sigma-rules

name

sigma-rules

description

Author Sigma detection rules, correlation rules, filter rules, and processing pipelines from natural language descriptions. Covers the full Sigma v2.1.0 specification including logsource, detection blocks, field modifiers, condition expressions, multi-document YAML, correlation types (event_count, value_count, temporal, temporal_ordered, value_sum, value_avg, value_percentile, value_median), filter injection, and pySigma-compatible pipelines. Use this skill whenever the user mentions Sigma rules, SIEM detection, detection engineering, detection-as-code, SigmaHQ, correlation rules, Sigma filters, Sigma pipelines, field modifiers, logsource, or asks to write, review, or fix detection rules -- even if they don't explicitly say 'Sigma'.

Sigma Rules

Write Sigma detection, correlation, and filter rules plus processing pipelines per the Sigma v2.1.0 specification. This version is backward-compatible with v2.0.0.

Detection Rules

A detection rule matches log events against field conditions.

Template

title: <concise description of what is detected>
id: <UUIDv4>
status: <stable|test|experimental|deprecated|unsupported>
description: <what this rule detects and why it matters>
author: <name>
date: YYYY-MM-DD
modified: YYYY-MM-DD
references:
    - <URL>
tags:
    - attack.<tactic>
    - attack.<technique_id>
logsource:
    category: <category>
    product: <product>
    service: <service>
detection:
    <selection_name>:
        <FieldName|modifier1|modifier2>: <value or list>
    <filter_name>:
        <FieldName>: <value>
    condition: <selection_name> and not <filter_name>
falsepositives:
    - <known false positive scenario>
level: <informational|low|medium|high|critical>

Detection Block

The detection section maps named identifiers to field conditions, then combines them with a condition expression.

YAML mapping (AND-linked fields):

selection:
    EventID: 1
    Image|endswith: '\whoami.exe'

YAML list of mappings (OR-linked):

selection:
    - EventID: 1
      Image|endswith: '\whoami.exe'
    - EventID: 4688
      NewProcessName|endswith: '\whoami.exe'

Keyword list (field-agnostic search):

keywords:
    - 'mimikatz'
    - 'sekurlsa'

Field Modifiers

Modifiers chain with | on the field name. Common modifiers:

Modifier	Effect
contains	Substring match (wraps value in *...*)
startswith	Prefix match (appends *)
endswith	Suffix match (prepends *)
all	AND-link all values (default is OR)
re	Value is a regex (disables wildcard parsing)
cidr	CIDR network match
base64 / base64offset	Match base64-encoded value
wide	UTF-16LE encoding
windash	Match both - and / dash styles
exists	Field existence check (value: true/false)
gt, gte, lt, lte	Numeric comparison
cased	Case-sensitive match
fieldref	Value references another field name

For the full list of 30 modifiers, incompatible combinations, and encoding chains, see references/modifiers.md.

Condition Expressions

Conditions combine named detections with boolean logic:

condition: selection and not filter
condition: 1 of selection* or keywords
condition: all of them

Precedence: not > and > or. Quantifiers: 1 of, all of, any of, N of. Wildcard patterns match detection names (selection*). them matches all identifiers except _-prefixed ones.

For the full grammar, see references/condition-syntax.md.

Wildcards in Values

* matches any number of characters, ? matches exactly one. Escape with backslash: \*, \?, \\. Non-special backslash sequences like \W are preserved literally (important for Windows paths).

Worked Example

Request: "Detect use of the Windows command line to delete shadow copies"

title: Shadow Copy Deletion via Vssadmin or WMIC
id: c947b146-0abc-4f7a-a55e-bf2fcb8dbb60
status: test
description: >
    Detects the use of vssadmin or wmic to delete volume shadow copies,
    a common ransomware and anti-forensics technique.
author: Security Team
date: 2025-01-15
references:
    - https://attack.mitre.org/techniques/T1490/
tags:
    - attack.impact
    - attack.t1490
logsource:
    category: process_creation
    product: windows
detection:
    selection_vssadmin:
        Image|endswith: '\vssadmin.exe'
        CommandLine|contains|all:
            - 'delete'
            - 'shadows'
    selection_wmic:
        Image|endswith: '\wmic.exe'
        CommandLine|contains|all:
            - 'shadowcopy'
            - 'delete'
    condition: 1 of selection_*
falsepositives:
    - Legitimate backup rotation scripts
level: high

For the full detection rule reference (metadata fields, logsource, multi-document YAML, tags), see references/detection-rules.md.

---

Correlation Rules

Correlation rules aggregate or sequence events matched by detection rules over a time window, grouped by key fields.

Template

title: <what the correlation detects>
id: <UUIDv4>
correlation:
    type: <correlation_type>
    rules:
        - <rule-id or wildcard>
    group-by:
        - <field>
    timespan: <duration>
    condition:
        gte: <threshold>
level: <level>

Correlation Types

Type	Purpose	Condition
event_count	Count matching events per group	Threshold: {gte: N}
value_count	Count distinct values of a field per group	Threshold with field: {field: X, gte: N}
temporal	Multiple rule types fire in same window	Extended: "rule_a and rule_b" or default
temporal_ordered	Same as temporal, rules must fire in order	Extended: "rule_a and rule_b"
value_sum	Sum a numeric field across events	Threshold with field
value_avg	Average a numeric field	Threshold with field
value_percentile	Percentile of a numeric field	Threshold with field
value_median	Median of a numeric field	Threshold with field

Condition Block

Threshold (mapping): for count/metric types:

condition:
    gte: 100

With field (required for value_count, value_sum, value_avg, value_percentile, value_median):

condition:
    field: SourceIP
    gte: 5

Operators: gt, gte, lt, lte, eq, neq. Values must be numeric.

Extended (string): for temporal types:

condition: "recon_scan and lateral_movement"

Timespan

Format: integer + unit suffix. Units: s (seconds), m (minutes), h (hours), d (days), w (weeks), M (months, uppercase), y (years). Both timespan and timeframe keys are accepted.

Worked Example

Request: "Alert on brute force: more than 5 failed logins from the same user within 5 minutes"

title: Failed Login
id: d4c9a825-fdb3-472e-9b0e-fa4709aba44c
status: test
logsource:
    category: authentication
    product: windows
detection:
    selection:
        EventType: failed_login
    condition: selection
level: low
---
title: Brute Force Detection
id: a1b2c3d4-e5f6-7890-abcd-ef1234567890
correlation:
    type: event_count
    rules:
        - d4c9a825-fdb3-472e-9b0e-fa4709aba44c
    group-by:
        - User
    timespan: 5m
    condition:
        gte: 5
level: critical

For all 8 correlation types with full examples, see references/correlation-rules.md.

---

Filter Rules

Filter rules inject AND NOT exclusion conditions into referenced detection rules, enabling centralized tuning without modifying original rules.

Template

title: <what is being filtered>
logsource:
    category: <must match target rule>
    product: <must match target rule>
filter:
    rules:
        - <target-rule-id>
    selection:
        <FieldName|modifier>: <value>
    condition: selection

Key Points

• selection, condition, and rules all live inside the filter section
• rules: [] (empty) applies the filter globally to all matching rules
• Filter rules should not have level or status fields
• Multiple filters on the same rule use independent detection namespaces (no collision)

Worked Example

Request: "Exclude service accounts from the brute force rule"

title: Exclude Service Accounts from Brute Force
logsource:
    category: authentication
    product: windows
filter:
    rules:
        - d4c9a825-fdb3-472e-9b0e-fa4709aba44c
    selection:
        User|startswith: 'svc_'
    condition: selection

For global vs targeted filters and multi-filter patterns, see references/filter-rules.md.

---

Processing Pipelines

Pipelines transform Sigma rule ASTs before evaluation -- typically for field name mapping between generic Sigma field names and backend-specific schemas (ECS, Splunk CIM, etc.).

Template

name: <pipeline name>
priority: <integer, lower runs first>
transformations:
  - type: field_name_mapping
    mapping:
      <SigmaField>: <backend_field>
    rule_conditions:
      - type: logsource
        product: <product>

Common Transformations

Type	Purpose	Key Parameters
field_name_mapping	Rename fields	mapping: {old: new}
field_name_prefix	Add prefix to all fields	prefix: string
replace_string	Regex replacement in values	regex, replacement
drop_detection_item	Remove matching detection items	(none)
change_logsource	Rewrite logsource fields	category, product, service
add_condition	Inject extra conditions	conditions: {field: value}

Rule Conditions

Transformations only apply when all rule_conditions match:

Type	Matches When
logsource	Rule logsource matches category/product/service
contains_detection_item	Rule has a detection item with the given field
tag	Rule has the given tag
is_sigma_rule	Document is a detection rule
is_sigma_correlation_rule	Document is a correlation rule

Worked Example

Request: "Map generic Sigma fields to Elastic Common Schema for Windows process creation rules"

name: ECS Windows Process Creation
priority: 10
transformations:
  - type: field_name_mapping
    mapping:
      CommandLine: process.command_line
      Image: process.executable
      ParentImage: process.parent.executable
      User: user.name
      OriginalFileName: process.pe.original_file_name
      Hashes: process.hash
      ParentCommandLine: process.parent.command_line
      IntegrityLevel: winlog.event_data.IntegrityLevel
      LogonId: winlog.logon.id
    rule_conditions:
      - type: logsource
        product: windows
        category: process_creation
  - type: change_logsource
    product: windows
    category: process_creation
    rule_conditions:
      - type: logsource
        product: windows
        category: process_creation

For the full list of 26 transformations, all condition types, variables, and expression syntax, see references/pipelines.md.

---

Authoring Checklist

When writing or reviewing Sigma rules, verify:

• title is present and under 256 characters
• id is a valid UUIDv4 (8-4-4-4-12 hex format)
• status is one of: stable, test, experimental, deprecated, unsupported
• level is one of: informational, low, medium, high, critical
• date and modified use YYYY-MM-DD format; modified >= date
• logsource is present with at least one of category, product, service
• Logsource values are lowercase
• Detection has at least one named identifier and a condition
• Condition only references identifiers that exist in the detection block
• Tags match ^[a-z0-9_-]+\.[a-z0-9._-]+$ (e.g. attack.t1059)
• No incompatible modifier combinations (e.g. contains|startswith, re|contains)
• deprecated rules have a related entry
• Correlation rules have type, rules, group-by, and timespan
• Filter rules have rules, selection, and condition inside the filter section
• Filter rules do not have level or status

Multi-Document YAML

Multiple rules in one file are separated by ---. Collection actions control template inheritance:

• action: global -- store as template merged into all subsequent rules
• action: reset -- clear the template
• action: repeat -- clone the previous rule and merge current fields on top

This is commonly used to share logsource across detection + correlation rule pairs.

Additional References

• Detection rules deep dive -- metadata, logsource, multi-document, tags
• Correlation rules -- all 8 types with examples
• Filter rules -- global vs targeted, multi-filter patterns
• Pipelines -- all 26 transformations and conditions
• Field modifiers -- all 30 modifiers, chaining, compatibility
• Condition syntax -- grammar, precedence, quantifiers