building-detection-rules-with-sigma

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• LICENSE
• SKILL.md
• api-reference.md · references/
• agent.py · scripts/

SKILL.md (first lines)

# Building Detection Rules with Sigma

## When to Use

Use this skill when:
- SOC engineers need to create detection rules portable across multiple SIEM platforms
- Threat intelligence reports describe TTPs requiring new detection coverage
- Existing vendor-specific rules need standardization into a shareable format
- The team adopts Sigma as a detection-as-code standard in CI/CD pipelines

**Do not use** for real-time streaming detection (Sigma is for batch/scheduled searches) or when the target SIEM has native detection features that Sigma cannot express (e.g., Splunk RBA risk scoring).

## Prerequisites

- Python 3.8+ with `pySigma` and appropriate backend (`pySigma-backend-splunk`, `pySigma-backend-elasticsearch`, `pySigma-backend-microsoft365defender`)
- Sigma rule repository cloned: `git clone https://github.com/SigmaHQ/sigma.git`
- MITRE ATT&CK framework knowledge for technique mapping
- Understanding of target SIEM log source field mappings

## Workflow

### Step 1: Define Detection Logic from Threat Intelligence

Start with a threat report or ATT&CK technique. Example: detecting Mimikatz credential dumping (T1003.001 — LSASS Memory):

```yaml
title: Mimikatz Credential Dumping via LSASS Access
id: 0d894093-71bc-43c3-8d63-bf520e73a7c5
status: stable
level: high
description: Detects process accessing lsass.exe memory, indicative of credential dumping tools like Mimikatz
references:
    - https://attack.mitre.org/techniques/T1003/001/
    - https://github.com/gentilkiwi/mimikatz
author: mahipal
date: 2024/03/15
modified: 2024/03/15
tags:
    - attack.credential_access
    - attack.t1003.001
logsource:
    category: process_access
    product: windows
detection:
    selection:
        TargetImage|endswith: '\lsass.exe'
        GrantedAccess|contains:
            - '0x1010'
            - '0x1038'
            - '0x1fffff'
            - '0x40'
    filter_main_svchost:
        SourceImage|endswith: '\svchost.exe'
    filter_main_csrss:
        SourceImage|endswith: '\csrss.exe'
    filter_main_wininit:
        SourceImage|endswith: '\wininit.exe'
    condition: selection and not 1 of filter_main_*
falsepositives:
    - Legitimate security tools accessing LSASS
    - Windows Defender scanning
    - CrowdStrike Falcon sensor
```

### Step 2: Validate Sigma Rule Syntax

Use `sigma check` to validate the rule:

```bash
# Install pySigma and validators
pip install pySigma pySigma-validators-sigmaHQ

# Validate rule
sigma check rule.yml
```

Alternatively, validate with Python:

```python
from sigma.rule import SigmaRule
from sigma.validators.core import SigmaValidator

rule = SigmaRule.from_yaml(open("rule.yml").read())
validator = SigmaValidator()
issues = validator.validate_rule(rule)
for issue in issues:
    print(f"{issue.severity}: {issue.message}")
```

### Step 3: Convert to Target SIEM Query

**Convert to Splunk SPL:**

```python
from sigma.rule import SigmaRule
from sigma.backends.splunk import SplunkBackend
from sigma.pipelines.splunk import splunk_windows_pipeline

pipeline = splunk_windows_pipeline()
backend = SplunkBackend(pipeline)

rule = SigmaRule.from_yaml(open("rule.yml").read())
splunk_query = backend.convert_rule(rule)
print(splunk_query[0])
```

Output:
```spl
TargetImage="*\\lsass.exe" (GrantedAccess="*0x1010*" OR GrantedAccess="*0x1038*"
OR GrantedAccess="*0x1fffff*" OR GrantedAccess="*0x40*")
NOT (SourceImage="*\\svchost.exe") NOT (SourceImage="*\\csrss.exe")
NOT (SourceImage="*\\wininit.exe")
```

**Convert to Elastic Query (Lucene):**

```python
from sigma.backends.elasticsearch import LuceneBackend
from sigma.pipelines.elasticsearch import ecs_windows_pipeline

From adriannoes/awesome-agentic-ai, Apache-2.0.

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