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Air-gapped / Local-LLM Mode

AiSOC can run entirely within your network perimeter with zero outbound LLM calls. The feature is controlled by a single environment variable and a companion Docker Compose overlay that wires in a local inference server (Ollama, LiteLLM, or vLLM).

Quick start (Ollama + Docker Compose)​

The easiest path is the pre-built air-gap overlay shipped in the repository:

docker compose \
  -f infra/compose/docker-compose.demo.yml \
  -f infra/compose/docker-compose.airgap.yml \
  up -d

What it does:

ComponentAction
ollama serviceStarts ollama/ollama:0.6.7 bound to 127.0.0.1:11434
ollama-pull init containerPulls the pinned model on first boot (cached on restart)
agents service overrideSets AISOC_AIRGAPPED=true, LLM_BASE_URL, LLM_MODEL, blanks external keys

The pinned default model is llama3.2:3b-instruct-q4_K_M (~2 GB). To use a larger model:

AIRGAP_LLM_MODEL=llama3.1:8b-instruct-q4_K_M \
docker compose -f infra/compose/docker-compose.demo.yml -f infra/compose/docker-compose.airgap.yml up -d

How air-gap enforcement works​

Setting AISOC_AIRGAPPED=true activates an allow-list check inside the LLM resolver (services/agents/app/security/llm_resolver.py). When a credential set is resolved:

  1. Local providers pass — any base URL containing ollama, vllm, or litellm (or mapped by the _HOSTED_SUBSTRINGS table) is classified as local and is always permitted.
  2. External providers are blocked — any credential pointing to a hosted API (api.openai.com, *.azure.com, generativelanguage.googleapis.com, etc.) raises AirgapViolationError before the HTTP call is made.
  3. Deterministic fallback — if no local LLM is configured either, the investigator's deterministic synthesizer fills all LLM response fields with canned, reproducible output so the demo seed and evaluation harness complete without errors.

Environment variables​

VariableDefaultDescription
AISOC_AIRGAPPEDfalseSet to true to enforce local-only LLM calls
LLM_BASE_URL(unset)OpenAI-compatible base URL of the local server (e.g. http://ollama:11434/v1)
LLM_API_KEY(unset)API key passed to the local server (Ollama ignores it; use any non-empty string)
LLM_MODEL(unset)Model name as understood by the local server (e.g. llama3.2:3b-instruct-q4_K_M)

Plugging in a different local inference server​

AISOC_AIRGAPPED=true
LLM_BASE_URL=http://ollama.internal:11434/v1
LLM_API_KEY=ollama
LLM_MODEL=llama3.1:70b-instruct-q4_K_M

LiteLLM proxy​

LiteLLM can front multiple local backends (Ollama, vLLM, GGUF servers) behind a single OpenAI-compatible endpoint:

AISOC_AIRGAPPED=true
LLM_BASE_URL=http://litellm.internal:4000
LLM_API_KEY=<litellm-master-key>
LLM_MODEL=ollama/llama3.1:70b-instruct

vLLM​

AISOC_AIRGAPPED=true
LLM_BASE_URL=http://vllm.internal:8000/v1
LLM_API_KEY=vllm-api-key
LLM_MODEL=meta-llama/Llama-3.1-70B-Instruct

Tenant-level overrides (BYOK under air-gap)​

Platform operators can allow individual tenants to bring their own local LLM credentials via Settings → Deployment & AI → LLM Provider. The UI exposes three local-provider options:

Provider labelInternal provider_type
Local Ollamalocal-ollama
Local LiteLLMlocal-litellm
Local vLLMlocal-vllm

When AISOC_AIRGAPPED=true, the resolver validates that the tenant-supplied base URL is classified as a local endpoint before allowing it. If a tenant tries to configure an external endpoint, the request is rejected with HTTP 422 and the error "airgap_violation".

Verifying air-gap compliance​

Call the LLM status endpoint after startup:

curl -s http://localhost:8000/api/v1/llm/status | jq .

A compliant response looks like:

{
  "provider_type": "local-ollama",
  "model": "llama3.2:3b-instruct-q4_K_M",
  "reachable": true,
  "airgap_compliant": true
}

airgap_compliant: false means the resolved provider would make external calls. Stop the stack, correct the environment variables, and restart.

Running the demo seed in air-gapped mode​

The demo seed script (scripts/demo_seed.py) seeds a reference incident and kicks off an investigation with "mode": "deterministic". In this mode:

  • Triage, hunt, and enrichment nodes use the local LLM for scoring if LLM_BASE_URL is set, otherwise they use pre-computed deterministic stubs.
  • All external connector calls remain in simulation mode (no live integrations are contacted).
  • Zero external LLM calls are made when AISOC_AIRGAPPED=true and the local server is healthy.
# With the air-gap overlay running:
docker exec aisoc-api python scripts/demo_seed.py

Expected output includes investigation_status: closed and no openai.com entries in the network logs.

Kubernetes / production deployment​

For production air-gapped clusters add these env vars to the agents Deployment:

env:
  - name: AISOC_AIRGAPPED
    value: "true"
  - name: LLM_BASE_URL
    value: "http://ollama.llm-infra.svc.cluster.local:11434/v1"
  - name: LLM_API_KEY
    valueFrom:
      secretKeyRef:
        name: airgap-llm-creds
        key: api-key
  - name: LLM_MODEL
    value: "llama3.1:70b-instruct-q4_K_M"
  # Blank external keys explicitly
  - name: OPENAI_API_KEY
    value: ""
  - name: ANTHROPIC_API_KEY
    value: ""

Use a Kubernetes NetworkPolicy to deny egress to api.openai.com and other external LLM endpoints as a defence-in-depth measure alongside the software enforcement.

Troubleshooting​

SymptomLikely causeFix
AirgapViolationError in logsLLM_BASE_URL points to an external hostCorrect LLM_BASE_URL to your local server
reachable: false in /api/v1/llm/statusLocal server not runningCheck docker compose ps and Ollama health
Model pull timeoutLarge model, slow diskUse a smaller quantised model or increase start_period
connection refused on port 11434Port binding conflictChange 127.0.0.1:11434 → a free port in the overlay