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:
from aminer.parsing import AnyByteDataModelElement
parsing_model = AnyByteDataModelElement('AnyByteDataModelElement')
# 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.events.StreamPrinterEventHandler import StreamPrinterEventHandler
stream_printer_event_handler = StreamPrinterEventHandler(analysis_context)
anomaly_event_handlers = [stream_printer_event_handler]
# Now define the AtomizerFactory using the model. A simple line
# based one is usually sufficient.
from aminer.input import SimpleByteStreamLineAtomizerFactory
analysis_context.atomizer_factory = SimpleByteStreamLineAtomizerFactory(
parsing_model, [atom_filter], anomaly_event_handlers)
# Just report all unparsed atoms to the event handlers.
from aminer.input 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 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)
from aminer.analysis.NewMatchPathValueDetector import NewMatchPathValueDetector
new_match_path_value_detector = NewMatchPathValueDetector(
analysis_context.aminer_config, ['/AnyByteDataModelElement'],
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)
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 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 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.input 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 import WhitelistViolationDetector
whitelist_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.
whitelist_violation_detector = WhitelistViolationDetector(
analysis_context.aminer_config, whitelist_rules,
anomaly_event_handlers)
analysis_context.register_component(whitelist_violation_detector,
component_name="Whitelist")
atom_filter.add_handler(whitelist_violation_detector)
from aminer.analysis 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):
extra_data = enhanced_new_match_path_value_combo_detector.known_values_dict.get(
tuple(match_value_list), None)
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,
2,
1,
0,
anomaly_event_handlers,
record_count_before_event=70000)
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 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:
from aminer.parsing import FirstMatchModelElement, SequenceModelElement, DecimalFloatValueModelElement, FixedDataModelElement, \
DelimitedDataModelElement, AnyByteDataModelElement, FixedWordlistDataModelElement, DecimalIntegerValueModelElement, \
DateTimeModelElement, IpAddressDataModelElement, Base64StringModelElement, ElementValueBranchModelElement, HexStringModelElement, \
MultiLocaleDateTimeModelElement, OptionalMatchModelElement, RepeatedElementDataModelElement, VariableByteDataModelElement, \
WhiteSpaceLimitedDataModelElement
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('FixedWorkload', 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('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'),
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('', [
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')
]))
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', '%s.%s' %
(loc), 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!'),
SequenceModelElement('', [
FixedDataModelElement('FixedDME', b'Any:'),
AnyByteDataModelElement('AnyByteDataModelElement')
])
])))
alphabet = b'abcdef'
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
stream_printer_event_handler = StreamPrinterEventHandler(analysis_context)
anomaly_event_handlers = [stream_printer_event_handler]
# Now define the AtomizerFactory using the model. A simple line
# based one is usually sufficient.
from aminer.input import SimpleByteStreamLineAtomizerFactory
analysis_context.atomizer_factory = SimpleByteStreamLineAtomizerFactory(
parsing_model, [simple_monotonic_timestamp_adjust],
anomaly_event_handlers,
default_timestamp_paths=["/model/DailyCron/DTM"])
# Just report all unparsed atoms to the event handlers.
from aminer.input 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 import AllowlistViolationDetector
# 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_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'))
])
]
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 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)
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)
analysis_context.register_component(
vtd, component_name="VariableCorrelationDetector")
atom_filter.add_handler(vtd)
from aminer.analysis 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_filter.add_handler(ecd)
from aminer.analysis 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 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)
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,
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.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."""
# Build the parsing model:
from aminer.parsing import FirstMatchModelElement
from aminer.parsing import SequenceModelElement
from aminer.parsing.DateTimeModelElement import DateTimeModelElement
import datetime
from aminer.parsing import FixedDataModelElement
from aminer.parsing.DelimitedDataModelElement import DelimitedDataModelElement
from aminer.parsing import AnyByteDataModelElement
service_children_disk_upgrade = [
DateTimeModelElement(
'DTM', b'%Y-%m-%d %H:%M:%S',
datetime.datetime.now(datetime.timezone.utc).astimezone().tzinfo),
FixedDataModelElement('UNameSpace1', b' '),
DelimitedDataModelElement('UName', b' '),
FixedDataModelElement('UNameSpace2', b' '),
DelimitedDataModelElement('User', b' '),
FixedDataModelElement('HDRepair',
b' System rebooted for hard disk upgrade')
]
service_children_home_path = [
FixedDataModelElement(
'Pwd',
b'The Path of the home directory shown by pwd of the user '),
DelimitedDataModelElement('Username', b' '),
FixedDataModelElement('Is', b' is: '),
AnyByteDataModelElement('Path')
]
parsing_model = FirstMatchModelElement('model', [
SequenceModelElement('DiskUpgrade', service_children_disk_upgrade),
SequenceModelElement('HomePath', service_children_home_path)
])
# 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.events.StreamPrinterEventHandler import StreamPrinterEventHandler
stream_printer_event_handler = StreamPrinterEventHandler(analysis_context)
from aminer.events.SyslogWriterEventHandler import SyslogWriterEventHandler
syslog_writer_event_handler = SyslogWriterEventHandler(analysis_context)
anomaly_event_handlers = [
stream_printer_event_handler, syslog_writer_event_handler
]
from aminer.input import SimpleMultisourceAtomSync
simple_multisource_atom_sync = SimpleMultisourceAtomSync([atom_filter], 9)
# Now define the AtomizerFactory using the model. A simple line
# based one is usually sufficient.
from aminer.input import SimpleByteStreamLineAtomizerFactory
analysis_context.atomizer_factory = SimpleByteStreamLineAtomizerFactory(
parsing_model, [simple_multisource_atom_sync],
anomaly_event_handlers,
default_timestamp_paths=['model/DiskUpgrade/Date'])
# Just report all unparsed atoms to the event handlers.
from aminer.input 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 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="NewPath")
atom_filter.add_handler(new_match_path_detector)
from aminer.analysis import NewMatchPathValueComboDetector
new_match_path_value_combo_detector = NewMatchPathValueComboDetector(
analysis_context.aminer_config,
['/model/HomePath/Username', '/model/HomePath/Path'],
anomaly_event_handlers,
auto_include_flag=True)
analysis_context.register_component(new_match_path_value_combo_detector,
component_name="NewValueCombo")
atom_filter.add_handler(new_match_path_value_combo_detector)
# 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 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', 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', 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')
]
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_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)
anomaly_event_handlers = [stream_printer_event_handler]
# Now define the AtomizerFactory using the model. A simple line based one is usually sufficient.
from aminer.input 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.input 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 import AllowlistViolationDetector
# 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_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'))
])
]
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 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/Job Number'],
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 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:
from aminer.parsing import SequenceModelElement
import ApacheAccessModel
apache_access_model = ApacheAccessModel.get_model()
parsing_model = SequenceModelElement('model', [apache_access_model])
# 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)
anomaly_event_handlers = []
# Now define the AtomizerFactory using the model. A simple line
# based one is usually sufficient.
from aminer.input import SimpleByteStreamLineAtomizerFactory
analysis_context.atomizer_factory = SimpleByteStreamLineAtomizerFactory(
parsing_model, [atom_filter],
anomaly_event_handlers,
default_timestamp_paths='/model/accesslog/time')
# Just report all unparsed atoms to the event handlers.
from aminer.input import SimpleUnparsedAtomHandler
atom_filter.add_handler(SimpleUnparsedAtomHandler(anomaly_event_handlers),
stop_when_handled_flag=True)
from aminer.analysis import NewMatchPathDetector
new_match_path_detector = NewMatchPathDetector(
analysis_context.aminer_config,
anomaly_event_handlers,
auto_include_flag=learn_mode)
analysis_context.register_component(new_match_path_detector,
component_name=None)
atom_filter.add_handler(new_match_path_detector)
# Check if status-code changed
from aminer.analysis import NewMatchPathValueDetector
new_match_path_value_detector = NewMatchPathValueDetector(
analysis_context.aminer_config, ["/model/accesslog/status"],
anomaly_event_handlers,
auto_include_flag=learn_mode)
analysis_context.register_component(new_match_path_value_detector,
component_name=None)
atom_filter.add_handler(new_match_path_value_detector)
# Check if HTTP-Method for a HTTP-Request has changed
from aminer.analysis import NewMatchPathValueComboDetector
new_match_path_value_combo_detector = NewMatchPathValueComboDetector(
analysis_context.aminer_config,
["/model/accesslog/request", "/model/accesslog/method"],
anomaly_event_handlers,
auto_include_flag=learn_mode)
analysis_context.register_component(new_match_path_value_combo_detector,
component_name=None)
atom_filter.add_handler(new_match_path_value_combo_detector)
# Check if HTTP-Statuscode for a HTTP-Request has changed
new_match_path_value_combo_detector2 = NewMatchPathValueComboDetector(
analysis_context.aminer_config,
["/model/accesslog/request", "/model/accesslog/status"],
anomaly_event_handlers,
auto_include_flag=learn_mode)
analysis_context.register_component(new_match_path_value_combo_detector2,
component_name=None)
atom_filter.add_handler(new_match_path_value_combo_detector2)
# Add stdout stream printing for debugging, tuning.
from aminer.events import StreamPrinterEventHandler
anomaly_event_handlers.append(StreamPrinterEventHandler(analysis_context))
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."""
# skipcq: PYL-W0611
import importlib
# skipcq: PYL-W0611
import configparser
# skipcq: PYL-W0611
import sys
# import json
# from pprint import pprint
parserModelDict = {}
start = None
wscount = 0
whitespace_str = b' '
# We might be able to remove this and us it like the config_properties
# skipcq: PYL-W0603
global yamldata
for item in yamldata['Parser']:
if item['id'] == 'START':
start = item
continue
if item['type'].endswith('ModelElement') and item['id'] != 'START':
func = getattr(__import__("aminer.parsing", fromlist=[item['type']]), item['type'])
if 'args' in item:
if isinstance(item['args'], list):
# encode string to bytearray
for j in range(len(item['args'])):
item['args'][j] = item['args'][j].encode()
parserModelDict[item['id']] = func(item['name'], item['args'])
else:
parserModelDict[item['id']] = func(item['name'], item['args'].encode())
else:
parserModelDict[item['id']] = func(item['name'])
else:
# skipcq: PTC-W0034
func = getattr(__import__(item['type']), 'get_model')
parserModelDict[item['id']] = func()
argslist = []
if start['type'].endswith('ModelElement'):
# skipcq: PTC-W0034
func = getattr(__import__("aminer.parsing", fromlist=[start['type']]), start['type'])
else:
# skipcq: PTC-W0034
func = getattr(__import__(start['type']), 'get_model')
if 'args' in start:
if isinstance(start['args'], list):
for i in start['args']:
if i == 'WHITESPACE':
from aminer.parsing import FixedDataModelElement
sp = 'sp%d' % wscount
argslist.append(FixedDataModelElement(sp, whitespace_str))
wscount += 1
else:
argslist.append(parserModelDict[i])
parsing_model = func(start['name'], argslist)
else:
parsing_model = func(start['name'], [parserModelDict[start['args']]])
else:
parsing_model = func()
# 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.
atomFilter = AtomFilters.SubhandlerFilter(None)
anomaly_event_handlers = []
# Now define the AtomizerFactory using the model. A simple line
# based one is usually sufficient.
from aminer.input import SimpleByteStreamLineAtomizerFactory
if yamldata['Input']['MultiSource'] is True:
from aminer.input import SimpleMultisourceAtomSync
analysis_context.atomizer_factory = SimpleByteStreamLineAtomizerFactory(
parsing_model, [SimpleMultisourceAtomSync([atomFilter], sync_wait_time=5)],
anomaly_event_handlers, default_timestamp_paths=yamldata['Input']['TimestampPath'])
else:
analysis_context.atomizer_factory = SimpleByteStreamLineAtomizerFactory(
parsing_model, [atomFilter], anomaly_event_handlers,
default_timestamp_paths=yamldata['Input']['TimestampPath'])
# Just report all unparsed atoms to the event handlers.
if yamldata['Input']['Verbose'] is True:
from aminer.input import VerboseUnparsedAtomHandler
atomFilter.add_handler(
VerboseUnparsedAtomHandler(anomaly_event_handlers, parsing_model),
stop_when_handled_flag=True)
else:
from aminer.input import SimpleUnparsedAtomHandler
atomFilter.add_handler(
SimpleUnparsedAtomHandler(anomaly_event_handlers),
stop_when_handled_flag=True)
from aminer.analysis import NewMatchPathDetector
if 'LearnMode' in yamldata:
learn = yamldata['LearnMode']
else:
learn = True
nmpd = NewMatchPathDetector(
analysis_context.aminer_config, anomaly_event_handlers, auto_include_flag=learn)
analysis_context.register_component(nmpd, component_name=None)
atomFilter.add_handler(nmpd)
for item in yamldata['Analysis']:
if item['id'] == 'None':
compName = None
else:
compName = item['id']
if 'LearnMode' in yamldata:
learn = yamldata['LearnMode']
else:
learn = item['learnMode']
func = getattr(__import__("aminer.analysis", fromlist=[item['type']]), item['type'])
if item['type'] == 'NewMatchPathValueDetector':
tmpAnalyser = func(
analysis_context.aminer_config,
item['paths'], anomaly_event_handlers, auto_include_flag=learn,
persistence_id=item['persistence_id'],
output_log_line=item['output_logline'])
elif item['type'] == 'NewMatchPathValueComboDetector':
tmpAnalyser = func(
analysis_context.aminer_config, item['paths'],
anomaly_event_handlers, auto_include_flag=learn,
persistence_id=item['persistence_id'],
allow_missing_values_flag=item['allow_missing_values'],
output_log_line=item['output_logline'])
else:
tmpAnalyser = func(
analysis_context.aminer_config,
item['paths'], anomaly_event_handlers, auto_include_flag=learn)
analysis_context.register_component(tmpAnalyser, component_name=compName)
atomFilter.add_handler(tmpAnalyser)
try:
for item in yamldata['EventHandlers']:
func = getattr(__import__("aminer.events", fromlist=[item['type']]), item['type'])
ctx = None
if item['type'] == 'StreamPrinterEventHandler':
if item['json'] is True:
from aminer.events import JsonConverterHandler
ctx = JsonConverterHandler([func(analysis_context)], analysis_context)
else:
ctx = func(analysis_context)
# if item['type'] == 'KafkaEventHandler':
# try:
# item['args'][0]
# except:
# raise ValueError("Kafka-Topic not defined")
# try:
# kafkaconfig = item['args'][1]
# except:
# kafkaconfig = '/etc/aminer/kafka-client.conf'
# config = configparser.ConfigParser()
# config.read(kafkaconfig)
# options = dict(config.items("DEFAULT"))
# for key, val in options.items():
# try:
# if key == "sasl_plain_username":
# continue
# options[key] = int(val)
# except:
# pass
# kafkaEventHandler = func(analysis_context.aminer_config, item['args'][0], options)
# from aminer.events import JsonConverterHandler
# anomaly_event_handlers.append(
# JsonConverterHandler(analysis_context.aminer_config, messageQueueEventHandlers,
# analysis_context, learningMode))
# else:
if ctx is None:
ctx = func(analysis_context)
anomaly_event_handlers.append(ctx)
except KeyError:
# Add stdout stream printing for debugging, tuning.
from aminer.events import StreamPrinterEventHandler
anomaly_event_handlers.append(StreamPrinterEventHandler(analysis_context))
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))