mirror of https://github.com/SHOGGOTH-SECTOR/sica-fondt.git synced 2026-08-01 08:30:20 +00:00

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

2.1 KiB

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API Reference — Hunting for Living-off-the-Cloud Techniques

Libraries Used

elasticsearch (elasticsearch-py): Query Elastic SIEM for cloud abuse indicators
re: Pattern matching against cloud C2 domain patterns in DNS logs

CLI Interface

python agent.py hunt --es-host <url> --index <pattern> [--api-key <key>] [--hours <n>]
python agent.py dns --log-file <path>

Core Functions

`hunt_lotc_elastic(es_host, es_index, api_key=None, hours=24)`

Executes five pre-built hunting queries against Elasticsearch to detect cloud service abuse.

Parameters:

Name	Type	Description
`es_host`	str	Elasticsearch host URL (e.g., `https://es:9200`)
`es_index`	str	Index pattern (default: `logs-*`)
`api_key`	str	Optional API key for authentication
`hours`	int	Lookback window in hours

Returns: dict with hunts list (each with name, description, hits, events) and total_hits.

`analyze_dns_logs(log_file)`

Scans DNS query log files for connections to known cloud services used for C2, staging, and exfiltration.

Parameters:

Name	Type	Description
`log_file`	str	Path to DNS query log file

Returns: dict with total_matches, findings list, and cloud_services_detected.

Hunting Queries

Query Name	MITRE Technique	Description
`azure_storage_exfil`	T1567.002	Large uploads to Azure Blob Storage
`aws_s3_staging`	T1537	Unusual S3 bucket creation or large PutObject
`saas_c2_channel`	T1102	Outbound connections to SaaS APIs (Telegram, Slack, Discord)
`cloud_function_invoke`	T1584.007	Cloud function invocation via LOLBins
`github_raw_download`	T1105	Payload downloads from raw GitHub content

Elasticsearch API Calls

Elasticsearch(hosts=[url], api_key=key) — Initialize client
es.search(index=pattern, body=query) — Execute search query
Response: resp["hits"]["total"]["value"], resp["hits"]["hits"][]._source

Dependencies

pip install elasticsearch>=8.0

2.1 KiB Raw Blame History