mirror of
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
1.7 KiB
1.7 KiB
API Reference: Implementing Cloud Workload Protection
AWS SSM Run Command (boto3)
import boto3
ssm = boto3.client("ssm")
# Execute command on instances
resp = ssm.send_command(
InstanceIds=["i-abc123"],
DocumentName="AWS-RunShellScript",
Parameters={"commands": ["ps aux"]},
TimeoutSeconds=60,
)
command_id = resp["Command"]["CommandId"]
# Get output
output = ssm.get_command_invocation(
CommandId=command_id, InstanceId="i-abc123"
)
print(output["StandardOutputContent"])
CloudWatch CPU Monitoring
cw = boto3.client("cloudwatch")
resp = cw.get_metric_statistics(
Namespace="AWS/EC2", MetricName="CPUUtilization",
Dimensions=[{"Name": "InstanceId", "Value": "i-abc123"}],
StartTime=start, EndTime=end, Period=300,
Statistics=["Average"],
)
Key Detection Commands
| Threat | Command |
|---|---|
| Cryptominer | ps aux | grep -iE 'xmrig|minerd' |
| Reverse shell | ss -tlnp | grep ESTAB |
| File integrity | rpm -Va | grep '^..5' |
| Unauthorized binaries | find /tmp -executable -type f |
| Cron persistence | crontab -l; ls /etc/cron.d/ |
GuardDuty Integration
gd = boto3.client("guardduty")
findings = gd.list_findings(DetectorId="detector-id")
for fid in findings["FindingIds"]:
detail = gd.get_findings(DetectorId="detector-id", FindingIds=[fid])
print(detail["Findings"][0]["Type"])