create-rule
DevOps & SecurityAuthor a Cartography security rule (one or more Cypher Facts plus a Pydantic Finding output model) under `cartography/rules/data/rules/`. Use when the user asks to add a security check, detection, attack-surface query, compliance control, CIS benchmark rule, or cross-cloud detection.
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create-rule
Cartography rules detect attack surfaces, security gaps, and compliance issues across the graph. Rules are composed of one or more Facts (Cypher queries) and a Finding output model (Pydantic).
Architecture
Rule (e.g., "database-exposed")
├─ Fact (e.g., "aws-rds-public")
├─ Fact (e.g., "azure-sql-public")
└─ Fact (e.g., "gcp-cloudsql-public")
- Rule — represents a security issue / attack surface.
- Fact — single Cypher query that gathers evidence.
- Finding — Pydantic model defining the result row structure.
Critical rules
cypher_queryaliases must matchFindingfield names exactly. UseRETURN x.id AS id, x.name AS name.cypher_visual_queryreturns nodes, not properties — used for graph viz.- All
Findingfields are| Nonewith defaultNone. Thesourcefield is auto-populated. - Compliance metadata uses
frameworks=, not tags. Keeptagsfor categories only (iam,credentials,stride:*). - Rule IDs and names describe the Cartography security detection, not the compliance control. Put framework scope, requirement/control id, and external control title in
frameworks=.
Instructions
Step 1 — Imports
from cartography.rules.spec.model import (
Fact,
Finding,
Framework,
Maturity,
Module,
Rule,
RuleReference,
)
Step 2 — Author Facts
A Fact is a Cypher query that detects one specific condition:
_aws_public_databases = Fact(
id="aws-rds-public",
name="Publicly accessible AWS RDS instances",
description="AWS RDS databases exposed to the internet",
cypher_query="""
MATCH (db:AWSRDSInstance)
WHERE db.publicly_accessible = true
RETURN db.id AS id, db.db_instance_identifier AS name, db.region AS region
""",
cypher_visual_query="""
MATCH (db:AWSRDSInstance)
WHERE db.publicly_accessible = true
RETURN db
""",
cypher_count_query="""
MATCH (db:AWSRDSInstance)
RETURN COUNT(db) AS count
""",
identity_fields=("id",),
module=Module.AWS,
maturity=Maturity.STABLE,
)
Fact fields:
| Field | Required | Notes |
|---|---|---|
id | Yes | lowercase + hyphens |
name | Yes | human-readable |
description | Yes | what this fact detects |
cypher_query | Yes | structured rows; AS aliases match Finding fields |
cypher_visual_query | Yes | returns nodes for visualization |
cypher_count_query | Yes | total assets evaluated; RETURN COUNT(...) AS count |
module | Yes | Module.AWS, Module.AZURE, Module.GCP, ... |
maturity | Yes | Maturity.EXPERIMENTAL or Maturity.STABLE |
asset_id_field | No | finding field that uniquely identifies an asset (dedupe) |
identity_fields | Yes | tuple of output-model fields forming the finding's stable logical identity across syncs (for downstream lifecycle tracking); required with no default, distinct from asset_id_field |
Step 3 — Define the Finding output model
class DatabaseExposedOutput(Finding):
"""Output model for publicly exposed databases."""
name: str | None = None # human-readable label first: used as the finding title
id: str | None = None
region: str | None = None
- Inherit from
Finding. - Field names must match
cypher_queryaliases exactly. - All fields are
| Nonewith defaultNone. - The
sourcefield is auto-populated with the module name. - Declare a human-readable label as the first field. Downstream consumers derive the finding's title from the first non-empty field in declaration order, so leading with an opaque id, ARN, URI, digest, region, or boolean produces an unreadable title. If the node has no natural name, alias one in the
cypher_query(e.g.coalesce(n.friendly_name, n.short_id) AS name, or an AWSNametag) and declare it first. This is independent ofidentity_fields/asset_id_fieldand ofRETURNorder. See "Display field order (finding title)" indocs/root/usage/rules.md. - Set
identity_fieldson the Fact (required) to the subset of these fields that forms the finding's stable logical identity, excluding volatile context (*_count,days_*,last_used*,*_date, posture booleans, aggregate lists) so downstream lifecycle tracking does not treat a changed metric as a new finding. See "Finding identity vs. display fields" indocs/root/usage/rules.md.
Step 4 — Compose the Rule
database_exposed = Rule(
id="database-exposed",
name="Publicly Accessible Databases",
description="Detects databases exposed to the internet across cloud providers",
output_model=DatabaseExposedOutput,
tags=("infrastructure", "attack_surface", "database"),
facts=(_aws_public_databases, _azure_public_databases, _gcp_cloudsql_public),
version="1.0.0",
)
Rule fields:
| Field | Required | Notes |
|---|---|---|
id | Yes | lowercase + underscores |
name | Yes | human-readable |
description | Yes | what security issue this detects |
output_model | Yes | Pydantic model class |
tags | Yes | tuple of categorisation tags (no compliance) |
facts | Yes | tuple of Fact objects |
version | Yes | semantic version string |
references | No | list of RuleReference for documentation |
frameworks | No | tuple of Framework (compliance metadata) |
Step 5 — Maturity, versioning, tagging
Maturity.EXPERIMENTAL— new, may have bugs / perf issues. Use for testing detection capabilities.Maturity.STABLE— production-ready, well-tested, optimized.
Versioning follows semver (0.1.0 initial, 0.2.0 add facts, 0.2.1 bug fix, 1.0.0 production-ready).
Tag categories:
- Category:
infrastructure,identity,data,network,compute. - Type:
attack_surface,misconfiguration,compliance,vulnerability. - Provider:
aws,azure,gcp,github,okta. - Threat model:
stride:spoofing,stride:tampering,stride:repudiation,stride:information_disclosure,stride:denial_of_service,stride:elevation_of_privilege.
Step 6 — Register the Rule
In cartography/rules/data/rules/__init__.py:
from cartography.rules.data.rules.my_security_rule import my_security_rule
RULES = {
# ... existing rules
my_security_rule.id: my_security_rule,
}
Step 7 — Test it
cartography-rules list my_security_rule
cartography-rules run my_security_rule
cartography-rules run my_security_rule --output json
cartography-rules run my_security_rule --no-experimental
Compliance frameworks
For CIS, NIST, SOC2, etc., attach a Framework object or framework helper instead of polluting tags:
from cartography.rules.data.frameworks.cis import cis_aws
my_rule = Rule(
id="aws_access_keys_not_rotated",
name="Access Keys Not Rotated",
# ...
tags=("iam", "credentials", "stride:spoofing"), # category tags only
frameworks=(
cis_aws("1.14"),
),
)
Compliance-style tags like cis:1.14, cis:aws-5.0 must NOT live in tags. CLI users filter via --framework CIS, --framework CIS:aws, --framework CIS:aws:5.0.
For framework helpers with known canonical controls, the helper fills Framework.control_title. For custom mappings, set Framework(control_title="...") to the external framework control or requirement title. Keep Rule.name as reusable Cartography security copy. Many Cartography rules may map to the same framework control.
Framework helpers encode the one active revision Cartography supports for each benchmark scope today. If Cartography needs to report against multiple benchmark revisions later, add version-aware helpers or explicit framework objects instead of mixing revisions in one helper.
For deeper framework guidance, including CIS benchmark conventions (rule names, IDs, file naming, headers, references), see references/compliance-frameworks.md and references/cis-conventions.md.
Cross-provider rules
Group facts from different cloud providers under one rule. Each fact's cypher_query should include the provider in the result so the Finding has it:
_aws_unencrypted_storage = Fact(
id="aws-s3-unencrypted",
cypher_query="""
MATCH (b:AWSS3Bucket) WHERE b.default_encryption IS NULL
RETURN b.id AS id, b.name AS name, 'aws' AS provider
""",
# ...
module=Module.AWS,
maturity=Maturity.STABLE,
)
_azure_unencrypted_storage = Fact(
id="azure-storage-unencrypted",
cypher_query="""
MATCH (s:AzureStorageAccount) WHERE s.encryption_enabled = false
RETURN s.id AS id, s.name AS name, 'azure' AS provider
""",
module=Module.AZURE,
maturity=Maturity.STABLE,
)
class UnencryptedStorageOutput(Finding):
id: str | None = None
name: str | None = None
provider: str | None = None
unencrypted_storage = Rule(
id="unencrypted_storage",
name="Unencrypted Cloud Storage",
description="Detects unencrypted storage across cloud providers",
output_model=UnencryptedStorageOutput,
tags=("data", "encryption", "compliance"),
facts=(_aws_unencrypted_storage, _azure_unencrypted_storage),
version="1.0.0",
)
Using the ontology
Leverage semantic labels (e.g. UserAccount) and _ont_* properties for cross-module detection:
_unmanaged_accounts = Fact(
id="unmanaged-accounts-ontology",
name="User Accounts Not Linked to Identity",
description="Detects user accounts without a corresponding User identity",
cypher_query="""
MATCH (ua:UserAccount)
WHERE NOT (ua)<-[:HAS_ACCOUNT]-(:User)
RETURN ua.id AS id, ua._ont_email AS email, ua._ont_source AS source
""",
cypher_visual_query="""
MATCH (ua:UserAccount)
WHERE NOT (ua)<-[:HAS_ACCOUNT]-(:User)
RETURN ua
""",
cypher_count_query="""
MATCH (ua:UserAccount)
RETURN COUNT(ua) AS count
""",
module=Module.CROSS_CLOUD,
maturity=Maturity.STABLE,
)
For semantic-label setup, see the enrich-ontology skill.
References (load on demand)
references/compliance-frameworks.md—Frameworkfield reference, CLI filtering,Rule.has_framework()checks.references/ontology-in-rules.md— usingUserAccount/Tenant/Databaselabels and_ont_*props in rule queries.references/cis-conventions.md— CIS rule naming, IDs, file layout, headers, references, complete CIS example.