Deterministic network threat hunting.
Zeek-first NDR research · local-first · authorized use.
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--- **Status: pre-release (initial version).** The project structure, documentation, CI, Zeek ingestion for `conn.log` and `dns.log`, DuckDB/Parquet analytical storage, and initial versions of detection pillars 1 to 4 are implemented and validated against public traffic. Automatic continuous ingestion and cross-restart alert persistence are planned for upcoming releases. Acauã is a network threat hunting engine built around deterministic evidence, not an opaque model. The goal is to answer not only "this looks suspicious" but "these exact inputs, with these intermediate values, produced this score". - **Deterministic by design:** fixed-order reductions, documented sentinels and a JSON evidence record for every future alert. - **Local-first:** the analytical store is embedded in the process; no external database and no telemetry by default. - **Zeek-first:** `dns.log`, `ssl.log`, `conn.log` and the protocol logs needed for identity and lateral-movement analysis. NetFlow/IPFIX is a documented degraded mode, never presented as equivalent. Suricata EVE JSON is an optional secondary input. - **Server daemon and web dashboard:** `acaua serve` runs continuous ingestion, scheduling, the API and the embedded web UI, distributed 100% via Docker. - **Research stays outside the product:** `research/` is an isolated Python workspace for scientific validation and fixtures. It is never compiled, packaged or released. ## What exists today | Area | State | |---|---| | Rust workspace and CLI (`acaua`) | ✅ functional | | Axum API with health, status, alerts and analyze routes | ✅ functional | | Embedded web dashboard | ✅ UI served by daemon | | Documentation and CI/release workflows | ✅ | | Docker multi-arch image and compose deployment | ✅ | | DuckDB analytical store | ✅ official prebuilt library linked | | Four detection pillars (P1–P4) | ✅ initial version | | Zeek log parser (`conn.log`, `dns.log`) | ✅ functional | | Alert evidence and scoring | ✅ deterministic JSON + noisy-OR fusion | | Published releases | ❌ none yet | ## The four pillars All four pillars are implemented in their **initial version (v1)** and validated against synthetic fixtures and public captures: 1. **Beaconing (Pilar 1 v1.2):** periodicity on event timestamps with a Rayleigh/Schuster periodogram bounded by the observed span, regularity significance gating, and infrastructure exclusions. 2. **Persistent sessions (Pilar 2 v1.0):** long TCP connections chained across Zeek inactivity timeouts (up to 3600s gap without new SYN), log-scale persistence score, and PCR/failed attempt tracking. 3. **Protocol anomalies (Pilar 3 v1.0):** deterministic information capacity (Shannon entropy $\times$ unique subdomain characters per UTC hour) in DNS queries to detect tunneling. 4. **Evidence fusion (Pilar 4 v1.0):** per-host weighted noisy-OR combination ($w_1=w_2=w_3=0.75$) with deterministic JSON evidence and ranking. The design decisions behind these pillars, including the six corrections to the original blueprint, are in **[docs/architecture.md](docs/architecture.md)**. ## Authorized use Acauã is defensive software for networks you own or are explicitly authorized to monitor. Capturing or analyzing third-party traffic without permission may be illegal. The operator is responsible for scope, privacy and retention. The daemon binds to `127.0.0.1` by default. The Docker Compose deployment isolates the daemon in an unprivileged, read-only container with dropped capabilities. ## Install Run via Docker Compose (recommended for operators): ```bash cp .env.example .env docker compose pull && docker compose up -d ``` Or build and run locally with Docker: ```bash docker compose up -d --build ``` To compile from source natively (Rust 1.88+ required): ```bash scripts/fetch-libduckdb.sh ~/.cache/acaua/duckdb export DUCKDB_LIB_DIR=~/.cache/acaua/duckdb LD_LIBRARY_PATH=~/.cache/acaua/duckdb cargo build --release -p acaua-cli ./target/release/acaua --help ``` Supported platform matrix for published container images: `linux/amd64` and `linux/arm64`. ## Getting started ```bash acaua doctor acaua serve --bind 127.0.0.1:8787 --data-dir .acaua acaua analyze /var/log/zeek/current --json acaua update ``` `analyze` currently validates the directory and returns a skeleton report; it does not parse Zeek logs yet. `serve` exposes the stub API and the embedded web UI. `update` checks for new versions and guides container image updates. ## Development ```bash scripts/fetch-libduckdb.sh ~/.cache/acaua/duckdb export DUCKDB_LIB_DIR=~/.cache/acaua/duckdb LD_LIBRARY_PATH=~/.cache/acaua/duckdb cargo test --workspace cargo clippy --workspace --all-targets node scripts/check-ui-i18n.mjs scripts/check.sh --full ``` See **[CONTRIBUTING.md](CONTRIBUTING.md)** and **[docs/architecture.md](docs/architecture.md)**. ## Known limits - The detection engine, Zeek parser and storage layer are stubs. - There is no published release image yet. - NetFlow/IPFIX is a degraded input mode by design; it cannot replace the Zeek protocol logs for every pillar. - The project targets Linux container environments (`linux/amd64`, `linux/arm64`). ## Where it's going Summary of the [ROADMAP](ROADMAP.md): | | | |---|---| | **Done** | Workspace, CLI/API stubs, web dashboard, Docker containerization, CI/release workflows | | **Next** | Pillar 1 and 2 implementations with deterministic fixtures; real Zeek parser | | **Later** | Full Parquet partitioning, TTL pruning, pillar 3 and 4, evidence fusion | | **Not planned** | Opaque AI scoring, a required cloud service, Python in the shipped runtime | ## License [MIT](LICENSE-MIT) or [Apache-2.0](LICENSE-APACHE), your choice.