Claude 24f816b6a3
Consolidate 22 sibling repos into layered organism structure
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):

- brain/        LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
                dispatch, A51 channels, and the OSINT cluster
- knowledge/    LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
                MITRE ATT&CK data
- reference/    defensive threat-reference (C3, shhbruh doc) + AdaYaml parser

License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.

Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.

https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
2026-06-10 06:53:01 +00:00

74 lines
2.1 KiB
Markdown

# API Reference: Building Detection Rules with Sigma
## pySigma (sigma-cli)
```python
from sigma.rule import SigmaRule
from sigma.collection import SigmaCollection
from sigma.backends.splunk import SplunkBackend
from sigma.pipelines.splunk import splunk_windows_pipeline
# Load and parse a Sigma rule
rule = SigmaRule.from_yaml(open("rule.yml").read())
print(rule.title, rule.id, rule.level, rule.status)
# Convert to Splunk SPL
pipeline = splunk_windows_pipeline()
backend = SplunkBackend(pipeline)
queries = backend.convert_rule(rule)
for q in queries:
print(q)
# Saved search output format
saved = backend.convert_rule(rule, output_format="savedsearches")
# Batch convert a collection
collection = SigmaCollection.load_ruleset(["./rules/"])
output = backend.convert(collection)
```
## Key Sigma Rule Fields
| Field | Required | Description |
|-------|----------|-------------|
| `title` | Yes | Short rule name |
| `id` | Yes | UUID for the rule |
| `status` | Yes | test, experimental, stable |
| `level` | Yes | informational, low, medium, high, critical |
| `logsource` | Yes | category, product, service |
| `detection` | Yes | Selection + condition logic |
| `tags` | No | ATT&CK tags (attack.tXXXX) |
## Available Backends (pySigma)
| Package | Backend | Target |
|---------|---------|--------|
| `pySigma-backend-splunk` | `SplunkBackend` | Splunk SPL |
| `pySigma-backend-elasticsearch` | `LuceneBackend` | Elastic/OpenSearch |
| `pySigma-backend-microsoft365defender` | `Microsoft365DefenderBackend` | KQL |
| `pySigma-backend-qradar` | `QRadarBackend` | AQL |
## sigma-cli Commands
```bash
# Convert single rule
sigma convert -t splunk -p splunk_windows rule.yml
# Convert directory
sigma convert -t splunk -p splunk_windows ./rules/ -o output.txt
# List backends and pipelines
sigma list backends
sigma list pipelines
# Validate a rule
sigma check rule.yml
```
### References
- pySigma: https://github.com/SigmaHQ/pySigma
- sigma-cli: https://github.com/SigmaHQ/sigma-cli
- Sigma rules repo: https://github.com/SigmaHQ/sigma
- SigmaHQ docs: https://sigmahq.io/docs/guide/getting-started.html