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# OpenUltraSAST
OpenUltraSAST is an experimental static security analyser. It is meant to be a safety net on
repositories it has never seen. It scans a checkout, or the commits a `git push` would publish. It
keeps what it can prove apart from what it only suspects. When a scan could not look at
something, it records a degradation. It does not report a clean result.
**State as of 2026-10-02 (v2.0.0):** the pre-push safety net is **NO-GO** for rollout.
No hook capability is enabled. No independent population (a case set frozen before any scan) has
passed the qualification gates (see [Evaluation](evaluation.md)).
## Three layers
| Layer | What it is | Where |
| --- | --- | --- |
| **Scanners** | `ousast scan` (`quick`, `standard`, `deep`) and `ousast pre-push`: language-scoped pattern rules, a Joern code property graph engine, verification and scoring. Deterministic in `quick`; no model is needed for a scan. | [Scanning](scanning.md), [Architecture](architecture.md) |
| **The agentic plane on ax** | Model-driven work over whole repositories, run as a DAG of tasks on google/ax, one isolated actor per task. What the runs learn is kept in a memory store. Maintainer surface: `ousast plane`. | [The plane on ax](plane.md), [Memory](memory.md) |
| **The decision engine** | A learned classifier that weighs every instrument's signals against similar labelled cases from memory. **In development, not adopted**: no scan, pre-push check or report uses it. Maintainer surface: `ousast learn`. | [Memory and detection](memory-and-detection.md), [Decision engine](decision-engine.md) |
A code property graph is a graph of the program's syntax, control flow and data flow. Joern builds
it.
## How they connect
```mermaid
flowchart LR
repo["Repository or push delta"] --> scan["Scanners: quick rules, Joern engine, verify, score"]
scan --> report["Report: findings with evidence, SARIF, score"]
scan -- "alerts on vulnerable and fixed pins" --> plane["Plane on ax: repo-facts, verify a/b/c, agree, features"]
plane -- "remember" --> mem[("Memory store: rows, facts, examples, blobs")]
mem -- "improve --memory: rule-status proposals" --> gate{"Validator and detection gate"}
gate -- "accepted round" --> ledger["Ruleset ledger: rule status"]
ledger --> scan
labels["Labels from ground truth"] --> mem
mem -- "retrieval of similar labelled cases" --> engine["Decision engine: compiled AI classifier"]
engine -. "intended, not adopted: BLOCK / ADVISORY" .-> report
```
- The **scanners** produce findings. Inside plane Runs, they also produce the `alerts` that become
memory rows.
- The **plane** runs model work per case: verify passes and roles. It also runs model-free
bookkeeping per case: facts, agreement and feature records. Its `remember` task turns a case's
artifacts into rows of the [memory store](memory.md).
- Memory feeds two consumers:
1. `ousast improve --memory` turns stored rows into rule-status proposals. They pass through the
same validator and gate as every other edit.
2. The decision engine retrieves labelled examples from the same store.
- The decision engine's output (dotted line) is the intended path. Nothing user-facing reads it
today.
## Where to go next
- The current state in one page, every figure with its record: [Where we stand](where-we-stand.md).
It covers capability against the M4 gates, the step-by-step approach, ax on the server, token
economics before and after, and the open items.
- Run a scan: [Examples](examples.md), and the commands in [Scanning](scanning.md).
- Understand a finding's evidence and score: [Architecture](architecture.md).
- The program analysis under a scan, what each representation can see and what it misses:
[Detection techniques](detection-techniques.md).
- Operate the plane and its store: [ax on this host](ops/ax/README.md) and
[RustFS setup](rustfs.md).
- Where the plane runs today, and what a separate Kubernetes cluster would take (planned, not
done): [Deployment](deployment.md).
- Where the model spend goes, per Task at runtime and in the maintainers' own coding sessions,
and what is reused instead of paid again: [Token ergonomics](token-ergonomics.md).
- Trust boundaries and hardening: [Threat model](threat-model.md).
Every number in these pages is quoted from a committed record. The record's path is given next to
the number.