mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
synced 2026-08-01 16:40:24 +00:00
24f816b6a3
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
71 lines
2.7 KiB
Markdown
71 lines
2.7 KiB
Markdown
# Workflows - Runtime Security with Tetragon
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## Deployment Workflow
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### Phase 1: Observation Mode
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1. Install Tetragon with default TracingPolicies (no enforcement)
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2. Collect baseline process execution data for 7-14 days
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3. Analyze event patterns to identify normal vs anomalous behavior
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4. Document expected processes per namespace and workload type
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### Phase 2: Detection Policies
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1. Create TracingPolicies for known attack patterns (container escape, privilege escalation)
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2. Configure event export to SIEM (Elasticsearch, Splunk, or Datadog)
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3. Build alerting rules based on TracingPolicy matches
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4. Validate detection accuracy with red team exercises
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### Phase 3: Enforcement
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1. Enable Sigkill actions for high-confidence threats (known malware binaries)
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2. Enable Override actions for dangerous syscalls in non-privileged containers
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3. Implement graduated response -- alert first, block after confirmation
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4. Monitor enforcement actions for false positives
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## TracingPolicy Development Workflow
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```
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1. Identify Threat -> Map to MITRE ATT&CK technique
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2. Determine Kernel Hook -> kprobe, tracepoint, or LSM hook
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3. Define Selectors -> Binary, namespace, capability filters
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4. Set Action -> Post (observe), Sigkill (block), Override (deny)
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5. Test in Staging -> Deploy to non-production namespace first
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6. Validate with Attack Simulation -> Confirm detection
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7. Deploy to Production -> Apply via GitOps
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8. Monitor False Positives -> Tune selectors as needed
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```
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## Incident Response Integration
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### When Tetragon Detects a Threat
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1. Event is generated with full context (pod, namespace, binary, args, capabilities)
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2. Event exported to SIEM via JSON log export or Prometheus metric
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3. SOAR platform receives alert and triggers playbook
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4. Automated actions: isolate pod network (via Cilium NetworkPolicy), capture forensic data
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5. Security team receives enriched alert with Kubernetes context
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### Forensic Data Collection
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```bash
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# Export recent events for a specific pod
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tetra getevents --namespace <ns> --pod <pod-name> \
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--since 1h -o json > /forensics/tetragon-events.json
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# Get process tree for suspicious activity
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tetra getevents --process-pid <pid> --ancestors 5 -o compact
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```
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## Operational Runbook
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### Daily Checks
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- Review `tetragon_missed_events_total` metric for event buffer overflows
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- Check Tetragon DaemonSet health across all nodes
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- Review new TracingPolicy match counts
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### Weekly Checks
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- Analyze top 10 most frequent event types
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- Review enforcement action logs for false positives
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- Update TracingPolicies based on new threat intelligence
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### Monthly Checks
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- Performance impact assessment (CPU/memory overhead per node)
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- TracingPolicy effectiveness review with red team
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- Update Tetragon to latest stable release
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