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The plane's memory store no longer names one vendor. `MinioStore`/`SdkClient`/ `minio_settings`/`MINIO_KEYS` become `S3Store`/`S3Client`/`s3_settings`/`S3_KEYS`; the URL scheme is `s3://<bucket>[/<prefix>]` (`s3://` alone uses `S3_BUCKET`); the settings are `S3_ENDPOINT` (a full URL), `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, optional `AWS_SESSION_TOKEN` and `S3_REGION`. The client is boto3 (extra `s3`, imported lazily): SigV4, path-style addressing, SDK checksum trailers off, paginated listing, versions and delete markers listed and deleted by version (`purge`, used by the contract tests' teardown so the bucket keeps nothing of a run). Behaviour is unchanged: the store never configures its bucket and verifies versioning, the `runs/` expiry rule, S3 Select and tag reads at startup; no local fallback; every row carries every queryable field with "" placeholders. The admin hints read `--endpoint-url "$S3_ENDPOINT"`. The fake client still reproduces RustFS's two Select failures (unbound leading-row field, null-typed column). Docs: rustfs.md stays the tested server's setup page (policy JSON unchanged, env names updated, any S3-compatible store with versioning, lifecycle, tags and Select works); memory.md, ops/ax/README.md, README.md, steering and the two current spec designs use the S3 naming. Retired specs and committed measurements are untouched. Real server (RustFS, OUSAST_MEMORY_TEST_S3=1): test_plane_memory + test_learn_compile 75 passed, 1 skipped. Store copy of the live local store to a temporary prefix: every count matched (776 row objects, 2982 rows, 22 facts, 788 excerpts, 2601 responses, 2 programs, 1793 index entries), 4190 versions purged afterwards. Co-Authored-By: Claude Fable 5.1 <[email protected]> Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
220 lines
14 KiB
Markdown
220 lines
14 KiB
Markdown
# Overview — what this is, and what is actually true of it
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## Current state, 2026-10-02
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Everything below this section is dated history; where it disagrees with this section, this section wins.
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User-facing documentation: `README.md`, `docs/architecture.md`, `docs/evaluation.md`, `docs/decision-engine.md`,
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`ops/ax/README.md`.
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- **Scanning.** `ousast scan --mode quick|standard|deep`. Quick rules for C/C++, Python, JavaScript/TypeScript,
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Java/Groovy and PHP (PHP numbers are in-sample only: `benchmarks/measurements/2026-09-30-php-quick-rules/`).
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Standard adds the MAP stage with the Joern model layer (shipped in the Docker image); deep adds sandboxed
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regression snippets when Docker is available. Framework knowledge is tagged as optional priors
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(`ruleset/frameworks.toml`, `priors=`). `ousast pre-push` compares head against base; the capability registry
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is empty, rollout NO-GO.
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- **Agentic plane.** google/ax over Agent Substrate on kind is the only executor of model work over whole
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repositories (`ousast plane run|status|doctor|workspaces|remember|alerts-engine|harvest`). Credentials travel
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only in the start request through `atenet-router`; egress is per task; budgets are per task; rows go to the
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memory store (`OUSAST_MEMORY`: FileStore, or S3Store on an S3-compatible bucket; RustFS is the tested server).
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- **Removed.** HarnessX (retired 2026-09-30): its config keys fail, a `[harnessx]` section warns. The LLM judge
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of the verifier and the LLM fusion panels are gone; fusion is deterministic.
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- **Improvement.** `ousast improve --memory` proposes rule-status edits from plane memory through the unchanged
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validator and gate; the loop also runs as a plane Run.
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- **Decision engine** (`learned-decision-engine`, implementation, not adopted). First slice, injection only:
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ADVISORY recall 0.90, precision 0.54, BLOCK not offered
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(`benchmarks/measurements/2026-10-01-decision-engine-injection-slice/record.json`).
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- **Evaluation.** Populations v1 and v2 are spent and failed every M4 gate (`benchmarks/independent/results-v1.json`,
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`results-v2.json`); v3 (PHP) is frozen and untouched for the one-time final check. The plane increment met its
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gate on the second measurement with a tie-break chosen after the first (`benchmarks/independent/plane-increment-2.json`).
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- **Providers.** DeepSeek for LLM calls, OpenRouter only for OpenAI embeddings; keys in `.env`, which never
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overrides an exported shell variable.
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## History
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**Direction, 2026-09-12:** an actionable pre-push security safety net for AI-accelerated
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development across supported ecosystems. See `safety-net.md` and the approved `pre-push-safety-net`
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spec. The ranker remains the scope mechanism; third-party vendor code stays outside targets and
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graphs. Advisory must meet the same actionability bar as blocking.
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**Historical scoreboard below:** it was written September 9. Later commits record a completing
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whole-PMPro scan and Joern 4.0.625 ranking measurements (82/91/54 on the three plugins), while
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default installation pins are now aligned to 4.0.625 with verified PHP/JavaScript image smoke.
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The pre-push workflow, changed-code latency and actionable
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precision are not demonstrated by those results. In particular, the manually selected two-file
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slice below is a useful experiment, not evidence that an automatic push scope would select the
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same context. Current scope/status corrections live in `flow-aware-ranking/brief.md` and the roadmap.
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The new scoring instrument retains missing targets and unanswered queries. Historical rank positions
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do not establish detection recall; VAmPI's old budget of 16 omitted its unmatched SQLI target. The
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corrected positional run keeps that target unresolved. Labeled PMPro/Node inputs and a frozen
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diagnostic profile are committed; independent capability evaluation is still required.
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**Written 2026-09-09.** Fourteen specs have accumulated and the roadmap still described a pre-Joern world, so
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this is the synthesis above them: what the system does, what has been measured, and what is not true yet.
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Every number here comes from a committed artifact in `benchmarks/measurements/`.
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## What the tool is
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A static analyser that separates **what it can prove from what it merely suspects**, and says which is which.
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The thesis is not the dataflow engine — CodeQL and Semgrep have one and developers do not turn it on. It is
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the **rung**: a claim you can act on without writing a query, and an explicit admission when the engine could
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not decide.
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```
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execution_confirmed a test or sandbox reproduced it (built, no production caller)
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model_entailed the graph decided: a flow with no discharge,
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an obligation with no guard, a permissive value ← the product
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model_corroborated the graph found the shape; a judge with
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coverage agreed on the residual question
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suspicion an enumerator or a pattern proposed it and
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nothing corroborated it ← everything below the line is noise
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until proven otherwise
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```
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Silence is not a clean bill of health. If no fact table covers a site, the model is **silent, not negative** —
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23 of the 39 misses in the original entailment ceiling were sinks simply absent from the tables.
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## How it works, in one pass
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```
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preprocess ─▶ entry-point map ─▶ MAP stage ─┬─ static patterns
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├─ semantic overlay
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├─ obligations (absence bugs)
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├─ tool hunter (LLM)
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└─ MODEL LAYER ──▶ one CPG per repository (Joern, subprocess)
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├─ taint reachability + sanitizer lattice
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├─ dominance guard governs obligated operation
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└─ config constant abstraction over a value
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```
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Three abstractions, one arbiter each, dispatched on spec type so a family without an arbiter cannot be
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silently routed to the wrong one. The CPG is built **once per scan** and every question is batched into one
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invocation per query kind.
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## What has been measured
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| | measured | source |
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|---|---|---|
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| entailment, flat IR → CPG | 2.2% → **41.3%** of the corpus | `2026-09-08-model-entailment-ceiling*.json` |
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| vibe-py pairs (30) | **90.0% pair-correct**, 6.7% leak, $0.0068 | `2026-09-08-pipeline-vibe-py.json` |
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| — against the LLM hunter | 76.7% / 12.3% at 5× the calls, ~100× the cost | same |
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| vampi (python, 520 lines) | **3 of 3** known vulnerabilities at `model_entailed` | `2026-09-09-repo-vampi-authz-precision.json` |
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| vampi access-control precision | 28.6% → **50.0%** | same |
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| access-control leak, pairs nobody tuned against | 42.9% → **0.0%**, pair-correct unchanged | same |
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| libpng envelope (89k lines of C) | build 16s, query 250s, scan 446s, **911 MB** | `2026-09-09-repo-libpng-envelope.json` |
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| libpng valid findings | **zero** | same |
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| report proportionality | libpng 198 sections → **39** | `2026-09-09-report-proportionality.json` |
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| **CVE-2023-23488, production plugin code** | **found at `class.memberorder.php:936`**, the exact line | `2026-09-09-pmpro-cve-found.json` |
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| — precision on that file | 16 of 26 unprepared `$wpdb` queries; **0 of 26 use `->prepare`** | same |
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## What is not true yet
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- **The C story does not work.** `c/memory` has produced zero true positives and three distinct classes of
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false one. It models string functions; libpng overflows through arithmetic, and its library code never
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calls a sink we model. This is structural, not tuning.
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- **Two languages are demonstrated.** Python end to end, and PHP on a real plugin slice where it found a
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real CVE. Ruby and Go still have **zero families** — Joern parses them and the engine says nothing.
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- **Not at repository scale for PHP.** The 637-file checkout does not load; the 2-file slice does. That
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boundary is unmeasured (task 5.10).
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- **The suspicion band is still too loud.** vampi emits 61 report sections for a 520-line application, 38 of
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them a candidate the graph could not decide with a judge's opinion attached.
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- **The evidence base is two repositories.** One has never produced a true positive.
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- **Control dependence is unavailable.** 0 of 13,184 calls in the libpng CPG and 0 of 1,152 in vampi's have a
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controlling control structure, so every guard question runs on CFG dominance instead.
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- **`execution_confirmed` has no production caller.** The rung exists and nothing reaches it.
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## What scoping is for, which is not what it looks like
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The first real CVE was found by **cutting**, not by scanning more. Two of Paid Memberships Pro's 637 files —
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the ones holding both ends of the bug — load in 9 seconds, query in 111, and report CVE-2023-23488 at the
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exact line. The full checkout does not load at all.
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That two-file slice **is the contributor case**. A developer editing `class.memberorder.php` gets precisely
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that scan. So scoping is not a workaround for a scale problem; it is the thesis, and the scale problem is
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what happens when the thesis is ignored.
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The distinction that matters is not whether to cut but **who decides and whether the decision is recorded**:
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| | decided by | recoverable afterwards |
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| --- | --- | --- |
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| **scoping** — a build declaration, a diff, a subtree | the project or the developer | yes, and it is in the artifact |
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| **triage** — "this looks like boilerplate" | a model | no; if it drops the file with the bug, the scan reports clean |
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Both give the same answer when the model is right. Only one of them tells you when it was wrong, and every
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failure found on this checkout was of exactly that shape.
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## Why a corpus of benchmarks is not enough on its own
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This is the finding worth teaching, and it is not an opinion — it is what the gates say.
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**Twelve engine defects were found in one session by pointing the tool at three real repositories. The three
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gates stayed byte-identical through every single fix.** A gate that does not move is a corpus that could not
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see the bug.
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| defect | what the corpus saw |
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| `resolve` matched inside `resolveUrl` (sanitizers) | nothing |
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| `user` matched inside `users` (dischargers) | nothing |
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| `gets` matched inside `fgets` (sinks) — 26 identical false positives | nothing |
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| the model layer had zero production callers | nothing |
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| `query_batch` implemented, tested, unreachable | nothing |
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| a paid budget halting unpaid arbitration | nothing |
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| a region with no function claiming the whole repository's answer | nothing |
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| a guard discharging an obligation it is not a guard of | nothing |
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| `joern-parse` failing where the frontend succeeds | nothing |
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| a 1.49MB batch over Linux's 128KB argv cap | nothing |
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| an array callable not recognised as a handler | nothing |
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| one defect reported as twenty-six findings | nothing |
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The reason is structural rather than a gap in the corpus's coverage. **A pair is a labelled function with a
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declared family and a known answer.** It cannot exercise: which region to look at, what to spend, whether the
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capability is even reachable, whether two entry points share a sink, whether the question fits in an argv
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slot, or whether a flow crosses a module boundary. Every one of those is a property of a *repository*, and
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none of them is a property of a function.
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Three of the twelve are worse than invisible — they are **quiet failures**, where the tool produced a clean
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report and every honesty counter agreed with it. The rung ladder labels a *verdict*; when no verdict is
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produced there is nothing to label. That is the failure mode a benchmark score cannot express at all, because
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the score is computed from the verdicts that exist.
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So the corpus is necessary and not sufficient: it is the **holdout** that stops per-repository tuning, and it
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is the wrong instrument for finding out whether the tool works. Both instruments, or neither number means
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anything.
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## The lesson that shaped the current specs
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Nine engine defects were found in one session by pointing the tool at two real repositories. **Three were the
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same bug in three matchers** — a spec token matched as a substring: `resolve` in `resolveUrl`, `user` in
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`users`, `gets` in `fgets`. Two were a capability built and unreachable: the model layer itself, then the
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query batcher. One was a paid budget stopping unpaid work.
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The three gates stayed **byte-identical through every one of those fixes**. That is the finding: a corpus of
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function-level pairs could not see any of them, and a repository showed all nine within minutes.
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## Where the specs stand
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Counted 2026-10-02 from each spec's `tasks.md` checkboxes and `spec.json`.
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| spec | phase | state |
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| `learned-decision-engine` | implementation | 11 of 17 tasks done |
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| `pre-push-safety-net` | implementation | 67 of 79 tasks done |
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| `contributor-scan` | implementation | 27 of 51 tasks done |
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| `ai-service-plane` | implementation | 11 of 11 tasks done; the ax plane is the agentic path |
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| `harnessx-removal` | complete | 8 of 8; HarnessX removed 2026-09-30 |
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| `finding-feedback-loop` | design | requirements approved, design awaiting approval |
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| `model-grounded-detection` | complete | 16 of 16; built the arbiter this all rests on |
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| `authorization-obligations` | dormant | tasks approved, 0 of 24 started; superseded in practice by the dominance arbiter |
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| `reachability-flow-model` | dormant | 23 tasks generated, nothing approved; largely delivered by adopting Joern |
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| `flow-aware-ranking`, `zero-with-a-reason`, `ir-consolidation` | dormant | brief only, unapproved |
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| four others | complete | `pair-corpus-honesty`, `corpus-seeded-mechanisms`, `propose-adjudicate-prove`, `tree-sitter-overlay-extra` |
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| six others | retired or superseded | `openrouter-sast-harness`, `three-stage-scan`, `harnessx-self-improving-rulesets`, `learning-harness` (retired with HarnessX), `constrained-detector`, `real-world-vfc-slice` (superseded) |
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> **Retired 2026-09-30:** HarnessX was removed by `harnessx-removal`; the agentic plane is ax (`ai-service-plane`),
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> and evolutionary proposals come from the plane memory. The HarnessX specs in the table above are history.
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As of 2026-09-09: 97 source modules, 90 load-bearing and 7 standalone capabilities; 814 tests.
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150 source modules, 145 load-bearing and 5 standalone capabilities, 0 orphaned
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(`benchmarks/measurements/2026-09-08-module-audit.json`, regenerated 2026-10-02); 1,964 tests collected.
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