selector = EventClassSelector('Execution', None,
[cron_job_announcement])
rules = [
Rules.PathExistsMatchRule('/model/CronAnnouncement/Run',
a_class_selector),
Rules.PathExistsMatchRule('/model/CronExecution/Job', b_class_selector)
]
time_correlation_violation_detector = TimeCorrelationViolationDetector(
analysis_context.aminer_config, rules, anomaly_event_handlers)
analysis_context.register_component(
time_correlation_violation_detector,
component_name="TimeCorrelationViolationDetector")
atom_filters.add_handler(time_correlation_violation_detector)
from aminer.events.DefaultMailNotificationEventHandler import DefaultMailNotificationEventHandler
if DefaultMailNotificationEventHandler.CONFIG_KEY_MAIL_TARGET_ADDRESS in analysis_context.aminer_config.config_properties:
mail_notification_handler = DefaultMailNotificationEventHandler(
analysis_context)
analysis_context.register_component(mail_notification_handler,
component_name="MailHandler")
anomaly_event_handlers.append(mail_notification_handler)
def build_analysis_pipeline(analysis_context):
"""
Define the function to create pipeline for parsing the log data.
It has also to define an AtomizerFactory to instruct aminer how to process incoming data streams to create log atoms from them.
"""
date_format_string = b'%Y-%m-%d %H:%M:%S'
cron = b' cron['
# Build the parsing model:
service_children_disk_report = [
FixedDataModelElement('Space', b' Current Disk Data is: Filesystem Type Size Used Avail Use%'),
DelimitedDataModelElement('Data', b'%'), AnyByteDataModelElement('Rest')]
service_children_login_details = [
FixedDataModelElement('User/LoginDetails', b'User '), DelimitedDataModelElement('Username', b' '),
FixedWordlistDataModelElement('Status', [b' logged in', b' logged out']),
OptionalMatchModelElement('PastTime', SequenceModelElement('Time', [
FixedDataModelElement('Blank', b' '), DecimalIntegerValueModelElement('Minutes'),
FixedDataModelElement('Ago', b' minutes ago.')]))]
service_children_cron_job = [
DateTimeModelElement('DTM', date_format_string), FixedDataModelElement('UNameSpace1', b' '),
DelimitedDataModelElement('UName', b' '), FixedDataModelElement('UNameSpace2', b' '), DelimitedDataModelElement('User', b' '),
FixedDataModelElement('Cron', cron), DecimalIntegerValueModelElement('JobNumber'),
FixedDataModelElement('Details', b']: Job `cron.daily` started.')]
service_children_random_time = [FixedDataModelElement('Space', b'Random: '), DecimalIntegerValueModelElement('Random')]
service_children_sensors = [SequenceModelElement('CPUTemp', [
FixedDataModelElement('FixedTemp', b'CPU Temp: '), DecimalIntegerValueModelElement('Temp'),
FixedDataModelElement('Degrees', b'\xc2\xb0C')]), FixedDataModelElement('Space1', b', '), SequenceModelElement('CPUWorkload', [
FixedDataModelElement('FixedWorkload', b'CPU Workload: '), DecimalIntegerValueModelElement('Workload'),
FixedDataModelElement('Percent', b'%')]), FixedDataModelElement('Space2', b', '),
DateTimeModelElement('DTM', date_format_string)]
service_children_user_ip_address = [
FixedDataModelElement('User/UserIPAddress', b'User '), DelimitedDataModelElement('Username', b' '),
FixedDataModelElement('Action', b' changed IP address to '), IpAddressDataModelElement('IP')]
service_children_cron_job_announcement = [
DateTimeModelElement('DTM', date_format_string), FixedDataModelElement('Space', b' '),
DelimitedDataModelElement('UName', b' '), FixedDataModelElement('Cron', cron), DecimalIntegerValueModelElement('JobNumber'),
FixedDataModelElement('Run', b']: Will run job `'),
FixedWordlistDataModelElement('CronType', [b'cron.daily', b'cron.hourly', b'cron.monthly', b'cron.weekly']),
FixedDataModelElement('StartTime', b'\' in 5 min.')]
service_children_cron_job_execution = [
DateTimeModelElement('DTM', date_format_string), FixedDataModelElement('Space1', b' '),
DelimitedDataModelElement('UName', b' '), FixedDataModelElement('Cron', cron), DecimalIntegerValueModelElement('JobNumber'),
FixedDataModelElement('Job', b']: Job `'),
FixedWordlistDataModelElement('CronType', [b'cron.daily', b'cron.hourly', b'cron.monthly', b'cron.weekly']),
FixedDataModelElement('Started', b'\' started')]
service_children_audit = [SequenceModelElement('path', [
FixedDataModelElement('type', b'type=PATH '), FixedDataModelElement('msg_audit', b'msg=audit('),
DelimitedDataModelElement('msg', b':'), FixedDataModelElement('placeholder', b':'), DecimalIntegerValueModelElement('id'),
FixedDataModelElement('item_string', b'): item='), DecimalIntegerValueModelElement('item'),
FixedDataModelElement('name_string', b' name="'), DelimitedDataModelElement('name', b'"'),
FixedDataModelElement('inode_string', b'" inode='), DecimalIntegerValueModelElement('inode'),
FixedDataModelElement('dev_string', b' dev='), DelimitedDataModelElement('dev', b' '),
FixedDataModelElement('mode_string', b' mode='),
DecimalIntegerValueModelElement('mode', value_pad_type=DecimalIntegerValueModelElement.PAD_TYPE_ZERO),
FixedDataModelElement('ouid_string', b' ouid='), DecimalIntegerValueModelElement('ouid'),
FixedDataModelElement('ogid_string', b' ogid='), DecimalIntegerValueModelElement('ogid'),
FixedDataModelElement('rdev_string', b' rdev='), DelimitedDataModelElement('rdev', b' '),
FixedDataModelElement('nametype_string', b' nametype='), FixedWordlistDataModelElement('nametype', [b'NORMAL', b'ERROR'])]),
SequenceModelElement('syscall', [
FixedDataModelElement('type', b'type=SYSCALL '), FixedDataModelElement('msg_audit', b'msg=audit('),
DelimitedDataModelElement('msg', b':'), FixedDataModelElement('placeholder', b':'), DecimalIntegerValueModelElement('id'),
FixedDataModelElement('arch_string', b'): arch='), DelimitedDataModelElement('arch', b' '),
FixedDataModelElement('syscall_string', b' syscall='), DecimalIntegerValueModelElement('syscall'),
FixedDataModelElement('success_string', b' success='), FixedWordlistDataModelElement('success', [b'yes', b'no']),
FixedDataModelElement('exit_string', b' exit='), DecimalIntegerValueModelElement('exit'),
AnyByteDataModelElement('remainding_data')])]
service_children_parsing_model_element = [
DateTimeModelElement('DateTimeModelElement', b'Current DateTime: %d.%m.%Y %H:%M:%S'),
DecimalFloatValueModelElement('DecimalFloatValueModelElement', value_sign_type='optional'),
DecimalIntegerValueModelElement('DecimalIntegerValueModelElement', value_sign_type='optional', value_pad_type='blank'),
SequenceModelElement('se', [
DelimitedDataModelElement('DelimitedDataModelElement', b';'), FixedDataModelElement('FixedDataModelElement', b';')])]
# ElementValueBranchModelElement
fixed_data_me1 = FixedDataModelElement("fixed1", b'match ')
fixed_data_me2 = FixedDataModelElement("fixed2", b'fixed String')
fixed_wordlist_data_model_element = FixedWordlistDataModelElement("wordlist", [b'data: ', b'string: '])
decimal_integer_value_model_element = DecimalIntegerValueModelElement("decimal")
service_children_parsing_model_element.append(
ElementValueBranchModelElement('ElementValueBranchModelElement', FirstMatchModelElement("first", [
SequenceModelElement("seq1", [fixed_data_me1, fixed_wordlist_data_model_element]),
SequenceModelElement("seq2", [fixed_data_me1, fixed_wordlist_data_model_element, fixed_data_me2])]), "wordlist",
{0: decimal_integer_value_model_element, 1: fixed_data_me2}))
service_children_parsing_model_element.append(HexStringModelElement('HexStringModelElement'))
service_children_parsing_model_element.append(SequenceModelElement('se2', [
FixedDataModelElement('FixedDataModelElement', b'Gateway IP-Address: '), IpAddressDataModelElement('IpAddressDataModelElement')]))
import locale
loc = locale.getlocale()
if loc == (None, None):
loc = ('en_US', 'utf8')
service_children_parsing_model_element.append(
MultiLocaleDateTimeModelElement('MultiLocaleDateTimeModelElement', [(b'%b %d %Y', None, '%s.%s' % loc)]))
service_children_parsing_model_element.append(
RepeatedElementDataModelElement('RepeatedElementDataModelElement', SequenceModelElement('SequenceModelElement', [
FixedDataModelElement('FixedDataModelElement', b'[drawn number]: '),
DecimalIntegerValueModelElement('DecimalIntegerValueModelElement')]), 1))
service_children_parsing_model_element.append(VariableByteDataModelElement('VariableByteDataModelElement', b'-@#'))
service_children_parsing_model_element.append(SequenceModelElement('se', [
WhiteSpaceLimitedDataModelElement('WhiteSpaceLimitedDataModelElement'), FixedDataModelElement('fixed', b' ')]))
# The Base64StringModelElement must be just before the AnyByteDataModelElement to avoid unexpected Matches.
service_children_parsing_model_element.append(Base64StringModelElement('Base64StringModelElement'))
# The OptionalMatchModelElement must be paired with a FirstMatchModelElement because it accepts all data and thus no data gets
# to the AnyByteDataModelElement. The AnyByteDataModelElement must be last, because all bytes are accepted.
service_children_parsing_model_element.append(
OptionalMatchModelElement('/', FirstMatchModelElement('FirstMatchModelElement//optional', [
FixedDataModelElement('FixedDataModelElement', b'The-searched-element-was-found!'), SequenceModelElement('se', [
FixedDataModelElement('FixedDME', b'Any:'), AnyByteDataModelElement('AnyByteDataModelElement')])])))
alphabet = b'ghijkl'
service_children_ecd = []
for _, char in enumerate(alphabet):
char = bytes([char])
service_children_ecd.append(FixedDataModelElement(char.decode(), char))
parsing_model = FirstMatchModelElement('model', [
SequenceModelElement('CronAnnouncement', service_children_cron_job_announcement),
SequenceModelElement('CronExecution', service_children_cron_job_execution),
SequenceModelElement('DailyCron', service_children_cron_job), SequenceModelElement('DiskReport', service_children_disk_report),
SequenceModelElement('LoginDetails', service_children_login_details), DecimalIntegerValueModelElement('Random'),
SequenceModelElement('RandomTime', service_children_random_time), SequenceModelElement('Sensors', service_children_sensors),
SequenceModelElement('IPAddresses', service_children_user_ip_address), FirstMatchModelElement('type', service_children_audit),
FirstMatchModelElement('ECD', service_children_ecd), FirstMatchModelElement('ParsingME', service_children_parsing_model_element)])
# Some generic imports.
from aminer.analysis import AtomFilters
# Create all global handler lists here and append the real handlers later on.
# Use this filter to distribute all atoms to the analysis handlers.
atom_filter = AtomFilters.SubhandlerFilter(None)
from aminer.analysis.TimestampCorrectionFilters import SimpleMonotonicTimestampAdjust
simple_monotonic_timestamp_adjust = SimpleMonotonicTimestampAdjust([atom_filter])
analysis_context.register_component(simple_monotonic_timestamp_adjust, component_name="SimpleMonotonicTimestampAdjust")
from aminer.events.StreamPrinterEventHandler import StreamPrinterEventHandler
from aminer.events.JsonConverterHandler import JsonConverterHandler
stream_printer_event_handler = StreamPrinterEventHandler(analysis_context)
json_converter_handler = JsonConverterHandler([stream_printer_event_handler], analysis_context)
anomaly_event_handlers = [json_converter_handler]
# Now define the AtomizerFactory using the model. A simple line based one is usually sufficient.
from aminer.input.SimpleByteStreamLineAtomizerFactory import SimpleByteStreamLineAtomizerFactory
analysis_context.atomizer_factory = SimpleByteStreamLineAtomizerFactory(parsing_model, [simple_monotonic_timestamp_adjust],
anomaly_event_handlers)
# Just report all unparsed atoms to the event handlers.
from aminer.analysis.UnparsedAtomHandlers import SimpleUnparsedAtomHandler, VerboseUnparsedAtomHandler
simple_unparsed_atom_handler = SimpleUnparsedAtomHandler(anomaly_event_handlers)
atom_filter.add_handler(simple_unparsed_atom_handler, stop_when_handled_flag=False)
analysis_context.register_component(simple_unparsed_atom_handler, component_name="SimpleUnparsedHandler")
verbose_unparsed_atom_handler = VerboseUnparsedAtomHandler(anomaly_event_handlers, parsing_model)
atom_filter.add_handler(verbose_unparsed_atom_handler, stop_when_handled_flag=True)
analysis_context.register_component(verbose_unparsed_atom_handler, component_name="VerboseUnparsedHandler")
from aminer.analysis.TimestampsUnsortedDetector import TimestampsUnsortedDetector
timestamps_unsorted_detector = TimestampsUnsortedDetector(analysis_context.aminer_config, anomaly_event_handlers)
atom_filter.add_handler(timestamps_unsorted_detector)
analysis_context.register_component(timestamps_unsorted_detector, component_name="TimestampsUnsortedDetector")
from aminer.analysis import Rules
from aminer.analysis.AllowlistViolationDetector import AllowlistViolationDetector
allowlist_rules = [
Rules.OrMatchRule([
Rules.AndMatchRule([
Rules.PathExistsMatchRule('/model/LoginDetails/PastTime/Time/Minutes'),
Rules.NegationMatchRule(Rules.ValueMatchRule('/model/LoginDetails/Username', b'root')),
Rules.DebugMatchRule(debug_match_result=True)]),
Rules.AndMatchRule([
Rules.NegationMatchRule(Rules.PathExistsMatchRule('/model/LoginDetails/PastTime/Time/Minutes')),
Rules.PathExistsMatchRule('/model/LoginDetails'),
Rules.DebugMatchRule(debug_match_result=True)]),
Rules.NegationMatchRule(Rules.PathExistsMatchRule('/model/LoginDetails'))])]
# This rule list should trigger, when the line does not look like: User root (logged in, logged out)
# or User 'username' (logged in, logged out) x minutes ago.
allowlist_violation_detector = AllowlistViolationDetector(analysis_context.aminer_config, allowlist_rules, anomaly_event_handlers,
output_log_line=True)
analysis_context.register_component(allowlist_violation_detector, component_name="Allowlist")
atom_filter.add_handler(allowlist_violation_detector)
from aminer.analysis.ParserCount import ParserCount
parser_count = ParserCount(analysis_context.aminer_config, None, anomaly_event_handlers, 10)
analysis_context.register_component(parser_count, component_name="ParserCount")
atom_filter.add_handler(parser_count)
from aminer.analysis.EventTypeDetector import EventTypeDetector
etd = EventTypeDetector(analysis_context.aminer_config, anomaly_event_handlers)
analysis_context.register_component(etd, component_name="EventTypeDetector")
atom_filter.add_handler(etd)
from aminer.analysis.VariableTypeDetector import VariableTypeDetector
vtd = VariableTypeDetector(analysis_context.aminer_config, anomaly_event_handlers, etd, silence_output_except_indicator=False,
output_log_line=False, ignore_list=["/model/RandomTime"])
analysis_context.register_component(vtd, component_name="VariableTypeDetector")
atom_filter.add_handler(vtd)
from aminer.analysis.VariableCorrelationDetector import VariableCorrelationDetector
vtd = VariableCorrelationDetector(analysis_context.aminer_config, anomaly_event_handlers, etd, disc_div_thres=0.5,
ignore_list=["/model/RandomTime"])
analysis_context.register_component(vtd, component_name="VariableCorrelationDetector")
atom_filter.add_handler(vtd)
from aminer.analysis.EventCorrelationDetector import EventCorrelationDetector
ecd = EventCorrelationDetector(analysis_context.aminer_config, anomaly_event_handlers, check_rules_flag=True,
hypothesis_max_delta_time=1.0)
analysis_context.register_component(ecd, component_name="EventCorrelationDetector")
atom_filter.add_handler(ecd)
from aminer.analysis.EventFrequencyDetector import EventFrequencyDetector
efd = EventFrequencyDetector(analysis_context.aminer_config, anomaly_event_handlers, window_size=0.1)
analysis_context.register_component(efd, component_name="EventFrequencyDetector")
atom_filter.add_handler(efd)
from aminer.analysis.EventSequenceDetector import EventSequenceDetector
esd = EventSequenceDetector(analysis_context.aminer_config, anomaly_event_handlers, ['/model/ParsingME'], ignore_list=[
'/model/ECD/g', '/model/ECD/h', '/model/ECD/i', '/model/ECD/j', '/model/ECD/k', '/model/ECD/l', '/model/Random',
'/model/RandomTime', '/model/DailyCron'])
analysis_context.register_component(esd, component_name="EventSequenceDetector")
atom_filter.add_handler(esd)
from aminer.analysis.MatchFilter import MatchFilter
match_filter = MatchFilter(analysis_context.aminer_config, ['/model/Random'], anomaly_event_handlers, target_value_list=[
1, 10, 100], output_log_line=True)
analysis_context.register_component(match_filter, component_name="MatchFilter")
atom_filter.add_handler(match_filter)
from aminer.analysis.NewMatchPathDetector import NewMatchPathDetector
new_match_path_detector = NewMatchPathDetector(analysis_context.aminer_config, anomaly_event_handlers, auto_include_flag=True,
output_log_line=True)
analysis_context.register_component(new_match_path_detector, component_name="NewMatchPath")
atom_filter.add_handler(new_match_path_detector)
def tuple_transformation_function(match_value_list):
"""Only allow output of the EnhancedNewMatchPathValueComboDetector after every 10th element."""
extra_data = enhanced_new_match_path_value_combo_detector.known_values_dict.get(tuple(match_value_list))
if extra_data is not None:
mod = 10
if (extra_data[2] + 1) % mod == 0:
enhanced_new_match_path_value_combo_detector.auto_include_flag = False
else:
enhanced_new_match_path_value_combo_detector.auto_include_flag = True
return match_value_list
from aminer.analysis.EnhancedNewMatchPathValueComboDetector import EnhancedNewMatchPathValueComboDetector
enhanced_new_match_path_value_combo_detector = EnhancedNewMatchPathValueComboDetector(analysis_context.aminer_config, [
'/model/DailyCron/UName', '/model/DailyCron/JobNumber'], anomaly_event_handlers, auto_include_flag=True,
tuple_transformation_function=tuple_transformation_function, output_log_line=True)
analysis_context.register_component(enhanced_new_match_path_value_combo_detector, component_name="EnhancedNewValueCombo")
atom_filter.add_handler(enhanced_new_match_path_value_combo_detector)
import re
ip_match_action = Rules.EventGenerationMatchAction(
"Analysis.Rules.IPv4InRFC1918MatchRule", "Private IP address occurred!", anomaly_event_handlers)
vdmt = Rules.ValueDependentModuloTimeMatchRule(None, 3, ["/model/ECD/j", "/model/ECD/k", "/model/ECD/l"], {b"e": [0, 2.95]}, [0, 3])
mt = Rules.ModuloTimeMatchRule(None, 3, 0, 3, None)
time_allowlist_rules = [
Rules.AndMatchRule([
Rules.ParallelMatchRule([
Rules.ValueDependentDelegatedMatchRule([
'/model/ECD/g', '/model/ECD/h', '/model/ECD/i', '/model/ECD/j', '/model/ECD/k', '/model/ECD/l'], {
(b"a",): mt, (b"b",): mt, (b"c",): mt, (b"d",): vdmt, (b"e",): vdmt, (b"f",): vdmt, None: mt}, mt),
Rules.IPv4InRFC1918MatchRule("/model/ParsingME/se2/IpAddressDataModelElement", ip_match_action),
Rules.DebugHistoryMatchRule(debug_match_result=True)
]),
# IP addresses 8.8.8.8, 8.8.4.4 and 10.0.0.0 - 10.255.255.255 are not allowed
Rules.NegationMatchRule(Rules.ValueListMatchRule("/model/ParsingME/se2/IpAddressDataModelElement", [134744072, 134743044])),
Rules.NegationMatchRule(Rules.ValueRangeMatchRule("/model/ParsingME/se2/IpAddressDataModelElement", 167772160, 184549375)),
Rules.NegationMatchRule(Rules.StringRegexMatchRule("/model/type/syscall/success", re.compile(b"^no$")))
])
]
time_allowlist_violation_detector = AllowlistViolationDetector(
analysis_context.aminer_config, time_allowlist_rules, anomaly_event_handlers, output_log_line=True)
analysis_context.register_component(time_allowlist_violation_detector, component_name="TimeAllowlist")
atom_filter.add_handler(time_allowlist_violation_detector)
from aminer.analysis.HistogramAnalysis import HistogramAnalysis, LinearNumericBinDefinition, ModuloTimeBinDefinition, \
PathDependentHistogramAnalysis
modulo_time_bin_definition = ModuloTimeBinDefinition(86400, 3600, 0, 1, 24, True)
linear_numeric_bin_definition = LinearNumericBinDefinition(50, 5, 20, True)
histogram_analysis = HistogramAnalysis(analysis_context.aminer_config, [
('/model/RandomTime/Random', modulo_time_bin_definition), ('/model/Random', linear_numeric_bin_definition)], 10,
anomaly_event_handlers, output_log_line=True)
analysis_context.register_component(histogram_analysis, component_name="HistogramAnalysis")
atom_filter.add_handler(histogram_analysis)
path_dependent_histogram_analysis = PathDependentHistogramAnalysis(
analysis_context.aminer_config, '/model/RandomTime', modulo_time_bin_definition, 10, anomaly_event_handlers, output_log_line=True)
analysis_context.register_component(path_dependent_histogram_analysis, component_name="PathDependentHistogramAnalysis")
atom_filter.add_handler(path_dependent_histogram_analysis)
from aminer.analysis.MatchValueAverageChangeDetector import MatchValueAverageChangeDetector
match_value_average_change_detector = MatchValueAverageChangeDetector(analysis_context.aminer_config, anomaly_event_handlers, None, [
'/model/Random'], 100, 10, output_log_line=True)
analysis_context.register_component(match_value_average_change_detector, component_name="MatchValueAverageChange")
atom_filter.add_handler(match_value_average_change_detector)
import sys
from aminer.analysis.MatchValueStreamWriter import MatchValueStreamWriter
match_value_stream_writer = MatchValueStreamWriter(
sys.stdout, ['/model/Sensors/CPUTemp', '/model/Sensors/CPUWorkload', '/model/Sensors/DTM'], b';', b'')
analysis_context.register_component(match_value_stream_writer, component_name="MatchValueStreamWriter")
atom_filter.add_handler(match_value_stream_writer)
from aminer.analysis.NewMatchPathValueComboDetector import NewMatchPathValueComboDetector
new_match_path_value_combo_detector = NewMatchPathValueComboDetector(
analysis_context.aminer_config, ['/model/IPAddresses/Username', '/model/IPAddresses/IP'],
anomaly_event_handlers, output_log_line=True)
analysis_context.register_component(new_match_path_value_combo_detector, component_name="NewMatchPathValueCombo")
atom_filter.add_handler(new_match_path_value_combo_detector)
from aminer.analysis.NewMatchIdValueComboDetector import NewMatchIdValueComboDetector
new_match_id_value_combo_detector = NewMatchIdValueComboDetector(analysis_context.aminer_config, [
'/model/type/path/name', '/model/type/syscall/syscall'], anomaly_event_handlers, id_path_list=[
'/model/type/path/id', '/model/type/syscall/id'], min_allowed_time_diff=5, auto_include_flag=True, allow_missing_values_flag=True,
output_log_line=True)
analysis_context.register_component(new_match_id_value_combo_detector, component_name="NewMatchIdValueComboDetector")
atom_filter.add_handler(new_match_id_value_combo_detector)
from aminer.analysis.NewMatchPathValueDetector import NewMatchPathValueDetector
new_match_path_value_detector = NewMatchPathValueDetector(analysis_context.aminer_config, [
'/model/DailyCron/JobNumber', '/model/IPAddresses/Username'], anomaly_event_handlers, auto_include_flag=True, output_log_line=True)
analysis_context.register_component(new_match_path_value_detector, component_name="NewMatchPathValue")
atom_filter.add_handler(new_match_path_value_detector)
from aminer.analysis.MissingMatchPathValueDetector import MissingMatchPathValueDetector
missing_match_path_value_detector = MissingMatchPathValueDetector(
analysis_context.aminer_config, ['/model/DiskReport/Space'], anomaly_event_handlers, auto_include_flag=True, default_interval=2,
realert_interval=5, output_log_line=True)
analysis_context.register_component(missing_match_path_value_detector, component_name="MissingMatch")
atom_filter.add_handler(missing_match_path_value_detector)
from aminer.analysis.TimeCorrelationDetector import TimeCorrelationDetector
time_correlation_detector = TimeCorrelationDetector(
analysis_context.aminer_config, anomaly_event_handlers, 2, min_rule_attributes=1, max_rule_attributes=5,
record_count_before_event=10000, output_log_line=True)
analysis_context.register_component(time_correlation_detector, component_name="TimeCorrelationDetector")
atom_filter.add_handler(time_correlation_detector)
from aminer.analysis.TimeCorrelationViolationDetector import TimeCorrelationViolationDetector, CorrelationRule, EventClassSelector
cron_job_announcement = CorrelationRule('CronJobAnnouncement', 5, 6, max_artefacts_a_for_single_b=1, artefact_match_parameters=[
('/model/CronAnnouncement/JobNumber', '/model/CronExecution/JobNumber')])
a_class_selector = EventClassSelector('Announcement', [cron_job_announcement], None)
b_class_selector = EventClassSelector('Execution', None, [cron_job_announcement])
rules = [Rules.PathExistsMatchRule('/model/CronAnnouncement/Run', a_class_selector),
Rules.PathExistsMatchRule('/model/CronExecution/Job', b_class_selector)]
time_correlation_violation_detector = TimeCorrelationViolationDetector(analysis_context.aminer_config, rules, anomaly_event_handlers,
output_log_line=True)
analysis_context.register_component(time_correlation_violation_detector, component_name="TimeCorrelationViolationDetector")
atom_filter.add_handler(time_correlation_violation_detector)
def build_analysis_pipeline(analysis_context):
"""
Define the function to create pipeline for parsing the log data.
It has also to define an AtomizerFactory to instruct aminer how to process incoming data streams to create log atoms from them.
"""
date_format_string = b'%Y-%m-%d %H:%M:%S'
cron = b' cron['
# Build the parsing model:
service_children_disk_report = [
FixedDataModelElement(
'Space',
b' Current Disk Data is: Filesystem Type Size Used Avail Use%'
),
DelimitedDataModelElement('Data', b'%'),
AnyByteDataModelElement('Rest')
]
service_children_login_details = [
FixedDataModelElement('User', b'User '),
DelimitedDataModelElement('Username', b' '),
FixedWordlistDataModelElement('Status',
[b' logged in', b' logged out']),
OptionalMatchModelElement(
'PastTime',
SequenceModelElement('Time', [
FixedDataModelElement('Blank', b' '),
DecimalIntegerValueModelElement('Minutes'),
FixedDataModelElement('Ago', b' minutes ago.')
]))
]
service_children_cron_job = [
DateTimeModelElement('DTM', date_format_string),
FixedDataModelElement('UNameSpace1', b' '),
DelimitedDataModelElement('UName', b' '),
FixedDataModelElement('UNameSpace2', b' '),
DelimitedDataModelElement('User', b' '),
FixedDataModelElement('Cron', cron),
DecimalIntegerValueModelElement('JobNumber'),
FixedDataModelElement('Details', b']: Job `cron.daily` started.')
]
service_children_random_time = [
FixedDataModelElement('Space', b'Random: '),
DecimalIntegerValueModelElement('Random')
]
service_children_sensors = [
SequenceModelElement('CPUTemp', [
FixedDataModelElement('FixedTemp', b'CPU Temp: '),
DecimalIntegerValueModelElement('Temp'),
FixedDataModelElement('Degrees', b'\xc2\xb0C')
]),
FixedDataModelElement('Space1', b', '),
SequenceModelElement('CPUWorkload', [
FixedDataModelElement('Fixed Workload', b'CPU Workload: '),
DecimalIntegerValueModelElement('Workload'),
FixedDataModelElement('Percent', b'%')
]),
FixedDataModelElement('Space2', b', '),
DateTimeModelElement('DTM', date_format_string)
]
service_children_user_ip_address = [
FixedDataModelElement('User', b'User '),
DelimitedDataModelElement('Username', b' '),
FixedDataModelElement('Action', b' changed IP address to '),
IpAddressDataModelElement('IP')
]
service_children_cron_job_announcement = [
DateTimeModelElement('DTM', date_format_string),
FixedDataModelElement('Space', b' '),
DelimitedDataModelElement('UName', b' '),
FixedDataModelElement('Cron', cron),
DecimalIntegerValueModelElement('JobNumber'),
FixedDataModelElement('Run', b']: Will run job `'),
FixedWordlistDataModelElement(
'CronType',
[b'cron.daily', b'cron.hourly', b'cron.monthly', b'cron.weekly']),
FixedDataModelElement('Start Time', b'\' in 5 min.')
]
service_children_cron_job_execution = [
DateTimeModelElement('DTM', date_format_string),
FixedDataModelElement('Space1', b' '),
DelimitedDataModelElement('UName', b' '),
FixedDataModelElement('Cron', cron),
DecimalIntegerValueModelElement('JobNumber'),
FixedDataModelElement('Job', b']: Job `'),
FixedWordlistDataModelElement(
'CronType',
[b'cron.daily', b'cron.hourly', b'cron.monthly', b'cron.weekly']),
FixedDataModelElement('Started', b'\' started')
]
service_children_parsing_model_element = [
DateTimeModelElement('DateTimeModelElement',
b'Current DateTime: %d.%m.%Y %H:%M:%S'),
DecimalFloatValueModelElement('DecimalFloatValueModelElement',
value_sign_type='optional'),
DecimalIntegerValueModelElement('DecimalIntegerValueModelElement',
value_sign_type='optional',
value_pad_type='blank'),
SequenceModelElement('', [
DelimitedDataModelElement('DelimitedDataModelElement', b';'),
FixedDataModelElement('FixedDataModelElement', b';')
])
]
# ElementValueBranchModelElement
fixed_data_me1 = FixedDataModelElement("fixed1", b'match ')
fixed_data_me2 = FixedDataModelElement("fixed2", b'fixed String')
fixed_wordlist_data_model_element = FixedWordlistDataModelElement(
"wordlist", [b'data: ', b'string: '])
decimal_integer_value_model_element = DecimalIntegerValueModelElement(
"decimal")
service_children_parsing_model_element.append(
ElementValueBranchModelElement(
'ElementValueBranchModelElement',
FirstMatchModelElement("first", [
SequenceModelElement(
"seq1",
[fixed_data_me1, fixed_wordlist_data_model_element]),
SequenceModelElement("seq2", [
fixed_data_me1, fixed_wordlist_data_model_element,
fixed_data_me2
])
]), "wordlist", {
0: decimal_integer_value_model_element,
1: fixed_data_me2
}))
service_children_parsing_model_element.append(
HexStringModelElement('HexStringModelElement'))
service_children_parsing_model_element.append(
SequenceModelElement('', [
FixedDataModelElement('FixedDataModelElement',
b'Gateway IP-Address: '),
IpAddressDataModelElement('IpAddressDataModelElement')
]))
service_children_parsing_model_element.append(
MultiLocaleDateTimeModelElement('MultiLocaleDateTimeModelElement',
[(b'%b %d %Y', "de_AT.utf8", None)]))
service_children_parsing_model_element.append(
RepeatedElementDataModelElement(
'RepeatedElementDataModelElement',
SequenceModelElement('SequenceModelElement', [
FixedDataModelElement('FixedDataModelElement',
b'drawn number: '),
DecimalIntegerValueModelElement(
'DecimalIntegerValueModelElement')
]), 1))
service_children_parsing_model_element.append(
VariableByteDataModelElement('VariableByteDataModelElement', b'-@#'))
service_children_parsing_model_element.append(
SequenceModelElement('', [
WhiteSpaceLimitedDataModelElement(
'WhiteSpaceLimitedDataModelElement'),
FixedDataModelElement('', b' ')
]))
# The Base64StringModelElement must be just before the AnyByteDataModelElement to avoid unexpected Matches.
service_children_parsing_model_element.append(
Base64StringModelElement('Base64StringModelElement'))
# The OptionalMatchModelElement must be paired with a FirstMatchModelElement because it accepts all data and thus no data gets
# to the AnyByteDataModelElement. The AnyByteDataModelElement must be last, because all bytes are accepted.
service_children_parsing_model_element.append(
OptionalMatchModelElement(
'OptionalMatchModelElement',
FirstMatchModelElement('FirstMatchModelElement', [
FixedDataModelElement('FixedDataModelElement',
b'The-searched-element-was-found!'),
AnyByteDataModelElement('AnyByteDataModelElement')
])))
parsing_model = FirstMatchModelElement('model', [
SequenceModelElement('CronAnnouncement',
service_children_cron_job_announcement),
SequenceModelElement('CronExecution',
service_children_cron_job_execution),
SequenceModelElement('DailyCron', service_children_cron_job),
SequenceModelElement('DiskReport', service_children_disk_report),
SequenceModelElement('LoginDetails', service_children_login_details),
DecimalIntegerValueModelElement('Random'),
SequenceModelElement('RandomTime', service_children_random_time),
SequenceModelElement('Sensors', service_children_sensors),
SequenceModelElement('IPAddresses', service_children_user_ip_address),
FirstMatchModelElement('ParsingME',
service_children_parsing_model_element)
])
# Some generic imports.
from aminer.analysis import AtomFilters
# Create all global handler lists here and append the real handlers
# later on.
# Use this filter to distribute all atoms to the analysis handlers.
atom_filter = AtomFilters.SubhandlerFilter(None)
from aminer.analysis.TimestampCorrectionFilters import SimpleMonotonicTimestampAdjust
simple_monotonic_timestamp_adjust = SimpleMonotonicTimestampAdjust(
[atom_filter])
analysis_context.register_component(
simple_monotonic_timestamp_adjust,
component_name="SimpleMonotonicTimestampAdjust")
from aminer.events.StreamPrinterEventHandler import StreamPrinterEventHandler
stream_printer_event_handler = StreamPrinterEventHandler(analysis_context)
from aminer.events.SyslogWriterEventHandler import SyslogWriterEventHandler
syslog_event_handler = SyslogWriterEventHandler(analysis_context)
from aminer.events.DefaultMailNotificationEventHandler import DefaultMailNotificationEventHandler
if DefaultMailNotificationEventHandler.CONFIG_KEY_MAIL_TARGET_ADDRESS in analysis_context.aminer_config.config_properties:
mail_notification_handler = DefaultMailNotificationEventHandler(
analysis_context)
analysis_context.register_component(mail_notification_handler,
component_name="MailHandler")
anomaly_event_handlers = [
stream_printer_event_handler, syslog_event_handler,
mail_notification_handler
]
# Now define the AtomizerFactory using the model. A simple line based one is usually sufficient.
from aminer.input.SimpleByteStreamLineAtomizerFactory import SimpleByteStreamLineAtomizerFactory
analysis_context.atomizer_factory = SimpleByteStreamLineAtomizerFactory(
parsing_model, [simple_monotonic_timestamp_adjust],
anomaly_event_handlers)
# Just report all unparsed atoms to the event handlers.
from aminer.analysis.UnparsedAtomHandlers import SimpleUnparsedAtomHandler
simple_unparsed_atom_handler = SimpleUnparsedAtomHandler(
anomaly_event_handlers)
atom_filter.add_handler(simple_unparsed_atom_handler,
stop_when_handled_flag=True)
analysis_context.register_component(simple_unparsed_atom_handler,
component_name="UnparsedHandler")
from aminer.analysis.TimestampsUnsortedDetector import TimestampsUnsortedDetector
timestamps_unsorted_detector = TimestampsUnsortedDetector(
analysis_context.aminer_config, anomaly_event_handlers)
atom_filter.add_handler(timestamps_unsorted_detector)
analysis_context.register_component(
timestamps_unsorted_detector,
component_name="TimestampsUnsortedDetector")
from aminer.analysis import Rules
from aminer.analysis.AllowlistViolationDetector import AllowlistViolationDetector
allowlist_rules = [
Rules.OrMatchRule([
Rules.AndMatchRule([
Rules.PathExistsMatchRule(
'/model/LoginDetails/PastTime/Time/Minutes'),
Rules.NegationMatchRule(
Rules.ValueMatchRule('/model/LoginDetails/Username',
b'root'))
]),
Rules.AndMatchRule([
Rules.NegationMatchRule(
Rules.PathExistsMatchRule(
'/model/LoginDetails/PastTime/Time/Minutes')),
Rules.PathExistsMatchRule('/model/LoginDetails')
]),
Rules.NegationMatchRule(
Rules.PathExistsMatchRule('/model/LoginDetails'))
])
]
# This rule list should trigger, when the line does not look like: User root (logged in, logged out)
# or User 'username' (logged in, logged out) x minutes ago.
allowlist_violation_detector = AllowlistViolationDetector(
analysis_context.aminer_config, allowlist_rules,
anomaly_event_handlers)
analysis_context.register_component(allowlist_violation_detector,
component_name="Allowlist")
atom_filter.add_handler(allowlist_violation_detector)
from aminer.analysis.NewMatchPathDetector import NewMatchPathDetector
new_match_path_detector = NewMatchPathDetector(
analysis_context.aminer_config,
anomaly_event_handlers,
auto_include_flag=True)
analysis_context.register_component(new_match_path_detector,
component_name="NewMatchPath")
atom_filter.add_handler(new_match_path_detector)
def tuple_transformation_function(match_value_list):
"""Only allow output of the EnhancedNewMatchPathValueComboDetector after every 10000th element."""
extra_data = enhanced_new_match_path_value_combo_detector.known_values_dict.get(
tuple(match_value_list))
if extra_data is not None:
mod = 10000
if (extra_data[2] + 1) % mod == 0:
enhanced_new_match_path_value_combo_detector.auto_include_flag = False
else:
enhanced_new_match_path_value_combo_detector.auto_include_flag = True
return match_value_list
from aminer.analysis.EnhancedNewMatchPathValueComboDetector import EnhancedNewMatchPathValueComboDetector
enhanced_new_match_path_value_combo_detector = EnhancedNewMatchPathValueComboDetector(
analysis_context.aminer_config,
['/model/DailyCron/UName', '/model/DailyCron/JobNumber'],
anomaly_event_handlers,
auto_include_flag=True,
tuple_transformation_function=tuple_transformation_function)
analysis_context.register_component(
enhanced_new_match_path_value_combo_detector,
component_name="EnhancedNewValueCombo")
atom_filter.add_handler(enhanced_new_match_path_value_combo_detector)
from aminer.analysis.HistogramAnalysis import HistogramAnalysis, LinearNumericBinDefinition, ModuloTimeBinDefinition, \
PathDependentHistogramAnalysis
modulo_time_bin_definition = ModuloTimeBinDefinition(
86400, 3600, 0, 1, 24, True)
linear_numeric_bin_definition = LinearNumericBinDefinition(50, 5, 20, True)
histogram_analysis = HistogramAnalysis(
analysis_context.aminer_config,
[('/model/RandomTime/Random', modulo_time_bin_definition),
('/model/Random', linear_numeric_bin_definition)], 10,
anomaly_event_handlers)
analysis_context.register_component(histogram_analysis,
component_name="HistogramAnalysis")
atom_filter.add_handler(histogram_analysis)
path_dependent_histogram_analysis = PathDependentHistogramAnalysis(
analysis_context.aminer_config, '/model/RandomTime',
modulo_time_bin_definition, 10, anomaly_event_handlers)
analysis_context.register_component(
path_dependent_histogram_analysis,
component_name="PathDependentHistogramAnalysis")
atom_filter.add_handler(path_dependent_histogram_analysis)
from aminer.analysis.MatchValueAverageChangeDetector import MatchValueAverageChangeDetector
match_value_average_change_detector = MatchValueAverageChangeDetector(
analysis_context.aminer_config, anomaly_event_handlers, None,
['/model/Random'], 100, 10)
analysis_context.register_component(
match_value_average_change_detector,
component_name="MatchValueAverageChange")
atom_filter.add_handler(match_value_average_change_detector)
import sys
from aminer.analysis.MatchValueStreamWriter import MatchValueStreamWriter
match_value_stream_writer = MatchValueStreamWriter(sys.stdout, [
'/model/Sensors/CPUTemp', '/model/Sensors/CPUWorkload',
'/model/Sensors/DTM'
], b';', b'')
analysis_context.register_component(
match_value_stream_writer, component_name="MatchValueStreamWriter")
atom_filter.add_handler(match_value_stream_writer)
from aminer.analysis.NewMatchPathValueComboDetector import NewMatchPathValueComboDetector
new_match_path_value_combo_detector = NewMatchPathValueComboDetector(
analysis_context.aminer_config,
['/model/IPAddresses/Username', '/model/IPAddresses/IP'],
anomaly_event_handlers,
auto_include_flag=True)
analysis_context.register_component(
new_match_path_value_combo_detector,
component_name="NewMatchPathValueCombo")
atom_filter.add_handler(new_match_path_value_combo_detector)
from aminer.analysis.NewMatchPathValueDetector import NewMatchPathValueDetector
new_match_path_value_detector = NewMatchPathValueDetector(
analysis_context.aminer_config,
['/model/DailyCron/JobNumber', '/model/IPAddresses/Username'],
anomaly_event_handlers,
auto_include_flag=True)
analysis_context.register_component(new_match_path_value_detector,
component_name="NewMatchPathValue")
atom_filter.add_handler(new_match_path_value_detector)
from aminer.analysis.MissingMatchPathValueDetector import MissingMatchPathValueDetector
missing_match_path_value_detector = MissingMatchPathValueDetector(
analysis_context.aminer_config, ['/model/DiskReport/Space'],
anomaly_event_handlers,
auto_include_flag=True,
default_interval=2,
realert_interval=5)
analysis_context.register_component(missing_match_path_value_detector,
component_name="MissingMatch")
atom_filter.add_handler(missing_match_path_value_detector)
from aminer.analysis.TimeCorrelationDetector import TimeCorrelationDetector
time_correlation_detector = TimeCorrelationDetector(
analysis_context.aminer_config,
anomaly_event_handlers,
2,
min_rule_attributes=1,
max_rule_attributes=5,
record_count_before_event=70000,
output_log_line=True)
analysis_context.register_component(
time_correlation_detector, component_name="TimeCorrelationDetector")
atom_filter.add_handler(time_correlation_detector)
from aminer.analysis.TimeCorrelationViolationDetector import TimeCorrelationViolationDetector, CorrelationRule, EventClassSelector
cron_job_announcement = CorrelationRule(
'CronJobAnnouncement',
5,
6,
max_artefacts_a_for_single_b=1,
artefact_match_parameters=[('/model/CronAnnouncement/JobNumber',
'/model/CronExecution/JobNumber')])
a_class_selector = EventClassSelector('Announcement',
[cron_job_announcement], None)
b_class_selector = EventClassSelector('Execution', None,
[cron_job_announcement])
rules = [
Rules.PathExistsMatchRule('/model/CronAnnouncement/Run',
a_class_selector),
Rules.PathExistsMatchRule('/model/CronExecution/Job', b_class_selector)
]
time_correlation_violation_detector = TimeCorrelationViolationDetector(
analysis_context.aminer_config, rules, anomaly_event_handlers)
analysis_context.register_component(
time_correlation_violation_detector,
component_name="TimeCorrelationViolationDetector")
atom_filter.add_handler(time_correlation_violation_detector)
def run_time_correlation_violation_detector(self, chance):
results = [None] * self.iterations
avg = 0
z = 0
while z < self.iterations:
correlation_rule = CorrelationRule('Correlation',
0,
chance,
max_artefacts_a_for_single_b=1,
artefact_match_parameters=[
('/integer/d0',
'/integer/d1')
])
a_class_selector = EventClassSelector('Selector1',
[correlation_rule], None)
b_class_selector = EventClassSelector('Selector2', None,
[correlation_rule])
rules = [
Rules.PathExistsMatchRule('/integer/d0', a_class_selector),
Rules.PathExistsMatchRule('/integer/d1', b_class_selector)
]
time_correlation_violation_detector = TimeCorrelationViolationDetector(
self.analysis_context.aminer_config, rules,
[self.stream_printer_event_handler])
seconds = time.time()
s = seconds
i = 0
decimal_integer_value_me = DecimalIntegerValueModelElement(
'd0', DecimalIntegerValueModelElement.SIGN_TYPE_NONE,
DecimalIntegerValueModelElement.PAD_TYPE_NONE)
while int(time.time() - seconds) < self.waiting_time:
integer = '/integer'
p = process_time()
r = random.randint(1, 100)
seconds = seconds + process_time() - p
decimal_integer_value_me1 = DecimalIntegerValueModelElement(
'd1', DecimalIntegerValueModelElement.SIGN_TYPE_NONE,
DecimalIntegerValueModelElement.PAD_TYPE_NONE)
match_context = MatchContext(str(i).encode())
match_element = decimal_integer_value_me.get_match_element(
integer, match_context)
log_atom = LogAtom(match_element.match_string,
ParserMatch(match_element), s,
time_correlation_violation_detector)
time_correlation_violation_detector.receive_atom(log_atom)
match_context = MatchContext(str(i).encode())
match_element = decimal_integer_value_me1.get_match_element(
integer, match_context)
log_atom = LogAtom(match_element.match_string,
ParserMatch(match_element), s + r / 100,
time_correlation_violation_detector)
time_correlation_violation_detector.receive_atom(log_atom)
s = s + r / 100
if r / 100 >= chance:
p = process_time()
match_context = MatchContext(str(i).encode())
match_element = decimal_integer_value_me.get_match_element(
integer, match_context)
log_atom = LogAtom(match_element.match_string,
ParserMatch(match_element), s,
time_correlation_violation_detector)
time_correlation_violation_detector.receive_atom(log_atom)
seconds = seconds + process_time() - p
time_correlation_violation_detector.do_timer(s)
i = i + 1
results[z] = i
z = z + 1
avg = avg + i
avg = avg / self.iterations
type(self).result = self.result + self.result_string % (
time_correlation_violation_detector.__class__.__name__, avg,
results, '%d%% chance of not finding an element' %
((1 - chance) * 100))
def buildAnalysisPipeline(analysisContext):
"""Define the function to create pipeline for parsing the log
data. It has also to define an AtomizerFactory to instruct AMiner
how to process incoming data streams to create log atoms from
them."""
# Build the parsing model first:
from aminer.parsing import FirstMatchModelElement
from aminer.parsing import SequenceModelElement
serviceChildren = []
import CronParsingModel
serviceChildren.append(CronParsingModel.getModel())
import EximParsingModel
serviceChildren.append(EximParsingModel.getModel())
import RsyslogParsingModel
serviceChildren.append(RsyslogParsingModel.getModel())
import SyslogPreambleModel
syslogPreambleModel = SyslogPreambleModel.getModel()
parsingModel = SequenceModelElement('model', [
syslogPreambleModel,
FirstMatchModelElement('services', serviceChildren)
])
# Some generic imports.
from aminer.analysis import AtomFilters
from aminer.analysis import Rules
# Create all global handler lists here and append the real handlers
# later on.
# Use this filter to distribute all atoms to the analysis handlers.
atomFilter = AtomFilters.SubhandlerFilter(None)
anomalyEventHandlers = []
# Now define the AtomizerFactory using the model. A simple line
# based one is usually sufficient.
from aminer.input import SimpleByteStreamLineAtomizerFactory
analysisContext.atomizerFactory = SimpleByteStreamLineAtomizerFactory(
parsingModel, [atomFilter],
anomalyEventHandlers,
defaultTimestampPath='/model/syslog/time')
# Always report the unparsed lines: a part of the parsing model
# seems to be missing or wrong.
from aminer.input import SimpleUnparsedAtomHandler
atomFilter.addHandler(SimpleUnparsedAtomHandler(anomalyEventHandlers),
stopWhenHandledFlag=True)
# Report new parsing model path values. Those occurr when a line
# with new structural properties was parsed.
from aminer.analysis import NewMatchPathDetector
newMatchPathDetector = NewMatchPathDetector(analysisContext.aminerConfig,
anomalyEventHandlers,
autoIncludeFlag=True)
analysisContext.registerComponent(newMatchPathDetector,
componentName='DefaultMatchPathDetector')
atomFilter.addHandler(newMatchPathDetector)
# Run a whitelisting over the parsed lines.
from aminer.analysis import WhitelistViolationDetector
violationAction = Rules.EventGenerationMatchAction(
'Analysis.GenericViolation', 'Violation detected',
anomalyEventHandlers)
whitelistRules = []
# Filter out things so bad, that we do not want to accept the
# risk, that a too broad whitelisting rule will accept the data
# later on.
whitelistRules.append(
Rules.ValueMatchRule('/model/services/cron/msgtype/exec/user',
'hacker', violationAction))
# Ignore Exim queue run start/stop messages
whitelistRules.append(
Rules.PathExistsMatchRule('/model/services/exim/msg/queue/pid'))
# Ignore all ntpd messages for now.
whitelistRules.append(Rules.PathExistsMatchRule('/model/services/ntpd'))
# Add a debugging rule in the middle to see everything not whitelisted
# up to this point.
whitelistRules.append(Rules.DebugMatchRule(False))
# Ignore hourly cronjobs, but only when started at expected time
# and duration is not too long.
whitelistRules.append(
Rules.AndMatchRule([
Rules.ValueMatchRule(
'/model/services/cron/msgtype/exec/command',
'( cd / && run-parts --report /etc/cron.hourly)'),
Rules.ModuloTimeMatchRule('/model/syslog/time', 3600, 17 * 60,
17 * 60 + 5)
]))
atomFilter.addHandler(
WhitelistViolationDetector(whitelistRules, anomalyEventHandlers))
# Include the e-mail notification handler only if the configuration
# parameter was set.
from aminer.events import DefaultMailNotificationEventHandler
if DefaultMailNotificationEventHandler.CONFIG_KEY_MAIL_TARGET_ADDRESS in analysisContext.aminerConfig.configProperties:
mailNotificationHandler = DefaultMailNotificationEventHandler(
analysisContext.aminerConfig)
analysisContext.registerComponent(mailNotificationHandler,
componentName=None)
anomalyEventHandlers.append(mailNotificationHandler)
# Add stdout stream printing for debugging, tuning.
from aminer.events import StreamPrinterEventHandler
anomalyEventHandlers.append(
StreamPrinterEventHandler(analysisContext.aminerConfig))