AiSOC is an open-source, AI-assisted Security Operations Center: telemetry comes in from your own security tools, gets normalized, matched against a detection corpus, correlated into alerts, triaged by an agent, and acted on through governed response verbs. It runs on your own infrastructure — cloud or on-premises — under the MIT license.

This file is for anyone changing the code, human or AI. It is the short version; each section points at the thing that is authoritative. If this file and the tree disagree, the tree is right and this file is a bug.

make up        # CORE profile: 16 long-running services, ~8 GB memory, ~20 GB disk
make doctor    # what is up, what is not, and what to do about it
make smoke     # the golden pipeline, eight stages, end to end

make up generates real secrets into .env, creates an administrator and prints its password once. There is no step where you hand-edit a compose file. make up-full adds the rest (21 services, ~12 GB) and switches on the lake writer and the entity graph.

A first run shows real data with no credentials configured: the CISA Known Exploited Vulnerabilities catalogue is a genuine public feed that needs no API key, and a small local model does the triage.

One event's journey, which is the thing worth understanding first:

connector  →  services/ingest  →  Kafka raw_events  →  services/fusion  →  Postgres alerts
  polls a      normalizes to       the spine            archives to the       + services/realtime
  vendor       OCSF, projects                           lake, matches         pushes to the console
  API          actor/action/                            detections,           ↓
               resource/location                        correlates,        services/agents
                                                        promotes           triages with an LLM
                                                                              ↓
                                                                        services/actions
                                                                        executes a governed verb

Each hop is a service in services/. The stores are Postgres (operational), ClickHouse (the event lake), Neo4j (the entity graph), Qdrant (vectors), Redis and Kafka.

Fuller treatment: docs/architecture/README.md and the architecture page on the docs site.

• detections/*.yaml is generated output. The engine loads services/fusion/app/data/detection_ruleset.json, compiled from Python spec modules. Editing the YAML changes nothing that runs.
• The severity ladder is exactly five tiers — info | low | medium | high | critical. A vendor that publishes a distinct critical must map to critical, never be collapsed into high. Confidence is a separate 0–100 integer and is not severity.
• A connector's normalized envelope nests the vendor payload under raw_event, not raw. Twenty-six connectors once used raw, missed the canonical-envelope check, and were silently misattributed and never promoted.
• A new connector needs one registration, in _CONNECTOR_CLASSES in services/connectors/app/connectors/__init__.py. Everything else is discovery.
• The tenant is never a parameter a caller or a model can set. It comes from the authenticated principal, or for service-to-service calls from a header. Three gates enforce this.
• Secrets in connector config are vault-encrypted at the application layer; services/api owns the write path.

Never copy a number out of prose — it goes stale silently and several have. Each of these regenerates:

"Executable" means the rule was replayed through its real connector and the real engine and watched to fire. It is not a claim that the rule detects an attack, and that distinction is deliberate.

main is protected: a pull request plus a set of required status checks. The checks are not decoration — most of them exist because something shipped broken in exactly the way they now prevent.

Before you push:

ruff check services/ scripts/ tests/ tools/ && ruff format --check .
python3 scripts/check_mypy_baseline.py

ruff is pinned (>=0.16.8,<0.17) and the version is the behaviour — a different one reformats files CI never asked for. Install the pin into a throwaway virtualenv rather than using whatever is on your PATH. Build a per-service environment from that service's own locked set with python3 scripts/service_requirements.py <service> --locked, and do not install anything else into it: adding one package has already moved a dependency off the lock and changed a generated artefact.

Three things, in order, and the middle one is not the hard part:

1. A test that fails on the current tree for the stated reason — through the real transport, the real app with its real dependencies, and a real database.
2. The fix.
3. A negative control: revert the fix, watch the test fail again.

A passing test on a function nothing calls is indistinguishable from a working feature. This repository has found that shape dozens of times, which is why scripts/check_module_reachability.py exists.

• No attribution to any tool, AI assistant, editor or vendor for the work — not in code, comments, documentation, commit messages, trailers or pull request bodies. scripts/check_attribution.py enforces it.
• No competitor product named outside an integration surface. Where one is the benchmark for a comparison, refer to it neutrally and keep the analysis. scripts/check_competitor_names.py enforces it; scripts/competitor_names.toml holds the integration allow-list.
• Never present fabricated data as real. Seeded or sample data is gated behind demo mode; everywhere else shows an honest empty, zero or error state. A measurement nobody took reads "not measured", never 0.
• Never raise a scanner ceiling to make a scan pass. Find the finding and fix it.
• Do not edit anything under plans/.
• Fetch every URL before you commit it and require a 200. A link that 404s is worse than no link: delete it and rewrite the sentence.

Everything above applies. Four things specific to you:

• Read before you assert. Several claims in this repository were wrong in both directions at different times — recorded as present when absent, then as absent after they had been written. Check the file is on disk and read past its rationale; a module docstring often opens by describing the problem it fixed, which is not a description of the current state.
• Prefer testing the path over the function. The most productive defect class here is a test double more capable than the real thing: a fake store that answers any query, a mock that bypasses the transport.
• Say what you could not verify. "I could not check X, and here is why" is worth more than an implied pass.
• Nothing in this repository can make a third-party AI tool reach for AiSOC by default. That comes from publishing the packages and listing the MCP server in a registry, which is tracked work, not a documentation change.

Machine-readable summaries live at llms.txt and llms-full.txt. Both are generated by scripts/generate_llms_txt.py — change the generator, never the output.

AiSOC's development is funded and supported by Cyble.