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test_conversion_correlations.py
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import pytest
from sigma.backends.test import TextQueryTestBackend
from sigma.collection import SigmaCollection
from sigma.exceptions import SigmaBackendError, SigmaConversionError
from sigma.processing.pipeline import ProcessingPipeline, QueryPostprocessingItem
from sigma.processing.postprocessing import EmbedQueryTransformation
from .test_conversion_base import test_backend
@pytest.fixture
def event_count_correlation_rule():
return SigmaCollection.from_yaml(
"""
title: Failed logon
name: failed_logon
status: test
logsource:
product: windows
service: security
detection:
selection:
EventID: 4625
condition: selection
---
title: Multiple failed logons for a single user (possible brute force attack)
status: test
correlation:
type: event_count
rules:
- failed_logon
group-by:
- TargetUserName
- TargetDomainName
- fieldB
timespan: 5m
condition:
gte: 10
"""
)
def test_event_count_correlation_single_rule_with_grouping(
test_backend, event_count_correlation_rule
):
assert test_backend.convert(event_count_correlation_rule) == [
"""EventID=4625
| aggregate window=5min count() as event_count by TargetUserName, TargetDomainName, mappedB
| where event_count >= 10"""
]
def test_correlation_without_normalization_support(
monkeypatch, test_backend, event_count_correlation_rule
):
monkeypatch.setattr(test_backend, "correlation_search_field_normalization_expression", None)
assert test_backend.convert(event_count_correlation_rule) == [
"""EventID=4625
| aggregate window=5min count() as event_count by TargetUserName, TargetDomainName, mappedB
| where event_count >= 10"""
]
def test_generate_query_without_referenced_rules_expression(
monkeypatch, test_backend, event_count_correlation_rule
):
monkeypatch.setattr(test_backend, "referenced_rules_expression", None)
monkeypatch.setattr(test_backend, "referenced_rules_expression_joiner", None)
assert test_backend.convert(event_count_correlation_rule) == [
"""EventID=4625
| aggregate window=5min count() as event_count by TargetUserName, TargetDomainName, mappedB
| where event_count >= 10"""
]
@pytest.fixture
def value_count_correlation_rule():
return SigmaCollection.from_yaml(
"""
title: Failed logon
name: failed_logon
status: test
logsource:
product: windows
service: security
detection:
selection:
EventID: 4625
condition: selection
---
title: Multiple failed logons for diffrerent users (possible password spraying attack)
status: test
correlation:
type: value_count
rules:
- failed_logon
timespan: 5m
condition:
gte: 100
field: TargetUserName
"""
)
def test_value_count_correlation_single_rule_without_grouping(
test_backend, value_count_correlation_rule
):
assert test_backend.convert(value_count_correlation_rule) == [
"""EventID=4625
| aggregate window=5min value_count(TargetUserName) as value_count
| where value_count >= 100"""
]
@pytest.fixture
def temporal_correlation_rule():
temporal_correlation_rule = SigmaCollection.from_yaml(
"""
title: Failed logon
name: failed_logon
status: test
logsource:
product: windows
service: security
detection:
selection:
EventID: 4625
condition: selection
---
title: Successful logon
name: successful_logon
status: test
logsource:
product: windows
service: security
detection:
selection:
EventID: 4624
condition: selection
---
title: Failed and successful logons for a single user
status: test
correlation:
type: temporal
rules:
- failed_logon
- successful_logon
timespan: 5m
group-by:
- TargetUserName
- TargetDomainName
"""
)
return temporal_correlation_rule
def test_temporal_correlation_multi_rule_without_condition(test_backend, temporal_correlation_rule):
assert test_backend.convert(temporal_correlation_rule) == [
"""subsearch { EventID=4625 | set event_type="failed_logon" }
subsearch { EventID=4624 | set event_type="successful_logon" }
| temporal window=5min eventtypes=failed_logon,successful_logon by TargetUserName, TargetDomainName
| where eventtype_count >= 2"""
]
def test_temporal_correlation_multi_rule_with_typing_expression(
monkeypatch, test_backend, temporal_correlation_rule
):
monkeypatch.setattr(
test_backend,
"temporal_correlation_query",
{"test": "{search}\n{typing}\n\n{aggregate}\n\n{condition}"},
)
monkeypatch.setattr(
test_backend, "correlation_search_multi_rule_query_expression", "( {query} )"
)
monkeypatch.setattr(
test_backend, "correlation_search_multi_rule_query_expression_joiner", " or "
)
monkeypatch.setattr(test_backend, "typing_expression", "| eval event_type=case({queries})")
monkeypatch.setattr(test_backend, "typing_rule_query_expression_joiner", ", ")
monkeypatch.setattr(test_backend, "typing_rule_query_expression", '{query}, "{ruleid}"')
assert test_backend.convert(temporal_correlation_rule) == [
"""( EventID=4625 ) or ( EventID=4624 )
| eval event_type=case(EventID=4625, "failed_logon", EventID=4624, "successful_logon")
| temporal window=5min eventtypes=failed_logon,successful_logon by TargetUserName, TargetDomainName
| where eventtype_count >= 2"""
]
def test_referenced_rule_expression_used_but_not_defined(
monkeypatch, test_backend, temporal_correlation_rule
):
monkeypatch.setattr(test_backend, "referenced_rules_expression", None)
monkeypatch.setattr(test_backend, "referenced_rules_expression_joiner", None)
with pytest.raises(SigmaBackendError, match="referenced rule expression"):
test_backend.convert(temporal_correlation_rule)
@pytest.fixture
def temporal_ordered_correlation_rule():
return SigmaCollection.from_yaml(
"""
title: Failed logon
name: failed_logon
status: test
logsource:
product: windows
service: security
detection:
selection:
EventID: 4625
condition: selection
---
title: Successful logon
name: successful_logon
status: test
logsource:
product: windows
service: security
detection:
selection:
EventID: 4624
condition: selection
---
title: Discovery activity
name: discovery_activity
status: test
logsource:
category: process_creation
product: windows
detection:
selection:
CommandLine|contains:
- whoami
- dsquery
- net group
condition: selection
---
title: Failed and successful logons for a single user
status: test
correlation:
type: temporal_ordered
rules:
- failed_logon
- successful_logon
- discovery_activity
timespan: 1h
aliases:
user:
failed_logon: TargetUserName
successful_logon: TargetUserName
discovery_activity: User
domain:
failed_logon: TargetDomainName
successful_logon: TargetDomainName
discovery_activity: Domain
mapped:
failed_logon: fieldB
successful_logon: fieldC
discovery_activity: fieldD
group-by:
- user
- domain
- mapped
condition:
gte: 2
"""
)
def test_temporal_ordered_correlation_multi_rule_with_condition_and_field_normalization(
test_backend, temporal_ordered_correlation_rule
):
assert test_backend.convert(temporal_ordered_correlation_rule) == [
"""subsearch { EventID=4625 | set event_type="failed_logon" | set user=TargetUserName | set domain=TargetDomainName | set mapped=mappedB }
subsearch { EventID=4624 | set event_type="successful_logon" | set user=TargetUserName | set domain=TargetDomainName | set mapped=fieldC }
subsearch { CommandLine in ("*whoami*", "*dsquery*", "*net group*") | set event_type="discovery_activity" | set user=User | set domain=Domain | set mapped=fieldD }
| temporal ordered=true window=1h eventtypes=failed_logon,successful_logon,discovery_activity by user, domain, mapped
| where eventtype_count >= 2 and eventtype_order=failed_logon,successful_logon,discovery_activity"""
]
def test_correlation_timespan_in_seconds(monkeypatch, test_backend, event_count_correlation_rule):
monkeypatch.setattr(test_backend, "timespan_seconds", True)
assert test_backend.convert(event_count_correlation_rule) == [
"""EventID=4625
| aggregate window=300 count() as event_count by TargetUserName, TargetDomainName, mappedB
| where event_count >= 10"""
]
def test_correlation_no_aggregation_expression(
monkeypatch, test_backend, value_count_correlation_rule
):
monkeypatch.setattr(test_backend, "groupby_expression_nofield", {"test": " by nothing"})
assert test_backend.convert(value_count_correlation_rule) == [
"""EventID=4625
| aggregate window=5min value_count(TargetUserName) as value_count by nothing
| where value_count >= 100"""
]
def test_correlation_generate_rule(test_backend):
rule_collection = SigmaCollection.from_yaml(
"""
title: Failed logon
name: failed_logon
status: test
logsource:
product: windows
service: security
detection:
selection:
EventID: 4625
condition: selection
---
title: Multiple failed logons for a single user (possible brute force attack)
status: test
correlation:
type: event_count
rules:
- failed_logon
generate: true
group-by:
- TargetUserName
- TargetDomainName
timespan: 5m
condition:
gte: 10
"""
)
assert test_backend.convert(rule_collection) == [
"EventID=4625",
"""EventID=4625
| aggregate window=5min count() as event_count by TargetUserName, TargetDomainName
| where event_count >= 10""",
]
def test_correlation_generate_chained_rule(test_backend):
rule_collection = SigmaCollection.from_yaml(
"""
title: Successful login
name: successful_login
logsource:
product: windows
service: security
detection:
selection:
EventID:
- 528
- 4624
condition: selection
---
title: Single failed login
name: failed_login
logsource:
product: windows
service: security
detection:
selection:
EventID:
- 529
- 4625
condition: selection
---
title: Multiple failed logons
name: multiple_failed_login
correlation:
type: event_count
rules:
- failed_login
generate: true
group-by:
- User
timespan: 10m
condition:
gte: 10
---
title: Multiple Failed Logins Followed by Successful Login
status: test
correlation:
type: temporal_ordered
rules:
- multiple_failed_login
- successful_login
generate: true
group-by:
- User
timespan: 10m
"""
)
assert test_backend.convert(rule_collection) == [
"""EventID in (528, 4624)""",
"""EventID in (529, 4625)""",
"""EventID in (529, 4625)
| aggregate window=10min count() as event_count by User
| where event_count >= 10""",
"""subsearch { EventID in (529, 4625)\n| aggregate window=10min count() as event_count by User\n| where event_count >= 10 | set event_type="multiple_failed_login" }
subsearch { EventID in (528, 4624) | set event_type="successful_login" }
| temporal ordered=true window=10min eventtypes=multiple_failed_login,successful_login by User
| where eventtype_count >= 2 and eventtype_order=multiple_failed_login,successful_login""",
]
def test_correlation_not_supported(monkeypatch, test_backend, event_count_correlation_rule):
monkeypatch.setattr(test_backend, "correlation_methods", None)
with pytest.raises(NotImplementedError, match="Backend does not support correlation"):
test_backend.convert(event_count_correlation_rule)
def test_correlation_method_not_supported(test_backend, event_count_correlation_rule):
with pytest.raises(SigmaConversionError, match="Correlation method 'invalid' is not supported"):
test_backend.convert(event_count_correlation_rule, correlation_method="invalid")
def test_correlation_method_no_supported_for_correlation_type(
monkeypatch, test_backend, event_count_correlation_rule
):
monkeypatch.setattr(
test_backend,
"correlation_methods",
{"test": "Test correlation method", "another": "Another correlation method"},
)
with pytest.raises(
SigmaConversionError,
match="Correlation method 'another' is not supported by backend for correlation type 'event_count'",
):
test_backend.convert(event_count_correlation_rule, correlation_method="another")
def test_correlation_type_not_supported(monkeypatch, test_backend, event_count_correlation_rule):
monkeypatch.setattr(test_backend, "default_correlation_query", None)
with pytest.raises(
NotImplementedError, match="Correlation rule type 'event_count' is not supported"
):
test_backend.convert(event_count_correlation_rule)
def test_correlation_normalization_not_supported(
monkeypatch, test_backend, temporal_ordered_correlation_rule
):
monkeypatch.setattr(test_backend, "correlation_search_field_normalization_expression", None)
monkeypatch.setattr(
test_backend, "correlation_search_field_normalization_expression_joiner", None
)
with pytest.raises(
NotImplementedError, match="Correlation field normalization is not supported"
):
test_backend.convert(temporal_ordered_correlation_rule)
def test_correlation_query_postprocessing(event_count_correlation_rule):
test_backend = TextQueryTestBackend(
ProcessingPipeline(
postprocessing_items=[
QueryPostprocessingItem(EmbedQueryTransformation(prefix="[ ", suffix=" ]"))
]
)
)
assert test_backend.convert(event_count_correlation_rule) == [
"""[ EventID=4625
| aggregate window=5min count() as event_count by TargetUserName, TargetDomainName, fieldB
| where event_count >= 10 ]"""
]