nethesis-insights

Central log-anomaly analysis, threat-intelligence sharing and hardware sizing for NethServer fleets. Nodes ship deduplicated, masked log bundles; the server gates each one against novelty and deviation, calls an LLM only when the gate fires, and stores findings under a server-computed identity so the same problem is never raised twice.

Contents

• What runs
• Documentation
• Build and test
• Running a service locally
• Against a real model
• Container images
• License

What runs

Four services behind one Traefik proxy, in one podman pod.

Service	Does
authd	forward-auth cache. Traefik calls it before any pipeline sees a request; it validates the node's credential upstream and caches the outcome
insightsd	the log pipeline: ingest → queue → gate → LLM → fingerprinted findings, at /logs
threatd	Threat Shield: turns the fleet's CrowdSec ban decisions into a consensus IP blocklist served back to nodes, at /blocklist
sizingd	fleet sizing: scores each node's daily workload report and publishes cohort hardware baselines, at /sizing

Three independent pipelines, three SQLite databases, nothing shared between them but Traefik, authd and internal/platform. No LLM call, no gate and no fingerprint outside insightsd.

sizingd is a dev preview: the server side is complete, but the NS8 cluster reporter that would feed it does not exist yet, so it stores nothing on a fresh deployment.

Documentation

docs/admin-guide.md	Install, remove, configure, and operate a server. Every environment variable. What a finding, template, baseline and cohort are, in plain language. Start here.
docs/architecture.md	Package layout, request flow, storage, the gate and fingerprint formulas, and the rules that must not be broken. For changing the code.
docs/api/openapi.yaml	Every HTTP endpoint, at its public prefixed path.
docs/api/threat-events-ingest.md	Wire contract ns8-crowdsec builds against.
docs/api/sizing-ingest.md	Wire contract ns8-core builds against.
docs/todo.md	What is not built yet.

Build and test

make build          # one static binary per service into bin/
make test           # go test ./... -race -count=1
make check          # license headers + golangci-lint + tests

Or directly:

go build ./...
go vet ./...
go test ./... -race -count=1

go test ./internal/gate/ -run TestKnownSecurityTemplateAloneNoCall -v
go test ./internal/prompt/ -update      # regenerate prompt goldens

Running a service locally

DB_PATH=/tmp/insights.db UI_LISTEN_ADDR=127.0.0.1:9596 go run ./cmd/insightsd

curl -u <system_id>:<anything> -X POST localhost:9595/v1/bundles -d @bundle.json
curl -u <system_id>:<anything> 'localhost:9595/v1/findings?since=0'

This runs one service standalone, with no Traefik and no authd in front of it, so it answers on its own unprefixed routes. Any password works: the credential is checked by authd in a real deployment, and a standalone service only checks that the request came from TRUSTED_PROXY_CIDRS (default 127.0.0.0/8, which already covers a local curl) before reading the system_id off the Basic username. Calling it from another machine needs that setting widened — see the admin guide's Authentication section for what that grants.

UI_LISTEN_ADDR turns on the operator dashboard, which is the fastest way to see what the server actually stored — findings, the cost ledger with its gate reasons, templates, baselines, queue depth and the effective configuration.

scripts/insights-api.sh wraps the same calls for all three pipelines (health, findings, open, post <bundle.json>, events, feed, allowlist-request, raw <path>).

Threat Shield, with the promotion rule relaxed to a single reporter:

BLOCKLIST_MIN_SYSTEMS=1 BLOCKLIST_CONSENSUS_INTERVAL=10s \
UI_LISTEN_ADDR=127.0.0.1:9606 DB_PATH=/tmp/threat.db go run ./cmd/threatd

The edge collector, without installing the module

The collector script runs standalone on any NS8 node:

runagent -m loki
cd ../bin
curl -o insights-collector https://raw.githubusercontent.com/NethServer/ns8-loki/refs/heads/anomaly_detector/imageroot/bin/insights-collector
INSIGHTS_SERVER_URL=https://<host> python3 insights-collector

INSIGHTS_SERVER_URL is the only required variable, and it takes the bare server root — the collector appends /logs/v1/bundles itself. On success it prints what it shipped:

shipped 76 templates, 332 lines -> 202 {"accepted":true}

Against a real model

Any OpenAI-compatible provider works with no code change:

LLM_BASE_URL=https://openrouter.ai/api/v1 \
LLM_MODEL=nvidia/nemotron-3-ultra-550b-a55b:free \
LLM_API_KEY=<key> DB_PATH=/tmp/insights.db \
  go run ./cmd/insightsd

Two things to know before assuming a bug on a free tier:

• It is slow, not hung. Some providers return headers immediately and the body only when generation finishes, commonly ~105 s later. LLM_TIMEOUT (default 120s) and ANALYSIS_TIMEOUT (default 5m) are already sized for this — do not lower them. Ingest answers 202 immediately regardless, so the delay is invisible at the HTTP layer; watch LOG_LEVEL=debug or poll /v1/findings.
• A free tier rate-limits and goes away. Treat a provider error as a reason to retry later, not as a regression.

Container images

One Containerfile builds all four binaries, selected by a SERVICE build argument. CI publishes each as its own public multi-arch (linux/amd64, linux/arm64) image on every push to main and every tag:

ghcr.io/nethesis/nethesis-insights-authd:latest
ghcr.io/nethesis/nethesis-insights-insightsd:latest
ghcr.io/nethesis/nethesis-insights-threatd:latest
ghcr.io/nethesis/nethesis-insights-sizingd:latest

Every binary is static (CGO_ENABLED=0, modernc.org/sqlite) and runs as uid 1001. Build one locally with:

podman build --build-arg SERVICE=threatd -t nethesis-insights-threatd .

To deploy, see the admin guide — the quadlet units and proxy templates are in deploy/.

License

GPL-3.0-or-later. See LICENSE.