Mika Ayenson
1356 lines
51 KiB
Python
1356 lines
51 KiB
Python
# Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
|
|
# or more contributor license agreements. Licensed under the Elastic License
|
|
# 2.0; you may not use this file except in compliance with the Elastic License
|
|
# 2.0.
|
|
"""Rule object."""
|
|
import copy
|
|
import dataclasses
|
|
import json
|
|
import os
|
|
import typing
|
|
from abc import ABC, abstractmethod
|
|
from dataclasses import dataclass, field
|
|
from functools import cached_property
|
|
from pathlib import Path
|
|
from typing import Any, Dict, List, Literal, Optional, Tuple, Union
|
|
from uuid import uuid4
|
|
|
|
import eql
|
|
from semver import Version
|
|
from marko.block import Document as MarkoDocument
|
|
from marko.ext.gfm import gfm
|
|
from marshmallow import ValidationError, validates_schema
|
|
|
|
import kql
|
|
|
|
from . import beats, ecs, endgame, utils
|
|
from .integrations import (find_least_compatible_version, get_integration_schema_fields,
|
|
load_integrations_manifests, load_integrations_schemas,
|
|
parse_datasets)
|
|
from .misc import load_current_package_version
|
|
from .mixins import MarshmallowDataclassMixin, StackCompatMixin
|
|
from .rule_formatter import nested_normalize, toml_write
|
|
from .schemas import (SCHEMA_DIR, definitions, downgrade,
|
|
get_min_supported_stack_version, get_stack_schemas,
|
|
strip_non_public_fields)
|
|
from .schemas.stack_compat import get_restricted_fields
|
|
from .utils import cached, convert_time_span, PatchedTemplate
|
|
|
|
_META_SCHEMA_REQ_DEFAULTS = {}
|
|
MIN_FLEET_PACKAGE_VERSION = '7.13.0'
|
|
|
|
BUILD_FIELD_VERSIONS = {
|
|
"related_integrations": (Version.parse('8.3.0'), None),
|
|
"required_fields": (Version.parse('8.3.0'), None),
|
|
"setup": (Version.parse('8.3.0'), None)
|
|
}
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class RuleMeta(MarshmallowDataclassMixin):
|
|
"""Data stored in a rule's [metadata] section of TOML."""
|
|
creation_date: definitions.Date
|
|
updated_date: definitions.Date
|
|
deprecation_date: Optional[definitions.Date]
|
|
|
|
# Optional fields
|
|
bypass_bbr_timing: Optional[bool]
|
|
comments: Optional[str]
|
|
integration: Optional[Union[str, List[str]]]
|
|
maturity: Optional[definitions.Maturity]
|
|
min_stack_version: Optional[definitions.SemVer]
|
|
min_stack_comments: Optional[str]
|
|
os_type_list: Optional[List[definitions.OSType]]
|
|
query_schema_validation: Optional[bool]
|
|
related_endpoint_rules: Optional[List[str]]
|
|
promotion: Optional[bool]
|
|
|
|
# Extended information as an arbitrary dictionary
|
|
extended: Optional[Dict[str, Any]]
|
|
|
|
def get_validation_stack_versions(self) -> Dict[str, dict]:
|
|
"""Get a dict of beats and ecs versions per stack release."""
|
|
stack_versions = get_stack_schemas(self.min_stack_version)
|
|
return stack_versions
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class RuleTransform(MarshmallowDataclassMixin):
|
|
"""Data stored in a rule's [transform] section of TOML."""
|
|
|
|
# note (investigation guides) Markdown plugins
|
|
# /elastic/kibana/tree/main/x-pack/plugins/security_solution/public/common/components/markdown_editor/plugins
|
|
##############################################
|
|
|
|
# timelines out of scope at the moment
|
|
|
|
@dataclass(frozen=True)
|
|
class OsQuery:
|
|
label: str
|
|
query: str
|
|
ecs_mapping: Optional[Dict[str, Dict[Literal['field', 'value'], str]]]
|
|
|
|
@dataclass(frozen=True)
|
|
class Investigate:
|
|
@dataclass(frozen=True)
|
|
class Provider:
|
|
excluded: bool
|
|
field: str
|
|
queryType: definitions.InvestigateProviderQueryType
|
|
value: str
|
|
valueType: definitions.InvestigateProviderValueType
|
|
|
|
label: str
|
|
description: Optional[str]
|
|
providers: List[List[Provider]]
|
|
relativeFrom: Optional[str]
|
|
relativeTo: Optional[str]
|
|
|
|
# these must be lists in order to have more than one. Their index in the list is how they will be referenced in the
|
|
# note string templates
|
|
osquery: Optional[List[OsQuery]]
|
|
investigate: Optional[List[Investigate]]
|
|
|
|
def render_investigate_osquery_to_string(self) -> Dict[definitions.TransformTypes, List[str]]:
|
|
obj = self.to_dict()
|
|
|
|
rendered: Dict[definitions.TransformTypes, List[str]] = {'osquery': [], 'investigate': []}
|
|
for plugin, entries in obj.items():
|
|
for entry in entries:
|
|
rendered[plugin].append(f'!{{{plugin}{json.dumps(entry, sort_keys=True, separators=(",", ":"))}}}')
|
|
|
|
return rendered
|
|
|
|
##############################################
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class BaseThreatEntry:
|
|
id: str
|
|
name: str
|
|
reference: str
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class SubTechnique(BaseThreatEntry):
|
|
"""Mapping to threat subtechnique."""
|
|
reference: definitions.SubTechniqueURL
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class Technique(BaseThreatEntry):
|
|
"""Mapping to threat subtechnique."""
|
|
# subtechniques are stored at threat[].technique.subtechnique[]
|
|
reference: definitions.TechniqueURL
|
|
subtechnique: Optional[List[SubTechnique]]
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class Tactic(BaseThreatEntry):
|
|
"""Mapping to a threat tactic."""
|
|
reference: definitions.TacticURL
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class ThreatMapping(MarshmallowDataclassMixin):
|
|
"""Mapping to a threat framework."""
|
|
framework: Literal["MITRE ATT&CK"]
|
|
tactic: Tactic
|
|
technique: Optional[List[Technique]]
|
|
|
|
@staticmethod
|
|
def flatten(threat_mappings: Optional[List]) -> 'FlatThreatMapping':
|
|
"""Get flat lists of tactic and technique info."""
|
|
tactic_names = []
|
|
tactic_ids = []
|
|
technique_ids = set()
|
|
technique_names = set()
|
|
sub_technique_ids = set()
|
|
sub_technique_names = set()
|
|
|
|
for entry in (threat_mappings or []):
|
|
tactic_names.append(entry.tactic.name)
|
|
tactic_ids.append(entry.tactic.id)
|
|
|
|
for technique in (entry.technique or []):
|
|
technique_names.add(technique.name)
|
|
technique_ids.add(technique.id)
|
|
|
|
for subtechnique in (technique.subtechnique or []):
|
|
sub_technique_ids.add(subtechnique.id)
|
|
sub_technique_names.add(subtechnique.name)
|
|
|
|
return FlatThreatMapping(
|
|
tactic_names=sorted(tactic_names),
|
|
tactic_ids=sorted(tactic_ids),
|
|
technique_names=sorted(technique_names),
|
|
technique_ids=sorted(technique_ids),
|
|
sub_technique_names=sorted(sub_technique_names),
|
|
sub_technique_ids=sorted(sub_technique_ids)
|
|
)
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class RiskScoreMapping(MarshmallowDataclassMixin):
|
|
field: str
|
|
operator: Optional[definitions.Operator]
|
|
value: Optional[str]
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class SeverityMapping(MarshmallowDataclassMixin):
|
|
field: str
|
|
operator: Optional[definitions.Operator]
|
|
value: Optional[str]
|
|
severity: Optional[str]
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class FlatThreatMapping(MarshmallowDataclassMixin):
|
|
tactic_names: List[str]
|
|
tactic_ids: List[str]
|
|
technique_names: List[str]
|
|
technique_ids: List[str]
|
|
sub_technique_names: List[str]
|
|
sub_technique_ids: List[str]
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class AlertSuppressionMapping(MarshmallowDataclassMixin, StackCompatMixin):
|
|
"""Mapping to alert suppression."""
|
|
@dataclass
|
|
class AlertSuppressionDuration:
|
|
"""Mapping to allert suppression duration."""
|
|
unit: definitions.TimeUnits
|
|
value: int
|
|
|
|
group_by: List[definitions.NonEmptyStr]
|
|
duration: Optional[AlertSuppressionDuration]
|
|
missing_fields_strategy: definitions.AlertSuppressionMissing
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class BaseRuleData(MarshmallowDataclassMixin, StackCompatMixin):
|
|
@dataclass
|
|
class RequiredFields:
|
|
name: definitions.NonEmptyStr
|
|
type: definitions.NonEmptyStr
|
|
ecs: bool
|
|
|
|
@dataclass
|
|
class RelatedIntegrations:
|
|
package: definitions.NonEmptyStr
|
|
version: definitions.NonEmptyStr
|
|
integration: Optional[definitions.NonEmptyStr]
|
|
|
|
actions: Optional[list]
|
|
author: List[str]
|
|
building_block_type: Optional[definitions.BuildingBlockType]
|
|
description: str
|
|
enabled: Optional[bool]
|
|
exceptions_list: Optional[list]
|
|
license: Optional[str]
|
|
false_positives: Optional[List[str]]
|
|
filters: Optional[List[dict]]
|
|
# trailing `_` required since `from` is a reserved word in python
|
|
from_: Optional[str] = field(metadata=dict(data_key="from"))
|
|
interval: Optional[definitions.Interval]
|
|
max_signals: Optional[definitions.MaxSignals]
|
|
meta: Optional[Dict[str, Any]]
|
|
name: definitions.RuleName
|
|
note: Optional[definitions.Markdown]
|
|
# can we remove this comment?
|
|
# explicitly NOT allowed!
|
|
# output_index: Optional[str]
|
|
references: Optional[List[str]]
|
|
related_integrations: Optional[List[RelatedIntegrations]] = field(metadata=dict(metadata=dict(min_compat="8.3")))
|
|
required_fields: Optional[List[RequiredFields]] = field(metadata=dict(metadata=dict(min_compat="8.3")))
|
|
risk_score: definitions.RiskScore
|
|
risk_score_mapping: Optional[List[RiskScoreMapping]]
|
|
rule_id: definitions.UUIDString
|
|
rule_name_override: Optional[str]
|
|
setup: Optional[definitions.Markdown] = field(metadata=dict(metadata=dict(min_compat="8.3")))
|
|
severity_mapping: Optional[List[SeverityMapping]]
|
|
severity: definitions.Severity
|
|
tags: Optional[List[str]]
|
|
throttle: Optional[str]
|
|
timeline_id: Optional[definitions.TimelineTemplateId]
|
|
timeline_title: Optional[definitions.TimelineTemplateTitle]
|
|
timestamp_override: Optional[str]
|
|
to: Optional[str]
|
|
type: definitions.RuleType
|
|
threat: Optional[List[ThreatMapping]]
|
|
|
|
@classmethod
|
|
def save_schema(cls):
|
|
"""Save the schema as a jsonschema."""
|
|
fields: Tuple[dataclasses.Field, ...] = dataclasses.fields(cls)
|
|
type_field = next(f for f in fields if f.name == "type")
|
|
rule_type = typing.get_args(type_field.type)[0] if cls != BaseRuleData else "base"
|
|
schema = cls.jsonschema()
|
|
version_dir = SCHEMA_DIR / "master"
|
|
version_dir.mkdir(exist_ok=True, parents=True)
|
|
|
|
# expand out the jsonschema definitions
|
|
with (version_dir / f"master.{rule_type}.json").open("w") as f:
|
|
json.dump(schema, f, indent=2, sort_keys=True)
|
|
|
|
def validate_query(self, meta: RuleMeta) -> None:
|
|
pass
|
|
|
|
@cached_property
|
|
def get_restricted_fields(self) -> Optional[Dict[str, tuple]]:
|
|
"""Get stack version restricted fields."""
|
|
fields: List[dataclasses.Field, ...] = list(dataclasses.fields(self))
|
|
return get_restricted_fields(fields)
|
|
|
|
@cached_property
|
|
def data_validator(self) -> Optional['DataValidator']:
|
|
return DataValidator(is_elastic_rule=self.is_elastic_rule, **self.to_dict())
|
|
|
|
@cached_property
|
|
def notify(self) -> bool:
|
|
return os.environ.get('DR_NOTIFY_INTEGRATION_UPDATE_AVAILABLE') is not None
|
|
|
|
@cached_property
|
|
def parsed_note(self) -> Optional[MarkoDocument]:
|
|
dv = self.data_validator
|
|
if dv:
|
|
return dv.parsed_note
|
|
|
|
@property
|
|
def is_elastic_rule(self):
|
|
return 'elastic' in [a.lower() for a in self.author]
|
|
|
|
def get_build_fields(self) -> {}:
|
|
"""Get a list of build-time fields along with the stack versions which they will build within."""
|
|
build_fields = {}
|
|
rule_fields = {f.name: f for f in dataclasses.fields(self)}
|
|
|
|
for fld in BUILD_FIELD_VERSIONS:
|
|
if fld in rule_fields:
|
|
build_fields[fld] = BUILD_FIELD_VERSIONS[fld]
|
|
|
|
return build_fields
|
|
|
|
@classmethod
|
|
def process_transforms(cls, transform: RuleTransform, obj: dict) -> dict:
|
|
"""Process transforms from toml [transform] called in TOMLRuleContents.to_dict."""
|
|
# only create functions that CAREFULLY mutate the obj dict
|
|
|
|
def process_note_plugins():
|
|
"""Format the note field with osquery and investigate plugin strings."""
|
|
note = obj.get('note')
|
|
if not note:
|
|
return
|
|
|
|
rendered = transform.render_investigate_osquery_to_string()
|
|
rendered_patterns = {}
|
|
for plugin, entries in rendered.items():
|
|
rendered_patterns.update(**{f'{plugin}_{i}': e for i, e in enumerate(entries)})
|
|
|
|
note_template = PatchedTemplate(note)
|
|
rendered_note = note_template.safe_substitute(**rendered_patterns)
|
|
obj['note'] = rendered_note
|
|
|
|
# call transform functions
|
|
if transform:
|
|
process_note_plugins()
|
|
|
|
return obj
|
|
|
|
|
|
class DataValidator:
|
|
"""Additional validation beyond base marshmallow schema validation."""
|
|
|
|
def __init__(self,
|
|
name: definitions.RuleName,
|
|
is_elastic_rule: bool,
|
|
note: Optional[definitions.Markdown] = None,
|
|
interval: Optional[definitions.Interval] = None,
|
|
building_block_type: Optional[definitions.BuildingBlockType] = None,
|
|
setup: Optional[str] = None,
|
|
**extras):
|
|
# only define fields needing additional validation
|
|
self.name = name
|
|
self.is_elastic_rule = is_elastic_rule
|
|
self.note = note
|
|
# Need to use extras because from is a reserved word in python
|
|
self.from_ = extras.get('from')
|
|
self.interval = interval
|
|
self.building_block_type = building_block_type
|
|
self.setup = setup
|
|
self._setup_in_note = False
|
|
|
|
@cached_property
|
|
def parsed_note(self) -> Optional[MarkoDocument]:
|
|
if self.note:
|
|
return gfm.parse(self.note)
|
|
|
|
@property
|
|
def setup_in_note(self):
|
|
return self._setup_in_note
|
|
|
|
@setup_in_note.setter
|
|
def setup_in_note(self, value: bool):
|
|
self._setup_in_note = value
|
|
|
|
@cached_property
|
|
def skip_validate_note(self) -> bool:
|
|
return os.environ.get('DR_BYPASS_NOTE_VALIDATION_AND_PARSE') is not None
|
|
|
|
@cached_property
|
|
def skip_validate_bbr(self) -> bool:
|
|
return os.environ.get('DR_BYPASS_BBR_LOOKBACK_VALIDATION') is not None
|
|
|
|
def validate_bbr(self, bypass: bool = False):
|
|
"""Validate building block type and rule type."""
|
|
|
|
if self.skip_validate_bbr or bypass:
|
|
return
|
|
|
|
def validate_lookback(str_time: str) -> bool:
|
|
"""Validate that the time is at least now-119m and at least 60m respectively."""
|
|
try:
|
|
if "now-" in str_time:
|
|
str_time = str_time[4:]
|
|
time = convert_time_span(str_time)
|
|
# if from time is less than 119m as milliseconds
|
|
if time < 119 * 60 * 1000:
|
|
return False
|
|
else:
|
|
return False
|
|
except Exception as e:
|
|
raise ValidationError(f"Invalid time format: {e}")
|
|
return True
|
|
|
|
def validate_interval(str_time: str) -> bool:
|
|
"""Validate that the time is at least now-119m and at least 60m respectively."""
|
|
try:
|
|
time = convert_time_span(str_time)
|
|
# if interval time is less than 60m as milliseconds
|
|
if time < 60 * 60 * 1000:
|
|
return False
|
|
except Exception as e:
|
|
raise ValidationError(f"Invalid time format: {e}")
|
|
return True
|
|
|
|
bypass_instructions = "To bypass, use the environment variable `DR_BYPASS_BBR_LOOKBACK_VALIDATION`"
|
|
if self.building_block_type:
|
|
if not self.from_ or not self.interval:
|
|
raise ValidationError(
|
|
f"{self.name} is invalid."
|
|
"BBR require `from` and `interval` to be defined. "
|
|
"Please set or bypass." + bypass_instructions
|
|
)
|
|
elif not validate_lookback(self.from_) or not validate_interval(self.interval):
|
|
raise ValidationError(
|
|
f"{self.name} is invalid."
|
|
"Default BBR require `from` and `interval` to be at least now-119m and at least 60m respectively "
|
|
"(using the now-Xm and Xm format where x is in minuets). "
|
|
"Please update values or bypass. " + bypass_instructions
|
|
)
|
|
|
|
def validate_note(self):
|
|
if self.skip_validate_note or not self.note:
|
|
return
|
|
|
|
try:
|
|
for child in self.parsed_note.children:
|
|
if child.get_type() == "Heading":
|
|
header = gfm.renderer.render_children(child)
|
|
|
|
if header.lower() == "setup":
|
|
|
|
# check that the Setup header is correctly formatted at level 2
|
|
if child.level != 2:
|
|
raise ValidationError(f"Setup section with wrong header level: {child.level}")
|
|
|
|
# check that the Setup header is capitalized
|
|
if child.level == 2 and header != "Setup":
|
|
raise ValidationError(f"Setup header has improper casing: {header}")
|
|
|
|
self.setup_in_note = True
|
|
|
|
else:
|
|
# check that the header Config does not exist in the Setup section
|
|
if child.level == 2 and "config" in header.lower():
|
|
raise ValidationError(f"Setup header contains Config: {header}")
|
|
|
|
except Exception as e:
|
|
raise ValidationError(f"Invalid markdown in rule `{self.name}`: {e}. To bypass validation on the `note`"
|
|
f"field, use the environment variable `DR_BYPASS_NOTE_VALIDATION_AND_PARSE`")
|
|
|
|
# raise if setup header is in note and in setup
|
|
if self.setup_in_note and self.setup:
|
|
raise ValidationError("Setup header found in both note and setup fields.")
|
|
|
|
|
|
@dataclass
|
|
class QueryValidator:
|
|
query: str
|
|
|
|
@property
|
|
def ast(self) -> Any:
|
|
raise NotImplementedError()
|
|
|
|
@property
|
|
def unique_fields(self) -> Any:
|
|
raise NotImplementedError()
|
|
|
|
def validate(self, data: 'QueryRuleData', meta: RuleMeta) -> None:
|
|
raise NotImplementedError()
|
|
|
|
@cached
|
|
def get_required_fields(self, index: str) -> List[dict]:
|
|
"""Retrieves fields needed for the query along with type information from the schema."""
|
|
current_version = Version.parse(load_current_package_version(), optional_minor_and_patch=True)
|
|
ecs_version = get_stack_schemas()[str(current_version)]['ecs']
|
|
beats_version = get_stack_schemas()[str(current_version)]['beats']
|
|
endgame_version = get_stack_schemas()[str(current_version)]['endgame']
|
|
ecs_schema = ecs.get_schema(ecs_version)
|
|
|
|
beat_types, beat_schema, schema = self.get_beats_schema(index or [], beats_version, ecs_version)
|
|
endgame_schema = self.get_endgame_schema(index or [], endgame_version)
|
|
|
|
# construct integration schemas
|
|
packages_manifest = load_integrations_manifests()
|
|
integrations_schemas = load_integrations_schemas()
|
|
datasets, _ = beats.get_datasets_and_modules(self.ast)
|
|
package_integrations = parse_datasets(datasets, packages_manifest)
|
|
int_schema = {}
|
|
data = {"notify": False}
|
|
|
|
for pk_int in package_integrations:
|
|
package = pk_int["package"]
|
|
integration = pk_int["integration"]
|
|
schema, _ = get_integration_schema_fields(integrations_schemas, package, integration,
|
|
current_version, packages_manifest, {}, data)
|
|
int_schema.update(schema)
|
|
|
|
required = []
|
|
unique_fields = self.unique_fields or []
|
|
|
|
for fld in unique_fields:
|
|
field_type = ecs_schema.get(fld, {}).get('type')
|
|
is_ecs = field_type is not None
|
|
|
|
if not is_ecs:
|
|
if int_schema:
|
|
field_type = int_schema.get(fld, None)
|
|
elif beat_schema:
|
|
field_type = beat_schema.get(fld, {}).get('type')
|
|
elif endgame_schema:
|
|
field_type = endgame_schema.endgame_schema.get(fld, None)
|
|
|
|
required.append(dict(name=fld, type=field_type or 'unknown', ecs=is_ecs))
|
|
|
|
return sorted(required, key=lambda f: f['name'])
|
|
|
|
@cached
|
|
def get_beats_schema(self, index: list, beats_version: str, ecs_version: str) -> (list, dict, dict):
|
|
"""Get an assembled beats schema."""
|
|
beat_types = beats.parse_beats_from_index(index)
|
|
beat_schema = beats.get_schema_from_kql(self.ast, beat_types, version=beats_version) if beat_types else None
|
|
schema = ecs.get_kql_schema(version=ecs_version, indexes=index, beat_schema=beat_schema)
|
|
return beat_types, beat_schema, schema
|
|
|
|
@cached
|
|
def get_endgame_schema(self, index: list, endgame_version: str) -> Optional[endgame.EndgameSchema]:
|
|
"""Get an assembled flat endgame schema."""
|
|
|
|
if "endgame-*" not in index:
|
|
return None
|
|
|
|
endgame_schema = endgame.read_endgame_schema(endgame_version=endgame_version)
|
|
return endgame.EndgameSchema(endgame_schema)
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class QueryRuleData(BaseRuleData):
|
|
"""Specific fields for query event types."""
|
|
type: Literal["query"]
|
|
|
|
index: Optional[List[str]]
|
|
query: str
|
|
language: definitions.FilterLanguages
|
|
alert_suppression: Optional[AlertSuppressionMapping] = field(metadata=dict(metadata=dict(min_compat="8.8")))
|
|
|
|
@cached_property
|
|
def validator(self) -> Optional[QueryValidator]:
|
|
if self.language == "kuery":
|
|
return KQLValidator(self.query)
|
|
elif self.language == "eql":
|
|
return EQLValidator(self.query)
|
|
elif self.language == "esql":
|
|
return ESQLValidator(self.query)
|
|
|
|
def validate_query(self, meta: RuleMeta) -> None:
|
|
validator = self.validator
|
|
if validator is not None:
|
|
return validator.validate(self, meta)
|
|
|
|
@cached_property
|
|
def ast(self):
|
|
validator = self.validator
|
|
if validator is not None:
|
|
return validator.ast
|
|
|
|
@cached_property
|
|
def unique_fields(self):
|
|
validator = self.validator
|
|
if validator is not None:
|
|
return validator.unique_fields
|
|
|
|
@cached
|
|
def get_required_fields(self, index: str) -> List[dict]:
|
|
validator = self.validator
|
|
if validator is not None:
|
|
return validator.get_required_fields(index or [])
|
|
|
|
@validates_schema
|
|
def validates_query_data(self, data, **kwargs):
|
|
"""Custom validation for query rule type and subclasses."""
|
|
# alert suppression is only valid for query rule type and not any of its subclasses
|
|
if data.get('alert_suppression') and data['type'] != 'query':
|
|
raise ValidationError("Alert suppression is only valid for query rule type.")
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class MachineLearningRuleData(BaseRuleData):
|
|
type: Literal["machine_learning"]
|
|
|
|
anomaly_threshold: int
|
|
machine_learning_job_id: Union[str, List[str]]
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class ThresholdQueryRuleData(QueryRuleData):
|
|
"""Specific fields for query event types."""
|
|
|
|
@dataclass(frozen=True)
|
|
class ThresholdMapping(MarshmallowDataclassMixin):
|
|
@dataclass(frozen=True)
|
|
class ThresholdCardinality:
|
|
field: str
|
|
value: definitions.ThresholdValue
|
|
|
|
field: definitions.CardinalityFields
|
|
value: definitions.ThresholdValue
|
|
cardinality: Optional[List[ThresholdCardinality]]
|
|
|
|
type: Literal["threshold"]
|
|
threshold: ThresholdMapping
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class NewTermsRuleData(QueryRuleData):
|
|
"""Specific fields for new terms field rule."""
|
|
|
|
@dataclass(frozen=True)
|
|
class NewTermsMapping(MarshmallowDataclassMixin):
|
|
@dataclass(frozen=True)
|
|
class HistoryWindowStart:
|
|
field: definitions.NonEmptyStr
|
|
value: definitions.NonEmptyStr
|
|
|
|
field: definitions.NonEmptyStr
|
|
value: definitions.NewTermsFields
|
|
history_window_start: List[HistoryWindowStart]
|
|
|
|
type: Literal["new_terms"]
|
|
new_terms: NewTermsMapping
|
|
|
|
def transform(self, obj: dict) -> dict:
|
|
"""Transforms new terms data to API format for Kibana."""
|
|
|
|
obj[obj["new_terms"].get("field")] = obj["new_terms"].get("value")
|
|
obj["history_window_start"] = obj["new_terms"]["history_window_start"][0].get("value")
|
|
del obj["new_terms"]
|
|
return obj
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class EQLRuleData(QueryRuleData):
|
|
"""EQL rules are a special case of query rules."""
|
|
type: Literal["eql"]
|
|
language: Literal["eql"]
|
|
timestamp_field: Optional[str] = field(metadata=dict(metadata=dict(min_compat="8.0")))
|
|
event_category_override: Optional[str] = field(metadata=dict(metadata=dict(min_compat="8.0")))
|
|
tiebreaker_field: Optional[str] = field(metadata=dict(metadata=dict(min_compat="8.0")))
|
|
|
|
def convert_relative_delta(self, lookback: str) -> int:
|
|
now = len("now")
|
|
min_length = now + len('+5m')
|
|
|
|
if lookback.startswith("now") and len(lookback) >= min_length:
|
|
lookback = lookback[len("now"):]
|
|
sign = lookback[0] # + or -
|
|
span = lookback[1:]
|
|
amount = convert_time_span(span)
|
|
return amount * (-1 if sign == "-" else 1)
|
|
else:
|
|
return convert_time_span(lookback)
|
|
|
|
@cached_property
|
|
def is_sample(self) -> bool:
|
|
"""Checks if the current rule is a sample-based rule."""
|
|
return eql.utils.get_query_type(self.ast) == 'sample'
|
|
|
|
@cached_property
|
|
def is_sequence(self) -> bool:
|
|
"""Checks if the current rule is a sequence-based rule."""
|
|
return eql.utils.get_query_type(self.ast) == 'sequence'
|
|
|
|
@cached_property
|
|
def max_span(self) -> Optional[int]:
|
|
"""Maxspan value for sequence rules if defined."""
|
|
if self.is_sequence and hasattr(self.ast.first, 'max_span'):
|
|
return self.ast.first.max_span.as_milliseconds() if self.ast.first.max_span else None
|
|
|
|
@cached_property
|
|
def look_back(self) -> Optional[Union[int, Literal['unknown']]]:
|
|
"""Lookback value of a rule."""
|
|
# https://www.elastic.co/guide/en/elasticsearch/reference/current/common-options.html#date-math
|
|
to = self.convert_relative_delta(self.to) if self.to else 0
|
|
from_ = self.convert_relative_delta(self.from_ or "now-6m")
|
|
|
|
if not (to or from_):
|
|
return 'unknown'
|
|
else:
|
|
return to - from_
|
|
|
|
@cached_property
|
|
def interval_ratio(self) -> Optional[float]:
|
|
"""Ratio of interval time window / max_span time window."""
|
|
if self.max_span:
|
|
interval = convert_time_span(self.interval or '5m')
|
|
return interval / self.max_span
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class ESQLRuleData(QueryRuleData):
|
|
"""ESQL rules are a special case of query rules."""
|
|
type: Literal["esql"]
|
|
language: Literal["esql"]
|
|
query: str
|
|
|
|
@validates_schema
|
|
def validates_esql_data(self, data, **kwargs):
|
|
"""Custom validation for query rule type and subclasses."""
|
|
if data.get('index'):
|
|
raise ValidationError("Index is not a valid field for ES|QL rule type.")
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class ThreatMatchRuleData(QueryRuleData):
|
|
"""Specific fields for indicator (threat) match rule."""
|
|
|
|
@dataclass(frozen=True)
|
|
class Entries:
|
|
|
|
@dataclass(frozen=True)
|
|
class ThreatMapEntry:
|
|
field: definitions.NonEmptyStr
|
|
type: Literal["mapping"]
|
|
value: definitions.NonEmptyStr
|
|
|
|
entries: List[ThreatMapEntry]
|
|
|
|
type: Literal["threat_match"]
|
|
|
|
concurrent_searches: Optional[definitions.PositiveInteger]
|
|
items_per_search: Optional[definitions.PositiveInteger]
|
|
|
|
threat_mapping: List[Entries]
|
|
threat_filters: Optional[List[dict]]
|
|
threat_query: Optional[str]
|
|
threat_language: Optional[definitions.FilterLanguages]
|
|
threat_index: List[str]
|
|
threat_indicator_path: Optional[str]
|
|
|
|
def validate_query(self, meta: RuleMeta) -> None:
|
|
super(ThreatMatchRuleData, self).validate_query(meta)
|
|
|
|
if self.threat_query:
|
|
if not self.threat_language:
|
|
raise ValidationError('`threat_language` required when a `threat_query` is defined')
|
|
|
|
if self.threat_language == "kuery":
|
|
threat_query_validator = KQLValidator(self.threat_query)
|
|
elif self.threat_language == "eql":
|
|
threat_query_validator = EQLValidator(self.threat_query)
|
|
else:
|
|
return
|
|
|
|
threat_query_validator.validate(self, meta)
|
|
|
|
|
|
# All of the possible rule types
|
|
# Sort inverse of any inheritance - see comment in TOMLRuleContents.to_dict
|
|
AnyRuleData = Union[EQLRuleData, ESQLRuleData, ThresholdQueryRuleData, ThreatMatchRuleData,
|
|
MachineLearningRuleData, QueryRuleData, NewTermsRuleData]
|
|
|
|
|
|
class BaseRuleContents(ABC):
|
|
"""Base contents object for shared methods between active and deprecated rules."""
|
|
|
|
@property
|
|
@abstractmethod
|
|
def id(self):
|
|
pass
|
|
|
|
@property
|
|
@abstractmethod
|
|
def name(self):
|
|
pass
|
|
|
|
@property
|
|
@abstractmethod
|
|
def version_lock(self):
|
|
pass
|
|
|
|
@property
|
|
@abstractmethod
|
|
def type(self):
|
|
pass
|
|
|
|
def lock_info(self, bump=True) -> dict:
|
|
version = self.autobumped_version if bump else (self.latest_version or 1)
|
|
contents = {"rule_name": self.name, "sha256": self.sha256(), "version": version, "type": self.type}
|
|
|
|
return contents
|
|
|
|
@property
|
|
def is_dirty(self) -> Optional[bool]:
|
|
"""Determine if the rule has changed since its version was locked."""
|
|
min_stack = Version.parse(self.get_supported_version(), optional_minor_and_patch=True)
|
|
existing_sha256 = self.version_lock.get_locked_hash(self.id, f"{min_stack.major}.{min_stack.minor}")
|
|
|
|
if existing_sha256 is not None:
|
|
return existing_sha256 != self.sha256()
|
|
|
|
@property
|
|
def lock_entry(self) -> Optional[dict]:
|
|
lock_entry = self.version_lock.version_lock.data.get(self.id)
|
|
if lock_entry:
|
|
return lock_entry.to_dict()
|
|
|
|
@property
|
|
def has_forked(self) -> bool:
|
|
"""Determine if the rule has forked at any point (has a previous entry)."""
|
|
lock_entry = self.lock_entry
|
|
if lock_entry:
|
|
return 'previous' in lock_entry
|
|
return False
|
|
|
|
@property
|
|
def is_in_forked_version(self) -> bool:
|
|
"""Determine if the rule is in a forked version."""
|
|
if not self.has_forked:
|
|
return False
|
|
locked_min_stack = Version.parse(self.lock_entry['min_stack_version'], optional_minor_and_patch=True)
|
|
current_package_ver = Version.parse(load_current_package_version(), optional_minor_and_patch=True)
|
|
return current_package_ver < locked_min_stack
|
|
|
|
def get_version_space(self) -> Optional[int]:
|
|
"""Retrieve the number of version spaces available (None for unbound)."""
|
|
if self.is_in_forked_version:
|
|
current_entry = self.lock_entry['previous'][self.metadata.min_stack_version]
|
|
current_version = current_entry['version']
|
|
max_allowable_version = current_entry['max_allowable_version']
|
|
|
|
return max_allowable_version - current_version - 1
|
|
|
|
@property
|
|
def latest_version(self) -> Optional[int]:
|
|
"""Retrieve the latest known version of the rule."""
|
|
min_stack = self.get_supported_version()
|
|
return self.version_lock.get_locked_version(self.id, min_stack)
|
|
|
|
@property
|
|
def autobumped_version(self) -> Optional[int]:
|
|
"""Retrieve the current version of the rule, accounting for automatic increments."""
|
|
version = self.latest_version
|
|
if version is None:
|
|
return 1
|
|
|
|
return version + 1 if self.is_dirty else version
|
|
|
|
@classmethod
|
|
def convert_supported_version(cls, stack_version: Optional[str]) -> Version:
|
|
"""Convert an optional stack version to the minimum for the lock in the form major.minor."""
|
|
min_version = get_min_supported_stack_version()
|
|
if stack_version is None:
|
|
return min_version
|
|
return max(Version.parse(stack_version, optional_minor_and_patch=True), min_version)
|
|
|
|
def get_supported_version(self) -> str:
|
|
"""Get the lowest stack version for the rule that is currently supported in the form major.minor."""
|
|
rule_min_stack = self.metadata.get('min_stack_version')
|
|
min_stack = self.convert_supported_version(rule_min_stack)
|
|
return f"{min_stack.major}.{min_stack.minor}"
|
|
|
|
def _post_dict_conversion(self, obj: dict) -> dict:
|
|
"""Transform the converted API in place before sending to Kibana."""
|
|
|
|
# cleanup the whitespace in the rule
|
|
obj = nested_normalize(obj)
|
|
|
|
# fill in threat.technique so it's never missing
|
|
for threat_entry in obj.get("threat", []):
|
|
threat_entry.setdefault("technique", [])
|
|
|
|
return obj
|
|
|
|
@abstractmethod
|
|
def to_api_format(self, include_version: bool = True) -> dict:
|
|
"""Convert the rule to the API format."""
|
|
|
|
@cached
|
|
def sha256(self, include_version=False) -> str:
|
|
# get the hash of the API dict without the version by default, otherwise it'll always be dirty.
|
|
hashable_contents = self.to_api_format(include_version=include_version)
|
|
return utils.dict_hash(hashable_contents)
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class TOMLRuleContents(BaseRuleContents, MarshmallowDataclassMixin):
|
|
"""Rule object which maps directly to the TOML layout."""
|
|
metadata: RuleMeta
|
|
transform: Optional[RuleTransform]
|
|
data: AnyRuleData = field(metadata=dict(data_key="rule"))
|
|
|
|
@cached_property
|
|
def version_lock(self):
|
|
# VersionLock
|
|
from .version_lock import default_version_lock
|
|
|
|
return getattr(self, '_version_lock', None) or default_version_lock
|
|
|
|
def set_version_lock(self, value):
|
|
from .version_lock import VersionLock
|
|
|
|
if value and not isinstance(value, VersionLock):
|
|
raise TypeError(f'version lock property must be set with VersionLock objects only. Got {type(value)}')
|
|
|
|
# circumvent frozen class
|
|
self.__dict__['_version_lock'] = value
|
|
|
|
@classmethod
|
|
def all_rule_types(cls) -> set:
|
|
types = set()
|
|
for subclass in typing.get_args(AnyRuleData):
|
|
field = next(field for field in dataclasses.fields(subclass) if field.name == "type")
|
|
types.update(typing.get_args(field.type))
|
|
|
|
return types
|
|
|
|
@classmethod
|
|
def get_data_subclass(cls, rule_type: str) -> typing.Type[BaseRuleData]:
|
|
"""Get the proper subclass depending on the rule type"""
|
|
for subclass in typing.get_args(AnyRuleData):
|
|
field = next(field for field in dataclasses.fields(subclass) if field.name == "type")
|
|
if (rule_type, ) == typing.get_args(field.type):
|
|
return subclass
|
|
|
|
raise ValueError(f"Unknown rule type {rule_type}")
|
|
|
|
@property
|
|
def id(self) -> definitions.UUIDString:
|
|
return self.data.rule_id
|
|
|
|
@property
|
|
def name(self) -> str:
|
|
return self.data.name
|
|
|
|
@property
|
|
def type(self) -> str:
|
|
return self.data.type
|
|
|
|
def _post_dict_conversion(self, obj: dict) -> dict:
|
|
"""Transform the converted API in place before sending to Kibana."""
|
|
super()._post_dict_conversion(obj)
|
|
|
|
# build time fields
|
|
self._convert_add_related_integrations(obj)
|
|
self._convert_add_required_fields(obj)
|
|
self._convert_add_setup(obj)
|
|
|
|
# validate new fields against the schema
|
|
rule_type = obj['type']
|
|
subclass = self.get_data_subclass(rule_type)
|
|
subclass.from_dict(obj)
|
|
|
|
# rule type transforms
|
|
self.data.transform(obj) if hasattr(self.data, 'transform') else False
|
|
|
|
return obj
|
|
|
|
def _convert_add_related_integrations(self, obj: dict) -> None:
|
|
"""Add restricted field related_integrations to the obj."""
|
|
field_name = "related_integrations"
|
|
package_integrations = obj.get(field_name, [])
|
|
|
|
if not package_integrations and self.metadata.integration:
|
|
packages_manifest = load_integrations_manifests()
|
|
current_stack_version = load_current_package_version()
|
|
|
|
if self.check_restricted_field_version(field_name):
|
|
if (isinstance(self.data, QueryRuleData) or isinstance(self.data, MachineLearningRuleData)):
|
|
if (self.data.get('language') is not None and self.data.get('language') != 'lucene') or \
|
|
self.data.get('type') == 'machine_learning':
|
|
package_integrations = self.get_packaged_integrations(self.data, self.metadata,
|
|
packages_manifest)
|
|
|
|
if not package_integrations:
|
|
return
|
|
|
|
for package in package_integrations:
|
|
package["version"] = find_least_compatible_version(
|
|
package=package["package"],
|
|
integration=package["integration"],
|
|
current_stack_version=current_stack_version,
|
|
packages_manifest=packages_manifest)
|
|
|
|
# if integration is not a policy template remove
|
|
if package["version"]:
|
|
version_data = packages_manifest.get(package["package"],
|
|
{}).get(package["version"].strip("^"), {})
|
|
policy_templates = version_data.get("policy_templates", [])
|
|
|
|
if package["integration"] not in policy_templates:
|
|
del package["integration"]
|
|
|
|
# remove duplicate entries
|
|
package_integrations = list({json.dumps(d, sort_keys=True):
|
|
d for d in package_integrations}.values())
|
|
obj.setdefault("related_integrations", package_integrations)
|
|
|
|
def _convert_add_required_fields(self, obj: dict) -> None:
|
|
"""Add restricted field required_fields to the obj, derived from the query AST."""
|
|
if isinstance(self.data, QueryRuleData) and self.data.language != 'lucene':
|
|
index = obj.get('index') or []
|
|
required_fields = self.data.get_required_fields(index)
|
|
else:
|
|
required_fields = []
|
|
|
|
field_name = "required_fields"
|
|
if required_fields and self.check_restricted_field_version(field_name=field_name):
|
|
obj.setdefault(field_name, required_fields)
|
|
|
|
def _convert_add_setup(self, obj: dict) -> None:
|
|
"""Add restricted field setup to the obj."""
|
|
rule_note = obj.get("note", "")
|
|
field_name = "setup"
|
|
field_value = obj.get(field_name)
|
|
|
|
if not self.check_explicit_restricted_field_version(field_name):
|
|
return
|
|
|
|
data_validator = self.data.data_validator
|
|
|
|
if not data_validator.skip_validate_note and data_validator.setup_in_note and not field_value:
|
|
parsed_note = self.data.parsed_note
|
|
|
|
# parse note tree
|
|
for i, child in enumerate(parsed_note.children):
|
|
if child.get_type() == "Heading" and "Setup" in gfm.render(child):
|
|
field_value = self._convert_get_setup_content(parsed_note.children[i + 1:])
|
|
|
|
# clean up old note field
|
|
investigation_guide = rule_note.replace("## Setup\n\n", "")
|
|
investigation_guide = investigation_guide.replace(field_value, "").strip()
|
|
obj["note"] = investigation_guide
|
|
obj[field_name] = field_value
|
|
break
|
|
|
|
@cached
|
|
def _convert_get_setup_content(self, note_tree: list) -> str:
|
|
"""Get note paragraph starting from the setup header."""
|
|
setup = []
|
|
for child in note_tree:
|
|
if child.get_type() == "BlankLine" or child.get_type() == "LineBreak":
|
|
setup.append("\n")
|
|
elif child.get_type() == "CodeSpan":
|
|
setup.append(f"`{gfm.renderer.render_raw_text(child)}`")
|
|
elif child.get_type() == "Paragraph":
|
|
setup.append(self._convert_get_setup_content(child.children))
|
|
setup.append("\n")
|
|
elif child.get_type() == "FencedCode":
|
|
setup.append(f"```\n{self._convert_get_setup_content(child.children)}\n```")
|
|
setup.append("\n")
|
|
elif child.get_type() == "RawText":
|
|
setup.append(child.children)
|
|
elif child.get_type() == "Heading" and child.level >= 2:
|
|
break
|
|
else:
|
|
setup.append(self._convert_get_setup_content(child.children))
|
|
|
|
return "".join(setup).strip()
|
|
|
|
def check_explicit_restricted_field_version(self, field_name: str) -> bool:
|
|
"""Explicitly check restricted fields against global min and max versions."""
|
|
min_stack, max_stack = BUILD_FIELD_VERSIONS[field_name]
|
|
return self.compare_field_versions(min_stack, max_stack)
|
|
|
|
def check_restricted_field_version(self, field_name: str) -> bool:
|
|
"""Check restricted fields against schema min and max versions."""
|
|
min_stack, max_stack = self.data.get_restricted_fields.get(field_name)
|
|
return self.compare_field_versions(min_stack, max_stack)
|
|
|
|
@staticmethod
|
|
def compare_field_versions(min_stack: Version, max_stack: Version) -> bool:
|
|
"""Check current rule version is within min and max stack versions."""
|
|
current_version = Version.parse(load_current_package_version(), optional_minor_and_patch=True)
|
|
max_stack = max_stack or current_version
|
|
return min_stack <= current_version >= max_stack
|
|
|
|
@classmethod
|
|
def get_packaged_integrations(cls, data: QueryRuleData, meta: RuleMeta,
|
|
package_manifest: dict) -> Optional[List[dict]]:
|
|
packaged_integrations = []
|
|
datasets, _ = beats.get_datasets_and_modules(data.get('ast') or [])
|
|
|
|
# integration is None to remove duplicate references upstream in Kibana
|
|
# chronologically, event.dataset is checked for package:integration, then rule tags
|
|
# if both exist, rule tags are only used if defined in definitions for non-dataset packages
|
|
# of machine learning analytic packages
|
|
|
|
rule_integrations = meta.get("integration", [])
|
|
if rule_integrations:
|
|
for integration in rule_integrations:
|
|
ineligible_integrations = definitions.NON_DATASET_PACKAGES + \
|
|
[*map(str.lower, definitions.MACHINE_LEARNING_PACKAGES)]
|
|
if integration in ineligible_integrations or isinstance(data, MachineLearningRuleData):
|
|
packaged_integrations.append({"package": integration, "integration": None})
|
|
|
|
packaged_integrations.extend(parse_datasets(datasets, package_manifest))
|
|
|
|
return packaged_integrations
|
|
|
|
@validates_schema
|
|
def post_conversion_validation(self, value: dict, **kwargs):
|
|
"""Additional validations beyond base marshmallow schemas."""
|
|
data: AnyRuleData = value["data"]
|
|
metadata: RuleMeta = value["metadata"]
|
|
|
|
data.validate_query(metadata)
|
|
data.data_validator.validate_note()
|
|
data.data_validator.validate_bbr(metadata.get('bypass_bbr_timing'))
|
|
data.validate(metadata) if hasattr(data, 'validate') else False
|
|
|
|
@staticmethod
|
|
def validate_remote(remote_validator: 'RemoteValidator', contents: 'TOMLRuleContents'):
|
|
remote_validator.validate_rule(contents)
|
|
|
|
def to_dict(self, strip_none_values=True) -> dict:
|
|
# Load schemas directly from the data and metadata classes to avoid schema ambiguity which can
|
|
# result from union fields which contain classes and related subclasses (AnyRuleData). See issue #1141
|
|
metadata = self.metadata.to_dict(strip_none_values=strip_none_values)
|
|
data = self.data.to_dict(strip_none_values=strip_none_values)
|
|
self.data.process_transforms(self.transform, data)
|
|
dict_obj = dict(metadata=metadata, rule=data)
|
|
return nested_normalize(dict_obj)
|
|
|
|
def flattened_dict(self) -> dict:
|
|
flattened = dict()
|
|
flattened.update(self.data.to_dict())
|
|
flattened.update(self.metadata.to_dict())
|
|
return flattened
|
|
|
|
def to_api_format(self, include_version=True) -> dict:
|
|
"""Convert the TOML rule to the API format."""
|
|
converted_data = self.to_dict()['rule']
|
|
converted = self._post_dict_conversion(converted_data)
|
|
|
|
if include_version:
|
|
converted["version"] = self.autobumped_version
|
|
|
|
return converted
|
|
|
|
def check_restricted_fields_compatibility(self) -> Dict[str, dict]:
|
|
"""Check for compatibility between restricted fields and the min_stack_version of the rule."""
|
|
default_min_stack = get_min_supported_stack_version()
|
|
if self.metadata.min_stack_version is not None:
|
|
min_stack = Version.parse(self.metadata.min_stack_version, optional_minor_and_patch=True)
|
|
else:
|
|
min_stack = default_min_stack
|
|
restricted = self.data.get_restricted_fields
|
|
|
|
invalid = {}
|
|
for _field, values in restricted.items():
|
|
if self.data.get(_field) is not None:
|
|
min_allowed, _ = values
|
|
if min_stack < min_allowed:
|
|
invalid[_field] = {'min_stack_version': min_stack, 'min_allowed_version': min_allowed}
|
|
|
|
return invalid
|
|
|
|
|
|
@dataclass
|
|
class TOMLRule:
|
|
contents: TOMLRuleContents = field(hash=True)
|
|
path: Optional[Path] = None
|
|
gh_pr: Any = field(hash=False, compare=False, default=None, repr=False)
|
|
|
|
@property
|
|
def id(self):
|
|
return self.contents.id
|
|
|
|
@property
|
|
def name(self):
|
|
return self.contents.data.name
|
|
|
|
def get_asset(self) -> dict:
|
|
"""Generate the relevant fleet compatible asset."""
|
|
return {"id": self.id, "attributes": self.contents.to_api_format(), "type": definitions.SAVED_OBJECT_TYPE}
|
|
|
|
def save_toml(self):
|
|
assert self.path is not None, f"Can't save rule {self.name} (self.id) without a path"
|
|
converted = dict(metadata=self.contents.metadata.to_dict(), rule=self.contents.data.to_dict())
|
|
if self.contents.transform:
|
|
converted['transform'] = self.contents.transform.to_dict()
|
|
toml_write(converted, str(self.path.absolute()))
|
|
|
|
def save_json(self, path: Path, include_version: bool = True):
|
|
path = path.with_suffix('.json')
|
|
with open(str(path.absolute()), 'w', newline='\n') as f:
|
|
json.dump(self.contents.to_api_format(include_version=include_version), f, sort_keys=True, indent=2)
|
|
f.write('\n')
|
|
|
|
|
|
@dataclass(frozen=True)
|
|
class DeprecatedRuleContents(BaseRuleContents):
|
|
metadata: dict
|
|
data: dict
|
|
transform: Optional[dict]
|
|
|
|
@cached_property
|
|
def version_lock(self):
|
|
# VersionLock
|
|
from .version_lock import default_version_lock
|
|
|
|
return getattr(self, '_version_lock', None) or default_version_lock
|
|
|
|
def set_version_lock(self, value):
|
|
from .version_lock import VersionLock
|
|
|
|
if value and not isinstance(value, VersionLock):
|
|
raise TypeError(f'version lock property must be set with VersionLock objects only. Got {type(value)}')
|
|
|
|
# circumvent frozen class
|
|
self.__dict__['_version_lock'] = value
|
|
|
|
@property
|
|
def id(self) -> str:
|
|
return self.data.get('rule_id')
|
|
|
|
@property
|
|
def name(self) -> str:
|
|
return self.data.get('name')
|
|
|
|
@property
|
|
def type(self) -> str:
|
|
return self.data.get('type')
|
|
|
|
@classmethod
|
|
def from_dict(cls, obj: dict):
|
|
kwargs = dict(metadata=obj['metadata'], data=obj['rule'])
|
|
kwargs['transform'] = obj['transform'] if 'transform' in obj else None
|
|
return cls(**kwargs)
|
|
|
|
def to_api_format(self, include_version=True) -> dict:
|
|
"""Convert the TOML rule to the API format."""
|
|
data = copy.deepcopy(self.data)
|
|
if self.transform:
|
|
transform = RuleTransform.from_dict(self.transform)
|
|
BaseRuleData.process_transforms(transform, data)
|
|
|
|
converted = data
|
|
if include_version:
|
|
converted["version"] = self.autobumped_version
|
|
|
|
converted = self._post_dict_conversion(converted)
|
|
return converted
|
|
|
|
|
|
class DeprecatedRule(dict):
|
|
"""Minimal dict object for deprecated rule."""
|
|
|
|
def __init__(self, path: Path, contents: DeprecatedRuleContents, *args, **kwargs):
|
|
super(DeprecatedRule, self).__init__(*args, **kwargs)
|
|
self.path = path
|
|
self.contents = contents
|
|
|
|
def __repr__(self):
|
|
return f'{type(self).__name__}(contents={self.contents}, path={self.path})'
|
|
|
|
@property
|
|
def id(self) -> str:
|
|
return self.contents.id
|
|
|
|
@property
|
|
def name(self) -> str:
|
|
return self.contents.name
|
|
|
|
|
|
def downgrade_contents_from_rule(rule: TOMLRule, target_version: str, replace_id: bool = True) -> dict:
|
|
"""Generate the downgraded contents from a rule."""
|
|
rule_dict = rule.contents.to_dict()["rule"]
|
|
min_stack_version = target_version or rule.contents.metadata.min_stack_version or "8.3.0"
|
|
min_stack_version = Version.parse(min_stack_version,
|
|
optional_minor_and_patch=True)
|
|
rule_dict.setdefault("meta", {}).update(rule.contents.metadata.to_dict())
|
|
|
|
if replace_id:
|
|
rule_dict["rule_id"] = str(uuid4())
|
|
|
|
rule_dict = downgrade(rule_dict, target_version=str(min_stack_version))
|
|
meta = rule_dict.pop("meta")
|
|
rule_contents_dict = {"rule": rule_dict, "metadata": meta}
|
|
|
|
if rule.contents.transform:
|
|
rule_contents_dict["transform"] = rule.contents.transform.to_dict()
|
|
|
|
rule_contents = TOMLRuleContents.from_dict(rule_contents_dict)
|
|
payload = rule_contents.to_api_format()
|
|
payload = strip_non_public_fields(min_stack_version, payload)
|
|
return payload
|
|
|
|
|
|
def set_eql_config(min_stack_version: str) -> eql.parser.ParserConfig:
|
|
"""Based on the rule version set the eql functions allowed."""
|
|
if not min_stack_version:
|
|
min_stack_version = Version.parse(load_current_package_version(), optional_minor_and_patch=True)
|
|
else:
|
|
min_stack_version = Version.parse(min_stack_version, optional_minor_and_patch=True)
|
|
|
|
config = eql.parser.ParserConfig()
|
|
|
|
for feature, version_range in definitions.ELASTICSEARCH_EQL_FEATURES.items():
|
|
if version_range[0] <= min_stack_version <= (version_range[1] or min_stack_version):
|
|
config.context[feature] = True
|
|
|
|
return config
|
|
|
|
|
|
def get_unique_query_fields(rule: TOMLRule) -> List[str]:
|
|
"""Get a list of unique fields used in a rule query from rule contents."""
|
|
contents = rule.contents.to_api_format()
|
|
language = contents.get('language')
|
|
query = contents.get('query')
|
|
if language in ('kuery', 'eql'):
|
|
# TODO: remove once py-eql supports ipv6 for cidrmatch
|
|
|
|
config = set_eql_config(rule.contents.metadata.get('min_stack_version'))
|
|
with eql.parser.elasticsearch_syntax, eql.parser.ignore_missing_functions, config:
|
|
parsed = kql.parse(query) if language == 'kuery' else eql.parse_query(query)
|
|
|
|
return sorted(set(str(f) for f in parsed if isinstance(f, (eql.ast.Field, kql.ast.Field))))
|
|
|
|
|
|
# avoid a circular import
|
|
from .rule_validators import EQLValidator, ESQLValidator, KQLValidator # noqa: E402
|
|
from .remote_validation import RemoteValidator # noqa: E402
|