The standard scan now runs run_hunter_pool, verify_findings and the
deterministic fuse_findings directly; the HarnessX hunter orchestrator,
the LLM judge dispatcher (verify_judge.py, deleted with its test) and the
LLM fusion panels are gone, and so are their extra-absent degradations.
host_under_harnessx is dropped from stage_processors.
config: [models] verifier and [fusion] panel_model/decider_model raise
RetiredConfigError naming the plane replacement (the CLI prints it and
exits 2); a [harnessx] section loads with one warning and is otherwise
ignored. harness.json keeps "verifier": null. Tests that asserted the
fallback are renamed to the behaviour they assert; the module-audit
manifest drops verify_judge. Nothing outside the two modules deleted in
task 6 imports harness_ext or hunter_harness.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
`ousast plane workspaces --validation-set ... --loop` appends the loop to a Run:
per case `alerts` (plane/tasks/alerts.py: the quick-mode scan on the vulnerable
and the fixed pin, a fixed-pin Workspace per case, alerts attributed to their
enclosing function by the repo-facts patterns, `in_fix_range` from the fix's
old-side and new-side ranges, failing on an unread tree) feeding `remember`,
then `memory-snapshot` -> `loop-measure` -> `loop-propose` -> `loop-improve`
(plane/tasks/loop.py). Every new task binds no Model and has budget
{usd: 0, calls: 0}. The snapshot is the store's rows after the train-on-test
guard, written on the host by memory.seed (a sandboxed run of it fails loudly);
propose runs M1/M2 against this repository at the commit under test; improve
runs one unchanged evolve.run_round and delivers gate.json, journal.json, the
sidecar, rule_policy.json only when accepted, and proposal_outcome rows that
the host ingests. Adoption stays a maintainer commit.
`remember` is now a Run entry per case (the image contains it), with the facts
row keyed by the image the facts were computed on (repo-facts records it in
its summary; unknown -> the row is omitted, never guessed). Alert rows carry
their own pin; improve/memory.py counts a repeated alert once.
Runner image rebuilt (+0.39 MB: only the new modules; the quick scan needs no
extra and the rulesets were already in the package), pushed, plane/ re-pinned
and regenerated (validation-46: 105 entries). Fixture test runs the whole loop
graph through the fake ax, whose new `exec` mode runs the real task modules.
Live: one loop Run over three validation-46 cases on the local ax, recorded in
benchmarks/measurements/2026-09-30-harnessx-removal-loop/ (all done, $0 new
spend, 0 proposals, gate verdict no_proposals).
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
improve/memory.py: rules M1 (enabled->shadow on repeated false alerts across
>=2 repositories, no agreed or site_match hit) and M2 (shadow->enabled on
>=2 agreed declared sites no enabled rule catches); M3 disputed families are
advisory (signals.json) and never reach the validator. The train-on-test
guard drops rows of --qualify-population, gated benchmark cases and holdout
pair repositories before any rule sees a row. run_round(proposals=...) adds
memory edits after the benchmark's through the unchanged validator and gate;
provenance (row ids, object keys and versions, counts, exclusions, index
digest) goes to memory_proposals.jsonl and the journal's evidence field;
proposal_outcome rows are written back after a non-dry run.
ousast improve --memory is opt-in; default improve output is byte-identical
to the task-1 baseline.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
plane/memory.py: the MemoryStore interface with FileStore (index.jsonl, facts by
content hash, repos/<host>__<owner>__<name>/<pin>.jsonl, idempotent ingest,
deterministic row ids, refusal below 1 GiB free naming the path) and MinioStore
(object metadata and tags, S3 Select pushdown probed once per process with a
logged local fallback, object version ids on every row read, versioning and
runs/ lifecycle helper, presigned URLs). OUSAST_MEMORY selects the backend;
MINIO_* settings come from .env; the minio SDK is the optional extra `minio`.
plane/tasks/remember.py: model-free rows (facts, verdict, unit_cost, alert)
from a case's artifacts; remember_run computes them on the host for a recorded
run without writing into it. reconciler.mark_done (477 lines total), seed
before and ingest after `ousast plane run`, `ousast plane remember <run>`.
The generator annotates each repo-facts Task with openultrasast.io/memory-key
(repo, pin, candidates digest, image digest) and the Run with its population
and split; plane/ regenerated.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Equality script (design section 3) records suite outcomes, `ousast pairs --json`,
the python-vulnerable quick benchmark, one standard scan and `improve --dry-run`
from a frozen export with the harnessx extra absent and no model reachable.
Two independent records are byte-identical (determinism.json).
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Maintainer: use MinIO features including its JSON support; a server exists.
One MemoryStore interface with FileStore (laptop, tests) and MinioStore (the
store of record for the separate Kubernetes deployment): tags for indexing,
S3 Select pushed-down queries probed with a local fallback, versioning for
proposal provenance, lifecycle for raw outputs, presigned URLs and bucket
notifications kept for the follow-on that removes the host receiver.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Maintainer amendment: no HarnessX path stays, optional or not; the plane memory
layer replaces the HarnessX evolution proposer and carries loop engineering
(Requirement 6: persistent run memory, proposals from it through the existing
validator and gate, the loop as a plane Run, provenance per proposal).
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The ai-service-plane increment met its gate on ax (plane-increment-2.json), the
condition for removing HarnessX. Requirements: an explicit fate per capability
(moved to a plane task or retired), code/packaging/tests removed, deterministic
outputs proven byte-identical against a recorded baseline, docs and specs
retold, one reviewable sequence. Brief inventory re-verified.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
A third verify pass on the 10 disputed candidates, 2-of-3 agreement (Req 6.4),
run on ax by extending the same Run: 16/20 declared sites agreed (reference 16),
$0.0205 per candidate with recorded triage (reference $0.022). Caveats recorded:
a design change on the same set; 17 vs 19 sites flagged in any pass; three
non-declared pgadmin candidates promoted.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The design revisit after plane-increment-1.json (14/20 agreed, 19/20 in either
pass): a third verify pass on the candidates passes a and b dispute, and agree
decides 2-of-3 where pass c asked (the a/b rule elsewhere; c alone never decides).
- verify: optional OUSAST_INPUT_ONLY restricts the hunt to the named candidates
(agree's disputed.json); an empty list is done with 0 units and no model client.
- agree: optional OUSAST_INPUT_PASS_C; metrics keep every key and add tiebreak
{asked, flipped_to_agreed, flipped_to_rejected, rule}; usd_total, hunts and
declared-site metrics are on the final decision.
- generate: per case <case>-vc and <case>-final appended to validation-46; the
first 60 entries stay byte-identical, so a rerun keeps their done state.
- Offline replay over the recorded outputs with an empty pass c reproduces the
recorded agree summaries exactly (14/20 agreed, 23 agreed, 10 disputed).
- Spec: Requirement 6.4, design Measurement, task 8.1.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
validation-46 ran done on google/ax: 60 tasks, 357 DeepSeek calls, $0.83 with
recorded triage ($0.0194 per candidate, reference $0.022: cost met). Declared
sites agreed 14/20 against the reference's 16/20: recall criterion not met.
Both runs find 19/20 sites in at least one pass; the two-pass agreement
flicker moved three sites. Design revisit before task 9.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
A producer's artifact rendered as spec.files of a generated <task>-inputs
Workspace ends up in ax's AX_WORKSPACES_YAML env value; Agent Substrate
rejects values over 32768 characters, so a 182 KB facts.json broke ax apply
on the live cluster. The reconciler now passes OUSAST_INPUTS instead, the
receiver serves a running task its declared inputs over GET /inputs/..., and
the runner fetches them after the start (failed fetch -> failed summary).
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The end-to-end smoke Run finished done on the local ax: submit, egress policy,
resume, router start, repo-facts in gVisor, artifacts delivered through the
egress gateway, attribution table printed, task and policy cleaned up.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Agent Substrate's egress gateway denies an actor without an EgressPolicy, so
no task could deliver its artifacts or reach a model. egress.py grants each
task exactly: http/80 to ousast-receiver.ax-system.svc.cluster.local, and
TLS passthrough/443 to the bound Workspaces' https Git hosts and the bound
Model's openultrasast.io/egress-hosts (api.deepseek.com for deepseek-flash).
No IPs, no wildcards, no https (MITM) rules.
The reconciler writes the policy with kubectl-ate between ax apply and
resume, reads it back, waits OUSAST_EGRESS_SETTLE (11 s, the gateway's
cached deny), and after ax delete task confirms the policy went with its
actor (kubectl-ate has no delete verb; the store cascades).
The receiver is a selector-less Service (ops/ax/receiver-service.yaml.tmpl,
applied by up.sh together with the no-build agentgateway egress gateway)
on port 18090 of the host. Measured live: the gateway checks the policy on
Host but connects to the address the actor dialled, so the runner dials the
Service's ClusterIP (OUSAST_ARTIFACT_DIAL) with the receiver's name as Host.
The runner now labels its delivery with the Run's task name (OUSAST_TASK),
which is what the receiver accepts; the ax Task name was refused with 403.
The Receiver moved to egress.py to keep reconciler.py at 460 lines.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
agree matched declared sites through benchmarks/independent/evaluate.py,
which the runner image does not carry, so site matching would have been
"not assessed". The generator now resolves the fix's old-side ranges
(evaluate.hunks, line for line) into case.json, with the declared sites in
the set and the reference's cost, and agree.matches_declared reproduces
matches_v2; a parity test runs both over the recorded outputs of the 15
validation cases (200 probes, identical verdicts) and agree on those outputs
returns the reference's 16 of 20 and $0.022.
agree reports cost_per_candidate (plane spend) and
cost_per_candidate_with_recorded_triage; Requirement 6.2 is judged on the
latter (design.md). --runner-image re-pins the templates from ops/ax/up.sh's
pin file; the committed manifests are regenerated at the current digest.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Agent Substrate's golden-snapshot boot runs the same image with the same task env,
so the runner no longer starts its command by itself: after the workspaces are
ready it waits for POST /ousast/v1/start (run/task checked, once per boot, refused
after a delivered run). The reconciler sends it through svc/atenet-router with
ate-target-actor, which never addresses the golden actor (plane/router.py), and the
bound Model's secretKey variable travels only in that body, into the child's env.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The live cluster ran the task command twice: in the actor and in Substrate's
golden-snapshot boot, which gets the same image and task env. Requirement 4.5
gates the command on a router-addressed start request; 4.6 carries provider
credentials only in that request.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The first live run on the local ax cluster and ax's source (docs/runner.md,
docs/sandbox.md, internal/controller/reconciler.go, internal/server/server.go)
showed a lifecycle the task-3/4 code did not model:
- `ax apply` creates a Task Suspended (Ready=False, TaskSuspended); it runs only
after `ax resume task`. The first resume of a new image can fail with
DeadlineExceeded while Agent Substrate builds the golden snapshot, and ax's
server then stores phase Failed; a later resume succeeds.
- ax has no Completed phase and never reads a command's exit back.
- The runner is PID 1 and must keep serving after the command exits; stop and
suspend deliver SIGTERM, to be forwarded to the command's process group.
Our runner imported the task in-process and exited, which stopped the
container ("Container guest is stopped") and made every resume time out.
- ax's controller probes /readyz?check=workspace; the query string made our
handler answer 404.
Runner (Req 4.1-4.4): spec.command runs as a child
`python -m openultrasast.plane.tasks.<name>` in its own process group, cwd the
first workspace, AX_METADATA_URL set; ax's metadata paths are served. After the
child exits the runner reads summary.json (a crash without one becomes failed
with the exit code and stderr tail), delivers the output directory, writes
/workspace/.ousast-state/<task>.done.json and serves until SIGTERM (forwarded
to the group, SIGKILL after OUSAST_TERM_GRACE, exit 0). A boot with the marker
never reruns the command; a failed delivery is retried alone. Workspaces are
prepared on the first boot only. AX_RUNNER_EXIT_AFTER_COMMAND=1 is the
unit-test escape.
Reconciler (Req 2.2, 2.3, 3.1-3.3): `ax resume task` after apply, retrying
DeadlineExceeded/Unavailable with backoff up to OUSAST_RESUME_TIMEOUT (900 s);
completion is the artifact delivery; Failed after a resume went through, a
vanished task, or no delivery within OUSAST_TASK_TIMEOUT (7200 s) fail the
task with ax's condition message; `ax delete task` follows. Ax gains resume()
and phase() returns the condition message. doctor moves to plane/doctor.py
(tasks.md task 0 allows the sibling) to keep reconciler.py under 500 lines.
Tests: the fake ax follows the real lifecycle (Suspended, a failing first
resume that leaves Failed, Running forever, delivery only after a resume went
through), plus Failed-with-message, vanish, resume-timeout and task-timeout
scenarios; runner tests cover the child's cwd/group/metadata URL, stay-up and
SIGTERM in a real subprocess, SIGKILL of a SIGTERM-ignoring group, and the
marker. The opt-in live test now checks resume, Running, suspend and a second
resume instead of a Completed phase. design.md and tasks.md state the
lifecycle; the module audit manifest counts plane.doctor.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Requirement 1.1 (Task/Workspace/Model use only fields ax documents) and
Requirement 1.4 (no ax field repurposed) were violated: manifests accepted
metadata.namespace and a Workspace git `commit`, and the reconciler dumped
every git field into what `ax apply` receives.
Facts from ax's source (pkg/apis/v1alpha1/ax.proto, internal/workspace/setup.go):
- ObjectMeta is `name` and `atespace` (plus server-set creation_timestamp);
no `namespace`, no `annotations`.
- GitRepo is `name`, `repo`, `branch`, `dir`, `depth`; no `commit`.
- The API server decodes with protojson.UnmarshalOptions{}: an unknown field
is an error at `ax apply` (confirmed on the live cluster: a rendered
Workspace+Model applied cleanly; the same Workspace with `commit` was
refused with `unknown field "commit"`).
- ValidateModel checks only metadata; any spec.provider string is accepted.
Changes:
- manifests: metadata takes `name`, `atespace`, `annotations` (our extension,
never sent to ax); git entries take exactly ax's five fields (depth int);
`commit` in spec.git is rejected with a pointer to the new Workspace
annotation `openultrasast.io/git-commits: "<git name>=<40-hex>,..."`,
validated for unknown git names and non-hex shas.
- reconciler: rendered docs carry only ax fields; each bound Workspace's pins
reach the Task as env OUSAST_GIT_PINS = {"<workspace>/<git name>": "<sha>"}.
A test walks every rendered doc against ax's field lists.
- runner: pins come from OUSAST_GIT_PINS; git is fetched as setup.go does
(init/remote/fetch with --depth when depth > 0/checkout FETCH_HEAD, default
branch main, cloneDestination's dir and placeholder-name rules), then the
pin is checked out. A pinned entry without a branch fetches the commit.
- workspaces: emits the annotation, `dir: repo` and `depth: 1` instead of
`commit`, so generated case workspaces keep <path>/repo at depth 1.
- design.md: ax field names verbatim; pins and model binding as stripped
openultrasast.io/* annotations carried to the task by env.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Maintainer decisions 2026-09-29: ax (kind + Agent Substrate + ax controller on
this host) is the only executor; the Run layer carries dependencies, artifacts,
budgets and attribution until ax has them. Requirement 7 declares routing per
Task (one Model per Task, no runtime switching) and a token attribution table
from provider usage fields. Task 0 (bring-up, doctor), runner artifact delivery,
ax-backed reconciler with a fake-ax test seam. harnessx-removal brief records
the HarnessX inventory; removal is gated on the increment's measurement.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Nine tasks in dependency order: manifests, budget metering, runner contract,
reconciler and CLI, repo-facts, verify and agree, the increment's manifests, the
measurement against the recorded batched check, handover.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Package src/openultrasast/plane/: manifests (ax kinds + Run), a reconciler under
500 lines with persisted status and resume, an ax-contract runner, budget metering,
and task entrypoints. First increment: repo-facts (source-only callers, no model),
verify (the batched hunt with callers in the prompt, per-unit resume), agree.
Measurement on the 46-candidate set against the recorded batched check.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Six requirements from the brief: ax kinds plus a Run kind; isolated, idempotent,
resumable tasks with metered budgets; a local reconciler under 500 lines with no
pipeline logic; ax's runner contract; repo-facts as the memory layer; and a
measured first increment (repo-facts + verify on the 46-candidate set: at least 16
of 20 declared sites, under $0.022 per candidate for two passes).
Phase: requirements, not yet approved.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Adopt the design of google/ax (Task / Workspace / Model manifests, a reconciler,
isolated resumable execution, a runner contract), not yet its software: it needs
Kubernetes and Agent Substrate, lists only Google and Anthropic providers, and has
no pipelines, artifacts or budgets. We add a thin Run layer for those.
Each pipeline concern (classify, triage, repo-facts, verify, judge, recheck, score)
becomes a declared task with its own inputs, outputs and budget. That bounds the
tokens per task and lets each be developed alone. Decisions listed for the
maintainer.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Exploratory, 7 of 17 cases, stopped when the account emptied:
- source-only scope: a model reading every product file puts the vulnerable
function among the candidates in 15/17 (ranker 1/17, vocabulary 2/17);
- per-file triage + per-file 6-step hunts + two-pass agreement: 12/15 candidate
cases on the validation set; 4/7 on the full run, two more in one pass of two;
- precision: 5 pgAdmin agreed findings read against source, 3 true (privileged),
2 false with self-contradicting rationales; agreement cannot catch an error
both passes make;
- cost: $0.009-0.022 per candidate for two passes.
Four instrument defects fixed on the way (model id, provider routing, JSON-mode
final turn, unbounded tool output) void the earlier hunter number. No gate is
met; qualification needs population v3 and a protocol that states the judge
stage, the pass rule and a config-family question.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
v1 (1/11) and v2 (0/17 recall, 0/17 sampled precision, 12% completion) show that
fixes learned on one population do not transfer to the next. The causes are
breadth: framework-shaped entry points, module boundaries the frontends do not
resolve, name-matched sinks colliding, and scale.
Options:
- A: continue engine-first;
- B: the model proposes, the engine proves;
- C: narrow the product to one ecosystem.
Recommendation: first run the unchanged tool hunter on the v2 pins as the deciding
experiment.
For maintainer decision; no approved spec changes.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Every reserved case verified with git and file reads only -- nothing
scanned: pins present and ordered, the sink present at the vulnerable pin,
the fix touching the sink (or LearnPress's declared source-side fix site),
and the sink file hashed at both pins (benchmarks/independent/freeze.py,
record freeze-v1.json).
Each case now carries a benign control from its own history, reviewed by
diff. The mechanical keyword filter was not enough: it proposed an access
restriction, a filter check, API-token scopes, a login change and a
TLS-verification option, all rejected; Ultimate Member and alerta got
hand-picked controls (a WPCS reformat; a dependency change with both sides
still vulnerable). The guard test requires a benign pair per case once
frozen.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Eleven cases chosen by the maintainer from fifteen researched by advisory
and fix diff only -- nothing cloned, nothing scanned, none among the 262
repositories the benchmarks reference -- plus the earlier Ghost
reservation. Four are PHP repositories that ship JavaScript (two WordPress
plugins), satisfying the multi-language requirement; families are limited
to the v1 scope (injection, untrusted destination, permissive config).
The development subjects shaped every rule of the last week and can no
longer measure whether those rules generalise; this population can, until
something scans it. A guard test fails the moment a reserved repository is
referenced by a recipe, catalog, manifest or measurement outside
benchmarks/independent/. Freezing (pins and sinks verified by reading
source, a benign change per case) is the next step.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Same 500-region PHP run on frozen source: completion 281/406 against 153
(hard cap) and 131 (7.8), no portion killed, per-family findings never
lower, declared target still entailed. Records the 7.9 task, its limits,
and corrects the 7.8 reuse note, which was stated backwards.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Final end-to-end on the 500-region PHP subject: findings identical at 125 either way, completion
slightly lower under portioning (131 of 406 vs the hard-cap-plus-reserve 153), wall time higher
(2,982 vs 2,338 s). Told straight: portioning does not beat the cap on throughput here; it matches
it on what it finds, and what it buys is kill-safety -- a killed batch keeps its streamed answers
instead of losing them. Reaching the same 125 findings is the evidence that streaming loses nothing
the cap kept.
Completion did not rise because the requeue re-asks a killed portion remainder, and on this subject
those are the expensive output-encoding questions that keep hitting the ceiling in smaller pieces,
spending budget without completing. Telling a transient kill from a too-expensive family is the next
lever, not more portioning. Neither approach is release-ready anyway: 32-38% completion against a
95% gate on development data that qualifies nothing.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Four interacting defects surfaced in sequence when the portioner was measured end to end, each
hidden by the one before: run_batch timing polluted by its own retry, a single-attempt path missing
on the partitioned graph every plugin uses, and killed remainders dropped by a fixed chunk list. All
fixed and unit-tested; the end-to-end completion number is re-measuring on a frozen tree.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The joern-gated check passes on the real engine: the taint query streams one line per request, and
the comment-sink and literal-destination controls hold under the streamed form. Two defects the work
exposed are recorded as fixed -- the unportioned evidence pass, and a harvest that read a timed-out
pipe before killing its writer -- and one bypass is recorded as a limit rather than fixed: the reuse
layer re-query of missing ids calls the backend batch directly around the sink-weighted portioning.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The evidence pass bypasses the sink-weighted portioning by design: it is the pass that PRODUCES the
weights, and per request it is cheap, 17,700 answered in 44 s. It was still one all-or-nothing batch
protected only by the ceiling. On a plugin push transaction that batch is 22,125 requests, and under
the CPU and memory contention of concurrent test runs it exceeded the ceiling and cost the whole case.
It now runs in portions of 4,000 requests, roughly ten seconds of work behind one JVM start, with
answers merged and the census kept from the first portion that carried it. Streaming keeps what a
killed portion finished; portioning keeps that kill from being the entire pass.
Task 13.3 records the attempt that exposed this honestly: the case deadline was exhausted with no
artifact, and the failure was mine twice over -- the container mounts src live and the backend was
edited mid-run, and the evidence pass was unportioned. Neither is the algorithm. The rerun uses a
frozen export of the committed source with per-invocation logging.
1,423 tests pass, nineteen skipped; mypy clean.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
A hard per-invocation ceiling is all-or-nothing. A batch killed at 301 s lost every answer it had
already computed, and the retry paid a fresh JVM start per part to ask them all again: measured, 116
requests killed at 300 s, then eight restarts carrying the same everywhere-sinks in every part.
Three coordinated changes make portioning, not the cap, the thing that governs cost.
The taint query STREAMS. The census first, then one line per request as it is answered, flushed as
it goes, inside the unchanged fence. The other queries do not stream and need not; the driver
reads both forms, and a legacy single document parses exactly as before.
The driver HARVESTS a kill. The process group is terminated first -- a first cut read the pipe
before killing and a pipe whose writer is alive never reaches end-of-file; the suite own
hanging-engine control sat on that read for twenty-eight minutes -- then the pipe is drained and
every complete line becomes an answer, marked partial. The retry asks only the remainder.
Portion sizing ADAPTS. After each portion the observed seconds per sink visit, less the fixed
start, resizes the rest toward a 120 s target; a portion that did not answer halves the budget
rather than being fitted, because its true cost is unknown and above the ceiling. A portion cut
down to fit puts its remainder back at the front of the queue.
A census LINE carries nothing but the census. A first cut misread a legacy document that carried the
census beside its answers as a census line and dropped every answer it sat beside; a control caught
it. Task 7.8 in contributor-scan.
Verified: 1,423 host tests pass, nineteen skipped, including new controls for the assembler in both
forms and under a kill, for a retry that asks only the remainder, and for the sizer. Not yet
verified: the joern-gated streaming check and the plugin measurement, which wait for the transfer
replay to free the machine and are stated as open in the task.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Detection is not transfer, and the status says so: the comparison run is what decides M3. But the
target that task 13.2 could not reach for months is now found, and the reason is worth keeping where
the next reader will see it -- nothing about detection changed, the population became affordable.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
On the 500-region population where every earlier run produced nothing: 153 of 406 questions completed
and 125 findings, inside the deadline. 380 requests carrying 5,807 sink visits split into 11 batches,
each answering in 80 to 197 s, none near the 300 s ceiling. Every family that can speak on this
subject now does, injection included, which is the one holding a true positive here.
Four defects, each hidden by the one before it, and three of them one rule.
Batches sized by request count, when cost is per matched sink.
Packing heaviest-first, which starved injection of all 114 of its questions.
Any per-query timeout cancelling the whole scan, abandoning batches with 33 minutes left.
No budget kept for arbitration, which removing that cancellation exposed: rows are not findings.
The reserve had to be checked per BATCH. Checked between query kinds it changed nothing at all,
because one kind is a single loop iteration that runs every one of its batches inside it.
What it does not claim: 253 of 406 questions still went unanswered and one batch still records a
timeout; the raw finding count is dominated by output encoding, the family already measured to be
imprecise on PHP; and the reserve share of a fifth is a first value, not a tuned one.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Open since September and re-measured nine times. The cost of a taint batch is the number of CALL
NODES a family sink names match in the repository. Not the request count, not the declared sink
count, not any request parameter. reachableByFlows is asked per matched sink, and PHP
soutput-encoding sinks are echo and print, which a WordPress plugin writes thousands of times.
Three controlled sweeps on one graph, built once.
Batch size exonerated: 400 requests answer in 170 s, and cost per request FALLS with size because
roughly 70 s is fixed JVM start and graph load.
Request parameters exonerated: at 200 requests the full production shape, call depth 3 with
parameter sources, costs 221 s against a 150 s baseline.
The family is the variable: at the same 100 requests, SQL injection 147 s with six declared sinks,
path 194 s with sixteen, output encoding 704 s with seven.
And the driver named its own expensive step once it was asked to: 2,435 evidence requests in 45.5 s,
then 315 arbitration requests unanswered at 1,200 s, then a split abandoned for want of time.
It survived since September because every reproduction outside the driver carried the SQL sinks --
the family the declared target belongs to, and the one family that is cheap on this subject. Nine
hypotheses were eliminated by re-measuring the cheap case.
Splitting never rescued it because a failed batch is split by REQUEST COUNT and each part carries the
same everywhere-sinks. contributor-scan 7.7 carries the fix: budget a batch by the sink nodes it
implies, using the count the evidence pass already computes, and report a family whose sinks are
everywhere as expensive rather than as failed.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
