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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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Workflows — NoSQL Injection Exploitation
Detection Workflow
- Identify application technology stack (check for MongoDB, CouchDB indicators)
- Map all input points accepting JSON data or query parameters
- Submit operator payloads ($ne, $gt, $regex) in each parameter
- Monitor responses for authentication bypass or data leakage
- Test for JavaScript injection via $where operator
- Document all vulnerable endpoints with proof-of-concept payloads
Blind Extraction Workflow
- Confirm boolean-based injection by comparing true/false responses
- Determine password/field length using $regex with length patterns
- Extract characters one at a time using $regex "^<known_chars>"
- Automate extraction with Python script using binary search
- Validate extracted data by attempting authentication
Automated Scanning Workflow
- Configure proxy (Burp Suite) to intercept target traffic
- Run NoSQLMap against identified endpoints
- Use nuclei with NoSQL injection templates for broad coverage
- Manually verify automated findings with crafted payloads
- Escalate confirmed findings to data extraction or RCE attempts