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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
1.6 KiB
1.6 KiB
API Reference: Breach and Attack Simulation Agent
Dependencies
| Library | Version | Purpose |
|---|---|---|
| requests | >=2.28 | HTTP client for SIEM detection validation |
CLI Usage
python scripts/agent.py \
--target 10.0.1.50 \
--siem-url https://siem.example.com \
--siem-key YOUR_KEY \
--output-dir /reports/
Functions
simulate_technique(technique, target) -> dict
Simulates a MITRE ATT&CK technique and records detection/blocked status.
check_siem_detection(siem_url, api_key, technique_id, time_window) -> dict
Queries SIEM API for alerts matching the simulated technique within time window.
compute_detection_coverage(results) -> dict
Calculates overall detection rate and per-tactic coverage breakdown.
generate_report(target, siem_url, siem_key) -> dict
Runs 7 ATT&CK technique simulations and generates detection gap report.
ATT&CK Techniques Tested
| ID | Name | Tactic |
|---|---|---|
| T1566.001 | Spearphishing Attachment | Initial Access |
| T1059.001 | PowerShell | Execution |
| T1003.001 | LSASS Memory | Credential Access |
| T1021.002 | SMB Admin Shares | Lateral Movement |
| T1486 | Data Encrypted for Impact | Impact |
| T1071.001 | Web Protocols | C2 |
| T1048.003 | Exfiltration Over Unencrypted | Exfiltration |
Output Schema
{
"coverage": {"total_tests": 7, "detected": 5, "missed": 2, "detection_rate_pct": 71.4},
"gaps": [{"technique_id": "T1003.001", "technique_name": "LSASS Memory"}],
"recommendations": ["Create detection rule for T1003.001"]
}