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https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
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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
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API Reference: Implementing Alert Fatigue Reduction
Libraries
splunk-sdk (Splunk SDK for Python)
- Install:
pip install splunk-sdk - Docs: https://dev.splunk.com/enterprise/docs/devtools/python/sdk-python/
splunklib.client.connect(host, port, username, password)-- Connect to Splunkservice.jobs.create(query)-- Execute a search queryjob.is_done()-- Check if search job completedjob.results(output_mode="json")-- Retrieve results in JSON formatsplunklib.results.JSONResultsReader(stream)-- Parse JSON results
Splunk ES Notable Events API
- Endpoint:
/services/notable_update - Methods: POST to update notable event status
- Fields:
status,urgency,owner,comment,ruleUIDs - Status values:
0(Unassigned),1(New),2(In Progress),5(Resolved)
Key SPL Queries
| Purpose | Key Functions |
|---|---|
| Alert volume analysis | stats count by rule_name, eval fp_rate |
| Risk-based alerting | collect index=risk, eval risk_score |
| Alert consolidation | dedup src, rule_name span=300 |
| Capacity calculation | bin _time span=1d, stats avg(daily_alerts) |
| Tiered routing | eval routing = case(urgency, ...) |
Risk-Based Alerting (RBA) Framework
- Risk contributions replace individual alerts
index=riskstores cumulative risk scores per entity- Threshold alert fires only when
total_risk >= 75 - Typical risk score ranges: 5 (low) to 50 (critical)
Metrics Targets
| Metric | Target |
|---|---|
| False Positive Rate | < 30% per production rule |
| Alerts/Analyst/Shift | 40-60 (manageable range) |
| Signal-to-Noise Ratio | > 1.0 |
| MTTD | Under 15 minutes for critical |
| MTTR | Under 4 hours for high severity |
External References
- Splunk ES RBA Docs: https://docs.splunk.com/Documentation/ES/latest/Admin/RBA
- Splunk SDK Python: https://github.com/splunk/splunk-sdk-python
- MITRE ATT&CK Detection: https://attack.mitre.org/resources/