learn/retrieve.py: stage 1 is a per-instrument Gower distance over the
profile's allow-listed features with explicit missing (both ran: mean
feature distance; differing states 1; same non-ran state 0; null in one 1;
priors dropped with priors=off), n1 = 40 with seeded tie-breaks; stage 2
re-ranks by r = lam(1 - D) + (1 - lam)cos, signals_only without the
target's vector; the balance rule takes k_ret = 6 (<= k/2 per label, <= 2
per group, <= 2 other families; `short` recorded). eligible() is the only
way into a prompt: not the target's group, not an evaluated group, not the
held-out source or framework, and outside deployment not a near-duplicate
(cos >= 0.98). assert_boundary repeats the check on rendered ids;
demonstrations of a held-out framework swap to their alternates;
deployment_fold excludes a scanned repository that is a corpus group;
seed_memory never hands a case its own group.
learn/folds.py: compile split (25% of groups per primary family, 60/40
boot/val), outer grouped 5-fold stratified by family and label mix,
leave-one-source-out, leave-one-framework-out (insufficient data below 10
groups), assert_disjoint and a folds digest; all seeded.
Tests: test_learn_retrieve.py (hand-computed Gower, lam 0/0.5, balance,
near-duplicates, test_boundary over outer/LOSO/LOFO folds with
demonstrations), test_learn_folds.py.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Wrapper inference (learn/roles.py, no model): a function whose parameter reaches a
call already in the role set becomes a derived sink (or a sanitizer when it returns
the cleaned value) of the same operation, at depth + 1; a function returning a
source's value becomes a derived source. The role set starts from language-level
entries only (priors off by default, optional), grows to depth 3, and reads
vendored dependency source when present, so a vendored database class reaching
mysqli makes `->query` a sink without a framework table. A name the repository
declares more than once becomes a role only when every definition derives it.
Model roles (plane/tasks/roles.py): the model_sinks.py classification moved into
the package and extended to sink/source/sanitizer/guard/dispatch, per file chunk,
metered and resumable, client injected; a failed chunk is unclassified, never
"no roles". vocabulary_overlay merges inferred and model roles over the
language-level facts in the shape taint_specs takes, origin in the entry id.
Features: the roles (static) and model_sinks (plane) instruments are filled.
On the recorded validation-46 facts (15 cases, 14,368 product files, 87 MB read):
1,999 wrapper roles (1,753 sinks, 157 sources, 89 sanitizers; depth 1/2/3 =
973/651/375), 14 of 15 cases with at least one; the WordPress gopay plugin has
none with priors off, which is what model roles are for.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
learn/schema.py is the closed, typed allow-list of candidate features: 66 features over
11 instruments (language one-hot, quick rules with 23 mechanism buckets and a prior count,
engine, repo-facts, source span, entry-point distance, roles, delta, verify, agree, model
sinks), two profiles (static 57; plane adds verify, agree and model sinks for 66), schema_version and a feature-set digest.
No repository, path, file, function, rule or commit identity is a feature; site_match,
in_fix_range, fixed-pin alerts, case.json fields and costs are refused. Missing is not zero:
each record carries per-instrument state (ran | none | failed | not_applicable), and every
feature of an instrument that did not run is null.
learn/features.py builds records on the host (build_for_scan, whole repository or base..head
delta); plane/tasks/features.py builds them per case in a Run from the delivered artifacts,
dropping site_match and in_fix_range on read and ignoring fixed-pin alerts. The generator
adds a model-free `features` entry per case before `remember`, which stores the records as
`features` rows (re-validated). memory KINDS gains features, label, decision, experiment,
arm_outcome and experiment_result. The committed validation-46 manifests are regenerated
(entries appended; the first Run's entries are unchanged). The runner image must be rebuilt
and re-pinned before a Run executes the new task.
Proof on real artifacts (scratch store, not committed): the recorded validation-46 run gives
75 feature records over 15 cases (43 verify candidates plus vulnerable-pin alerts), each
case's vulnerable pin exported and read (0.5k-9k files); remember stored 75 features rows
beside 43 verdict, 84 alert, 61 unit_cost, 15 facts and 8 coverage rows.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Quick mode has rules only for c/cpp, groovy, java, javascript/typescript and
python, so every PHP case's "0 alerts" read as clean. The `alerts` task now
records per language of the files read whether quick mode covers it
(derived from the bundled ruleset, not a list): coverage quick | none, with
file counts per pin, and `uncovered`. `remember` turns that into `coverage`
memory rows (a new kind; the Run passes the alerts summary.json as input),
loop-measure reports coverage per language, and improve/memory.py's M1/M2
skip a repository+pin whose coverage for the rule's language is only
`none` (counted under `coverage_none` in the proposal's excluded).
`ousast plane alerts-engine <Run.yaml> --source <frozen export>`
(plane/engine_alerts.py) does the alerts task on the host for cases whose
files include a language the engine covers but quick mode does not (PHP):
exports both pins from the case cache, runs the quick scan and the
openultrasast:dev engine container (finding_dump.py, --network none,
--memory 3g, one at a time, per-pin deadline), writes engine findings in
the alerts.jsonl row shape (rule_id engine:<family>, source engine,
in_fix_range from case.json) with a summary (files read, questions,
completed, seconds, degradations per pin), and marks the task done via
reconciler.mark_done. No result, no files read, or questions == 0 fails
loudly and leaves the run untouched. Refuses a git checkout as source.
Runner image rebuilt and re-pinned (sha256:ebb40a9a...); validation-46
regenerated (digest only). Live, recorded in
benchmarks/measurements/2026-09-30-php-engine-alerts/: froxlor 366 files,
130/130 questions per pin, 6 alerts per pin, 0 in the fix range; wp-gopay
19 files, 101/101 questions, 0 alerts. The loop: 32 run rows (coverage 8,
php=engine), 0 proposals, gate no_proposals, $0.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Deletes harness_ext.py and hunter_harness.py with their HarnessX-only
tests (the judge path, verify_judge.py, went in task 5). The harnessx
extra, its mypy override and its uv.lock entries are removed (uv lock
drops only packages; no remaining version changes). The conftest
fixture becomes assert_cold_import; test_gate's two never-import checks
become one allow-list (stdlib, openultrasast, yaml) over the governance
planes' module-level imports, and the skipped live-extra tolerance test
is deleted. Audit rows for the two modules are removed, stage_processors
is reworded, and the module-audit manifest is regenerated (no orphan).
test_removed_plane_references implements Req 2.4 over src, tests and
pyproject.toml: a match must carry a `retired 2026-..` tag (the spec's
own slug is not counted). The README part is a strict xfail until task 8
rewrites the README's plane sections.
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
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
Model deepseek-flash (declared provider extension, endpoint prices in
parameters, secretKey naming the DEEPSEEK_API_KEY secret), digest-pinned
Task templates repo-facts / verify / agree, and a generator
(plane/generate.py, `ousast plane workspaces --validation-set ...`) that
emits per case the vulnerable-pin Workspace, a files-only inputs Workspace
(recorded candidates after the recorded triage, declared sites, triage),
per-case Tasks and one Run validation-46: facts -> verify a, verify b ->
agree for the 15 cases, 46 candidates (43 kept), budgets 1.5x the recorded
per-pass share. A Run entry cannot add a binding or env, and Run.inputs
names only task artifacts, so the case is fixed by per-case Tasks.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
ai-service-plane task 3, Requirements 4.1-4.4 (with 2.2 and 2.3 honoured by the
exit-code contract):
- src/openultrasast/plane/runner.py: the ax-task-runner entrypoint. Reads the Task
from AX_TASK_YAML and the bound Workspaces from AX_WORKSPACES_YAML (task-1 loaders),
serves /healthz and /readyz on port 80 (AX_RUNNER_PORT; 0 picks a free port,
AX_RUNNER_HTTP=0 disables it for unit tests), materialises each workspace at its
bound path (spec.files verbatim; spec.git at <path>/<name>, exported from the
OUSAST_CASE_CACHE checkout whose origin matches, else a shallow clone at the pin;
a repo already present on a resumed volume is kept) and only then answers 200 on
/readyz. Runs spec.command by importing openultrasast.plane.tasks.<name> with the
remaining elements as argv; sets OUSAST_WORKSPACE_DIR from the first binding when
the Task's env leaves it unset. A crash writes summary.json with status failed and
the traceback. When OUSAST_ARTIFACT_URL is set, the whole OUSAST_OUTPUT_DIR is
POSTed as an uncompressed tar (Content-Type application/x-tar, X-Ousast-Task,
X-Ousast-Run) with three attempts and backoff; a failed delivery rewrites
summary.json to failed and exits 2. Exit codes: done 0, failed 2, unfinished 3.
- plane/Dockerfile.runner: python:3.12-slim + git, `pip install .` (no extras), a
shell wrapper at /usr/local/bin/ax-task-runner exec'ing the module; built and
loaded into kind by ops/ax/up.sh, not by the tests.
- tests/test_plane_runner.py (+ tests/plane_stub_task.py registered as the task
module): env contract on a files workspace, readyz 503 then 200, delivery to a
local receiver with the headers and tar checked, delivery failure -> failed and
exit 2 after three attempts, crash -> failed with traceback, exit codes per
status, case-cache export at the pin, shallow-clone fallback, resume keeps the
checkout.
- model/audit.py: SPEC_OWNED row for plane.runner; module-audit measurement
regenerated (122 modules, no orphans, note kept).
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Requirements 3.1, 3.2, 3.3, 3.4, 3.5, 2.2, 7.1, 7.3 of ai-service-plane.
- plane/reconciler.py (492 lines, test-counted): a Run's tasks submitted to ax
in dependency order through the injectable `ax` CLI (apply / get task /
delete task), serialize labels never overlapping, --workers, state.json with
pending|running|suspended|done|failed|unfinished, a PID lock per run, done
tasks skipped on rerun, unfinished tasks holding their dependants, a failed
task halting the run. Budgets, inputs, output dir, artifact URL and the bound
Model (annotation openultrasast.io/model; identity and priced parameters) go
to the task as env in the rendered Task; consumed artifacts travel as files
of a generated Workspace bound under /workspace. A threaded HTTP receiver
takes each task's tar delivery, validating run/task and rejecting traversal.
Outcome comes from the delivered summary.json (done only when every unit
finished), never from ax's phase alone. status prints the token attribution
table per task and Model from the summaries' usage fields (n/a, never an
estimate) and writes attribution.json; doctor runs the four host checks.
- plane/workspaces.py: one Workspace manifest per case pin of a population.
- CLI: ousast plane run|status|doctor|workspaces.
- tests/test_plane_reconciler.py: a fake ax executable drives the DAG;
tests/test_plane_ax_live.py (marker ax) applies ops/ax/smoke-task.yaml on a
live cluster and skips unless doctor passes.
- Module audit rows and regenerated manifest.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Requirements 5.3, 2.1, 2.2, 2.3, 7.2 of ai-service-plane.
- plane/tasks/verify.py: the batched hunt of verify_batched.py moved into
the package (system prompt, one hunt per file, up to 6 candidates, 6
steps, candidate-anchored sites). New against the reference: each
candidate's known callers from facts.json in the prompt (capped at 8),
tool turns and usage per hunt in units.jsonl, per-unit resume (rows
with "error" are re-asked), pass label from env, MeteredClient wrapper:
BudgetExhausted -> unfinished (exit 3), AccountError -> failed with the
provider message (exit 2); summary.json is written last, names the bound
Model and the summed usage, and is done only when every unit finished.
- plane/tasks/agree.py: verify_batched.agreement over two pass outputs,
agreed.json / disputed.json, per-candidate cost and turns, declared-site
match via benchmarks/independent/evaluate.matches_v2 loaded by file;
metrics block in summary.json; no model calls.
- tests/test_plane_verify.py: a scripted usage-recording hunter client;
callers line, resume, 402, budget stop and resume, model and summed
usage, unpriced usd None, both main() env contracts, agreement metrics.
- model/audit.py + module-audit manifest: SPEC_OWNED rows for plane.tasks,
plane.tasks.verify, plane.tasks.agree; manifest regenerated.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
plane/tasks/repo_facts.py computes, from source text only and without a
model or git, the product files of a workspace (tests, vendored trees,
node_modules, dist/build, minified bundles and dot-directories excluded via
the layout facts plus the model_sinks.py filter), the functions each file
declares (Python, PHP, JavaScript/TypeScript, Java, Go, Ruby declaration
patterns extended from sink_candidates.py) and, per candidate function, the
call sites in other product files with path, 1-based line and enclosing
function, capped at 40 and sorted (Requirement 5.1). Output is byte-identical
across runs over the same tree (Requirement 5.2).
Under the task contract the unit is one file: a row goes to units.jsonl as
each file finishes and a restart reuses the rows computed for the same
candidate set (Requirement 2.2); facts.json is assembled from the rows and
summary.json is written last, refusing `done` unless every unit finished.
The entrypoint reads OUSAST_WORKSPACE_DIR, OUSAST_OUTPUT_DIR and optional
OUSAST_INPUT_CANDIDATES only (Requirement 2.1) and exits 0 on done, 2 on
failed with the traceback recorded in summary.json.
tests/test_plane_repo_facts.py: a three-file tree with a tests/ file, a
vendored file, a node_modules bundle and a dot-directory; cross-file callers
with line and enclosing function, same-file and declaration lines excluded,
the 40 cap, byte-identical second run, resume that recomputes only the
missing unit, a crash that leaves `failed` with the unit counts and resumes
to `done`, and the declaration patterns per language.
The two new modules are registered as spec-owned in the module audit (their
importer, the runner, lands in task 3) and the audit manifest is regenerated.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Add openultrasast.plane.manifests: frozen dataclasses and loaders for ax's
Task, Workspace and Model kinds (ax.io/v1alpha1, ax's fields only) and the
Run kind (openultrasast.io/v1alpha1: tasks, dependsOn, inputs, outputs,
budget, serialize). Every violation raises ManifestError naming the kind,
metadata.name and field path: unknown fields at any depth, wrong apiVersion
or kind, a provider outside google/anthropic unless deepseek is declared via
the openultrasast.io/provider-extension annotation, a Run with a dependency
cycle, an input naming no task, and a Run task naming no loaded Task.
load_manifests reads multi-document YAML files and indexes by kind and name.
PyYAML becomes the one declared core dependency; the two zero-dependency
guards now pin exactly that, and the module audit registers the plane
package under the ai-service-plane spec.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
MeteredClient wraps a ChatClient, sums the provider's usage rows per call,
prices them from a Model manifest's parameters (cache-hit, input, output per
million), and raises BudgetExhausted before a call once the usd or calls
ceiling is reached. A 401/402 or "Insufficient Balance" failure becomes
AccountError with the provider's message. An unpriced model reports usd None,
never zero, and refuses a usd budget; summary() gives the spend block of a
task's summary.json.
The two plane modules are registered as spec-owned in the module audit (their
consumers land in tasks 3-4) and the audit manifest is regenerated.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Every model call has failed since 2026-09-10 (83ab533):
- The default detector and judge model was `deepseek-v4.1-flash`, the product name.
The API rejects it with HTTP 400 ("The supported API model names are
deepseek-flash, deepseek-v4-pro"). The judge and pipeline record an endpoint
failure as a degradation, never a verdict, so nothing failed loudly.
- `tool_hunter.resolve_hunter_client` resolved OpenRouter only. In this project
DeepSeek is the chat provider and the OpenRouter key is scoped to embeddings, so
the hunter could not reach a chat model at all; the call came back 401.
The defaults are now `deepseek-flash` (priced). The hunter resolves DeepSeek first
when its key is set, and OpenRouter stays as the explicit or fallback route.
Verified live: plain completion and a tool call through both the endpoint resolver
and the hunter client.
Not affected: the independent evaluations (finding_dump runs with
max_model_calls=0) and the 2026-09-06 hunter measurement, which predates the id.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Three of the four fixed-side alerts left in the independent population had one
cause: the fix was a check, and checks were not modelled.
- wger's fix is `url_has_allowed_host_and_scheme`: `if not ...(next_url):
next_url = reverse(..)` and `if next_url and ...(next_url): return redirect`.
- Ultimate Member's fix is an allowlist: `in_array(strtoupper($order), [...],
true) ? $order : 'ASC'` and `elseif (in_array($sortby, $allowed, true))`.
(The fourth, Signal K, is `assertAllowedHost`, a project-local function. It is not
covered.)
Sanitizer facts can now say `guard = true`. A guard is a check, never a cleansing
call on a path. A flow is discharged only when a guard tests a variable the path
carries, and the flow is in one of these places:
- inside the branch whose condition requires the check. The guard may be combined
with `&&` only;
- past a failure test, a single `!` combined with `||` only, whose branch exits
(return, exit, die, wp_die, throw) or overwrites the value, and whose condition
dominates the flow's end;
- through a ternary whose condition requires the check, where the other arm cannot
carry the value. The engine can enter through the condition's own copy of the
value, which never becomes the result.
Facts: `in_array` (PHP) and Django's `url_has_allowed_host_and_scheme` /
`is_safe_url` (Python). A row now consults guards even when a request lists no
sanitizers.
Two Joern-gated tests cover the discharged shapes and, as controls, an unguarded
redirect, a guard on a different variable, a failure that is only logged, the
unguarded else branch, and the ternary arm the check does not select. Both tests
fail without the guard.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Two defects found by the cause-B rescan of the independent population (exploratory,
a retune after protocol-v1):
- `typescript_property_support_unvalidated` still reached the whole repository.
YesWiki is a PHP application that ships a few `.ts` files, and all 1,128 of its PHP
questions were unresolved. The limit is now owned by the TypeScript partition. A
TypeScript project (Mockoon, Signal K) is unchanged.
- `isSourceCall`, and the method-level "reads a source" heuristics, matched source
patterns as substrings. Flask's `request.get` therefore claimed Django's
`request.get_host()`. wger's fix passes that host to
`url_has_allowed_host_and_scheme`, and both fixed functions were reported as open
redirects from it. Patterns are now matched as bounded tokens, like sinks and
sanitizers. wger's vulnerable-pin detections rest on `request.GET`, which still
matches.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
This extends dbcb230 to the remaining graph-integrity gaps. In the independent
evaluation these gaps were repository-wide:
- alerta: one symlink, `alerta/app.wsgi`, which is not even source, made 261 of 261
questions unresolved.
- wger and Signal K: a language no frontend reads did the same.
- YesWiki: unparsed files did the same.
Now:
- the partition build records the paths a symlink boundary skipped (a directory
ends in `/`) and the languages no frontend reads;
- `files_unparsed` carries its full paths;
- the scan demotes only questions about an owned path or under an owned directory,
and only questions in an owned language.
Every gap stays in the report as a boundary. A gap that names nothing keeps its
partition-wide or repository-wide reach. Tier-0 pruning stays off, as before.
The tests that pinned repository-wide reach now assert ownership. The one about a
vendor exclusion masking an integrity failure keeps its intent, using a census gap
that names no file.
Retune after protocol-v1; exploratory only.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
`esc_sql` and the mysql/pg `*_escape_string` functions only backslash quotes. A value
they escape is safe inside a quoted literal and nowhere else. Ultimate Member
CVE-2024-1071 is `$sortby = esc_sql(...)` built into `" ORDER BY u.{$sortby} "`, and
it read as sanitized. Sanitizer facts can now say `quoted_only`. The escape keeps its
credit unless the first string the value is built into (concat, interpolation,
addition, f-string) places it after literal text that opens no quote. With no string
built downstream, the credit stays as before. pg_escape_literal adds its own quotes
and stays a full cleanser.
Two further defects hid the same CVE:
- The engine is field-insensitive on the object. Its one path from `$this->sql_order`
went `$this` -> `$this->having` -> `esc_sql($this->having)` -> ... -> the query.
absorbedByObject cut it, and it credited an unrelated field's escape. When a path
leaves a field through the object for another field and reads the first field
again, the detour is spliced out. The later read may be on the path or inside the
sink argument where the path ends.
- The field join judged a field clean if ANY sanitizer name was on its path. It now
uses the same quote-aware check as a row. This matters because the engine's own
path to the query changed between runs: 2 of 4 identical runs chose a path via
`$wpdb->prepare`. The field join is the deterministic route.
Exploratory (retune after protocol-v1): the Ultimate Member vulnerable pin is detected
at class-member-directory-meta.php:936. The fixed pin still alerts at :945. Its fix is
an allowlist (`in_array(...) ? $v : 'ASC'`, and an `in_array` guard), which is not
modelled yet.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
python.toml's sources were Flask-only, so no flow could start anywhere on a Django
project. OpenCVE's SSRF reads its URL from `form.cleaned_data`, and the scan answered
the sink file and found nothing. Added: request.GET/POST/body/COOKIES/FILES/META,
DRF's query_params, and cleaned_data.
With those sources known, OpenCVE reported three redirects that cannot leave the
site: `reverse("cves") + "?" + request.GET.urlencode()` (twice) and
`reverse(route, kwargs=...)`. Destination sink facts can now set
`prefix_fixes_origin` and `origin_anchors`. A path is cut when it enters a
concatenation, f-string or `+=` through anything other than its leftmost operand,
and that operand fixes the origin. Origin-fixing operands:
- a literal `/x`, `?` or `#`;
- a literal of the form scheme://host/;
- an anchor call;
- a variable whose every assignment fixes the origin.
A path is also cut when it passes through an anchor. `"/" + x` (//evil) and
`"https://" + host` stay reported. A Joern-gated test covers all seven shapes.
Exploratory (retune after protocol-v1): OpenCVE vulnerable and fixed pins are both
0 findings, down from 2 and 3. The SSRF itself is still missed, because the flow
crosses a registry dispatch (`REGISTRY.get(t)(extras).run()`) that the engine does
not follow.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The first independent evaluation (results-v1.json) completed no question on eight of
eleven projects. On the cases traced, the cause was a census gap: `.eslintrc.js` or
`webpack.config.js` missing from a JavaScript graph, or `contrib/apache/api.wsgi` from a
Python graph, and every question in that language was then marked unresolved. Now only
questions about a named missing file are demoted. The gap is still reported as a
boundary. A gap that names no files still reaches its whole partition.
This is a retune after the evaluation. Per protocol-v1 it cannot be qualified on the
same population.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The core-hook-argument class from the second PMPro adjudication:
pmpro_membership_history_profile_fields($user) on `edit_user_profile` was
a route entry, so its parameters were attacker input -- and $user is the
WP_User WordPress loaded; its ID became an SQL injection.
A callback registered in a string-keyed registry is handed its arguments by
the matching apply call, not by the request. The mapper now records the
registration call on the entry (`registered_by`), regions carry it, and the
dispatch fact says which registrations DO hand a callback request-borne
arguments (`request_arguments`; WordPress: add_shortcode, whose $atts are
post content). Every other registered callback keeps its call depth but
its parameters stop being sources; request data that reaches an apply
call's arguments is still followed by the hook half of the taint query.
REST routes are not registry entries and keep the parameter rule.
Controls: the fact field is validated against `register`; a hook callback
is not input, a shortcode and a plain route are.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The apply_filters class from the second PMPro adjudication (2 of 3
remaining false positives): `apply_filters('pmpro_random_code', $code,
$this)` returned whatever $this carried, and a report's `$type` reached SQL
only as an extra filter argument. Two causes, both fixed generally:
- The dispatch fact now says what an apply call RETURNS: `returns` names
the calls whose result is the dispatched value and `value_arg` its
position (WordPress: apply_filters/apply_filters_ref_array return
argument 2; do_action returns nothing). A path through such a call must
ENTER by that argument -- the first of the run of the call's arguments
before it, because the engine hops between sibling arguments
($_GET["c"] -> md5("x") -> apply_filters). Loaded and validated as data;
the query knows no framework.
- A call was a source when the pattern appeared anywhere in its text, so
`apply_filters(..., $_GET["c"])` and `sanitize_text_field($_POST[..])`
were sources themselves -- the "a token matches the thing it names"
invariant. A call is now a source when the pattern names its callee,
receiver or the access it is; the inner access stays a source.
Controls: dispatch facts load/validate; a real-Joern case with request
data as filter context (quiet) and as the filtered value (found). 1,453
host and 18 query tests pass.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
da0ee57 turned parameter sources off for the mapper's catch-all `function`
entries, and with them the field join's seeds, which read the same flag:
MW WP Form's CVE-2023-6559 ($this->Data, filled by a constructor) was lost
(10 -> 3). The field join now has its own request field,
`fieldParameterSources`, set by the old entry rule; a region's own
parameters follow the new one. Both known CVEs are found again (MW WP Form
10 -> 4, WP Statistics 39 -> 18, 91/91 and 774/774 completed). The dropped
findings sampled against their call sites all take internal values:
ExistTable('useronline'), wp_statistics_visit('today'), remove() on the
plugin's own temp directory, _render('text', ...).
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Two classes the traced PMPro survivors named after 1f91c0b:
- The mapper records every named PHP function as an entry of kind
`function` (3,507 of PMPro's 4,412), and every entry's parameters were
sources, so internal helpers became injections: sendCancelAdminEmail's
$user, a gateway hook callback's $user_id/$morder fired by do_action.
Regions now carry the entry kind; parameters are input only for request
entries (route, parser, privileged surface). Call depth is unchanged, so
such a region is still followed into its callees. JavaScript and Python
emit no `function` entries.
- The object rule is general: a field read continues a flow through the
bare object only if the taint came through the SAME field, or was
assigned to the variable or passed in as a parameter. It now also cuts
$this->Gateway -> this -> $this->user_id (memberorder.php:705).
plausible() memoises the sink test per node and skips the object walk for
paths with no field access (the filter had cost one outlier 101 s -> 160 s).
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The loop the maintainer called out: four scale defects in the PHP transfer
replay, found one per two-hour Joern run, all Python bookkeeping between
engine calls. benchmarks/push/python_overhead.py ends that: the real
replay() on the real PMPro pins, with a JoernBackend whose graphs are stubs
and whose queries answer instantly with rows recorded from the real engine.
Engine time is zero, so everything measured is ours, in about a minute,
under the sampling profiler. Its first pass named two more walls:
- Region discovery re-parsed the ruleset for every region: 89,127 TOML
parses, 275 s of a 339 s discovery, twice per push. The fact, obligation
and taxonomy loaders now keep the parsed (immutable) result keyed by each
file's name, size and mtime -- an edit in place or an added file reloads.
Discovery 339 s -> 7 s; output digest identical on PMPro.
- affected_context decoded every span's and every line anchor's path for
every context row -- a changed file has an anchor per unchanged line --
78% of a stubbed push. Decoded once per call, anchors indexed by line and
bisected, original order kept. A randomised control compares it against
the row-by-row matching over 200 contexts (>100 attachments).
Result: the whole stubbed PMPro push, 27,542 answered requests and 2,688
outcomes, runs in 58.5 s of Python. What is left is the engine.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The third wall under the 13.3 replay, found by the streamed case log: the
evidence and context passes finished at 14:53, then nothing -- no engine
call, no log line -- for 82 minutes, until the case was killed 60 s past
its 7,200 s deadline. `affected_context` tested membership with
`relation not in relationships` on a list: 7,998,000 comparisons for 4,000
relationships (profiled, 83% of the time), and a push over a WordPress
plugin attaches tens of thousands. The deadline is checked once per
question, so a single late question could run for minutes, which is also
why the process overran its cancellation allowance.
Membership now goes through a set beside the ordered list, and each
distinct context path is resolved once instead of once per row. Measured:
4,000 relationships 7.4 s -> 0.44 s; 400,000 in 16 s. The control counts
comparisons rather than timing them, and fails on the old code with
7,998,000.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The PHP transfer replay (pre-push 13.3) spent its whole 7,200 s case in the
head side's evidence pass. A probe on one PMPro graph named the cause: not
compute -- context adds ~20% engine time -- but OUTPUT. Each evidence request
listed every method its scope reached, up to 1,845 rows; 200 requests into
the bundled Braintree SDK returned 52,831 rows, 9.4 MB, against 211 rows
without context, over 22,125 requests in a 3 GB container.
`affected_context` only ever attaches a location in a changed file, and
every other row was checked (real file under the root, usable extent) and
discarded. The scan now sends the changed files; the engine itemises those
and folds the rest into one `context_elsewhere` row carrying exactly what
that check reads. With no safe file list the engine itemises everything,
as before.
Equivalence: unit controls over valid, missing-file, no-extent and
outside-root cases, with and without a changed-file row; a real-Joern
control; and on PMPro itself, 2,440 relationships and zero gaps decided
identically from both forms, 52,831 rows down to 3,241 with the most
referenced file as the change. Probe: benchmarks/push/context_cost_probe.py.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The measured-cost run left 99 taint requests unasked to keep time for
arbitration and reported them as `query_failed` -- an engine that could not
answer -- because they were simply missing from the answer. They are now
`query_budget_reserved`, both as a degradation and as each question's outcome
reason, and are no longer double counted when nothing answered.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The 7.8 trace showed the completion loss was a sizer death spiral, not
expensive families: after two kills the budget fell to 3 sink visits and
never recovered, because portions finishing in 25-30 s sat under an assumed
70 s fixed start and read as "no information", so the budget could only
shrink.
- taint.sc streams each answer's own cost (`ms`); the backend carries it as a
reserved `__timing__` list through shards, partitions and reuse.
- The sizer budgets predicted seconds from per-family seconds-per-visit rates
learned from those costs, and measures the fixed start as the wall time the
answers do not explain (median), instead of assuming it.
- A kill names its culprit: the first unanswered id in request order. The ids
behind it never started and are re-queued at once; the culprit is asked
alone after the rest. One that still fails alone after more than a
portion's target is reported as `query_too_expensive`, apart from
`query_failed`.
- Portions grow id by id from the queue head, and a single-portion scan now
goes through the queue too, so a kill there re-asks its remainder.
- Fix: the reuse wrapper wrapped only `run_batch`, so since 7.8 every
portioned query bypassed the graph-reuse cache and its source-root
normalization. `run_batch_once` is wrapped too.
Co-Authored-By: Claude Opus 5.5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The portioner iterated a fixed pre-split list, so a killed portion left its unanswered ids behind:
on the plugin the list ran out at 1,263 s of a 3,600 s budget with those remainders lost, and
completion sat far below what the budget could buy. It is now a work queue. A portion that comes back
short pushes its unanswered ids to the front, to be re-asked at the budget the kill just halved;
`fit` splits an over-budget head, so heads shrink toward single requests, and a single request a
whole ceiling could not answer is dropped rather than looped on forever. A control asserts both the
re-ask and that termination.
This is the last piece of portioning-over-cap: streaming keeps what a kill finished, single-attempt
timing keeps the sizer honest, coverage tells a too-big portion from a slow one, and the queue keeps
working while budget and work remain.
1,425 tests pass, nineteen skipped.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
run_batch_once was wired on the disposable and sharded paths but not the partitioned one -- and a
multi-language repository, which every WordPress plugin is, builds through the partitioned graph. So
the portioner fell back to run_batch there, whose internal split-retry folded into the time it
measured: a portion read 956 s and collapsed the sizer, exactly as before the single-attempt fix.
The fix had no effect on the one subject it was written for.
PartitionGraph now has run_batch_once, dispatching to each sub-graph the same way run_batch does --
the routing is factored into one _dispatch method that takes the per-graph method name. Sub-graphs
are built through the disposable path and already carry run_batch_once.
The lesson, again: a capability added at one construction site is not added at the others. There are
three that build a queryable graph -- disposable, sharded, partitioned -- and the one that mattered
for the measurement was the one missed.
1,424 tests pass, nineteen skipped.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
End-to-end, the adaptive portioner regressed completion -- 64 of 406 against 7.7 hard-cap 153 --
while finding the same defects. The cause: the portioner timed each portion with run_batch, which
splits on failure internally, so one portion folded its own eight-way retry into its number and read
953 s. The sizer fitted a per-visit rate from that and collapsed its budget to 14 visits, spending
the back half of the deadline on tiny portions.
Two portioning layers were fighting. The portioner is now the sole retry layer: it asks
run_batch_once, a single invocation whose kill returns the answers it streamed, so its wall time is
the cost of one attempt. And it observes COVERAGE, not emptiness -- a portion that came back short
of the ids it asked halves the budget, because it was too big for the ceiling; only a whole answer
gives a clean per-visit sample to fit from.
run_batch_once is new on CpgResult, wired on the disposable and sharded paths; a backend without it
falls back to run_batch unchanged. Host controls cover the single-attempt path and the
halve-on-short-answer rule.
1,424 tests pass, nineteen skipped. The end-to-end plugin re-measure on a frozen tree is the open
item; the mechanism (a kill keeps what finished) and the sizer logic are unit-verified.
Co-Authored-By: Claude Opus 4.8 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Measured on the plugin, first run of the adaptive sizer. A 600-visit portion answered in 184 s and
the budget was correctly cut to 262. The next portion, 199 visits, answered in 73 s -- three seconds
of work above the 70 s fixed start -- and 3 s over 199 visits read as 0.015 s each, so the budget
grew thirteen-fold to 3,404 visits. The ceiling killed that portion. The harvest kept the 13
answers it had streamed, which is the mechanism working; the sizing was not.
Two rules. A sample with less than ten seconds of work above the fixed start is not extrapolated
from, because it carries no information about cost per visit. And a budget may double per portion,
never more: the sizing may still be wrong, but by at most one factor of two, which a kill undoes.
1,423 tests pass, nineteen skipped; the sizer control asserts both rules.
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
The reserve was computed once and checked between kinds, and one kind is a single iteration that runs
every one of its batches inside it. So taint spent the whole budget and the reserve only stopped the
cheap kinds queued behind it: 0 of 406 questions completed, 2,435 s of a 2,700 s deadline in queries,
identical to having no reserve at all.
The granularity of a budget check has to match the granularity of the work it guards. It is now
checked before each batch, and the batches left unasked are logged rather than silently dropped.
1,420 tests pass, eighteen skipped.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Querying fills rows. Arbitration turns them into findings and the outcomes are assembled from that,
and neither costs the engine anything -- so a scan that spends its whole budget on queries reports
nothing at all, however many of them answered.
Found by accident, which is the honest way to tell it. A per-query timeout used to cancel the whole
scan. Removing that cancellation was right on its own terms and made the measured result worse: the
query phase then ran the full 2,700 s deadline to exhaustion and completed 0 of 406 questions, where
the cascade had stopped it at 958 s and left time to arbitrate 78 findings. The cascade had been an
accidental budget guard. This is the deliberate one.
The query loop now stops issuing batches with a reserve in hand: a fifth of what was left when
querying started, a sixty-second floor, and never more than half. The cap is not decoration -- held
back without it the floor swallowed a whole small budget and the query loop never ran at all, which a
control caught. A scan with a fifth of a second to spend must still spend it.
What the loop skipped is recorded as query_budget_reserved with the kind and the request count, not
left to look like a query that failed.
1,420 tests pass, eighteen skipped.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
A taint batch costs what its matched sink NODES cost, because reachableByFlows is asked per sink.
Measured at a fixed 100 requests on one plugin graph: SQL injection 147 s with six declared sinks,
path 194 s with sixteen, output encoding 704 s with seven. The declared count does not predict cost
and the request count does not predict cost.
So batches are budgeted in sink visits rather than requests, using the count the evidence pass
already produced: a family whose sinks are rare rides in one batch, and a family whose sinks are
everywhere is split until it fits. A request over the budget on its own gets its own batch rather
than being dropped, because the scan job is to report that it is expensive, not to decide it is
unaskable.
Measured on Paid Memberships Pro at 500 regions, where every earlier run produced nothing at all:
380 arbitration requests carrying 5,807 sink visits split into 12 batches, every one answered,
heaviest 103 s and none near the 300 s ceiling. 144 findings where there were none.
The order is the ranker and must stay the ranker. A first attempt packed heaviest-first, which packs
better and analyses worse: the expensive output-encoding batches ran first, spent the deadline, and
left injection with 114 questions asked and none answered -- the one family holding a true positive
on that subject. A deadline always cuts a tail, and the tail it should cut is the one the ranker put
last.
1,420 tests pass, eighteen skipped.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The mechanism already existed. A question whose evidence vector says no sink of its family is in
reach cannot produce a flow, and tier-zero pruning defers it. That was switched off for the whole
scan whenever any of twelve degradation reasons appeared, and a multi-language repository always
carries two of them, so the measured plugin arbitrated every question it could ask. Third instance
this week of one blast radius, and the invariant written into the design on Monday named it.
A prune blocker that names a partition now withholds pruning from that partition questions and from
nobody else. cross_partition_semantics_unresolved leaves the blocker set entirely, for the reason it
left the integrity gaps: a PHP family sink is PHP, so a second language cannot be why its vector saw
none.
Measured on Paid Memberships Pro. At 25 regions arbitration falls from 127 questions to 34 with 93
recorded deferred as tier_zero, and 19 findings before and after, identical family by family. At 500
it falls from 2,526 to 406 with 2,120 deferred.
It is not sufficient, and that is the useful half. The 500-region run still fails in the same way at
the same cost, because 406 questions at roughly one and a half seconds each still exceed the
300-second per-batch ceiling. This lever moved the volume; the ceiling is a separate limit.
The census now records what a scan skipped and why, per family, so a cheaper scan and a narrower one
stop looking identical: a family whose every question was pruned reports no sink of this family in
reach rather than region offered, no question asked.
1,420 tests pass, eighteen skipped.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
The scoping fix looked applied and was not. The same census gap is raised in TWO passes, arbitration
and evidence, and only the first carried the partition it came from, so an unscoped copy kept
demoting every question in the repository. One key in one dict.
What found it was the record, not the code: the census now prints each outcome reason rather than
only its status, and three separate causes had been looking identical as a bare count of unresolved.
Measured on Paid Memberships Pro at 25 regions: questions completed goes from 0 to 120 of 127, with
its 19 findings unchanged. The seven still unresolved are the JavaScript partition own questions,
which is correct, because the four missing files are its files and its answers are the ones that
could be wrong.
Still open, and recorded rather than implied: the push policy _blocking_degradations exempts declared
exclusions but does not yet respect a partition, and a post-hoc diagnostic copy carries no language,
so a JavaScript gap would still block admission of a PHP finding.
1,419 tests pass, eighteen skipped.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
A missing JavaScript file cannot make a PHP answer wrong. A census gap now carries the partition it
was raised for, and reaches only that partition questions. On the measured plugin four JavaScript
files -- a webpack build output, a minified select2, a build config and one source file -- had taken
the admissibility of 4,425 PHP regions with them.
Two controls exercise the real boundaries rather than injecting a reason, and both were confirmed to
FAIL with the old classification restored, so they guard what they claim to.
And the rule is now in the design, because this was the fifth instance found and fixed one at a time.
Two invariants, eleven instances between them:
A degradation is owned by the narrowest scope that caused it. Vendor exclusion as a global veto,
line ambiguity inherited by every question, an empty scope blocking a sibling comparison, a language
boundary demoting every answer, a census gap demoting every answer. The fourth and fifth cost the
declared v0.1 target its entire admissibility, and neither passing subject could reveal it because
both hold one language.
A token matches the thing it names, not text that contains it. gets inside fgets, resolve inside
resolveUrl, user inside users, a sink word inside a comment, a dotted setting on its last segment,
a flow query reading the receiver.
Each carries a review test: a new degradation must state the scope it reaches and justify demoting
that far, and a text match must be bounded AND confined to the part of the node that names the callee.
1,419 tests pass, eighteen skipped.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
Membership of GRAPH_INTEGRITY_GAPS should turn on whether a gap can make a reported answer WRONG,
not on whether it cost coverage. An unparsed file may hold the sanitizer that would have cleared a
flow this scan reports, so it belongs there. A flow this tool cannot follow from one language into
another can hide a finding and never invent one, because a PHP sink is sanitised in PHP.
cross_partition_semantics_unresolved therefore moves to DECLARED_EXCLUSION_GAPS. It touches exactly
two places, both of which already honour the distinction: the outcome demotion in scan.py, and
_blocking_degradations in the push policy, whose docstring already says a declared exclusion is not
one of them. The reason stays published in the scope unresolved boundaries either way, so the limit
is still reported; the class decides only whether every answer in the repository is demoted.
This corrects the task note written earlier today, which said not to reclassify on the grounds that
it would claim cross-language flows are out of scope rather than unresolved. That was a misreading
of the class.
PMPro still completes none of its questions, and the measurement now names why: the JavaScript
partition expected 36 files and holds 32, so partition_file_census_incomplete fires and is still an
integrity gap. The four absent files are js/blocks/blocks.build.js, js/jsapi.js, js/select2.min.js
and webpack.config.js -- a build output, a source file, a minified third-party library and a build
config. A bundled select2 costs 4,425 PHP regions their admissibility. Same over-broad blast
radius, third instance of one principle in this thread, and the fix direction is recorded.
The census harness now records each degradation whole rather than only its reason, because a
partition census that reports files missing carries WHICH files and without them the gap is a label
rather than a lead.
1,417 tests pass, eighteen skipped.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
NodeGoat's server.js configures a permissive session at line 78 and disables template
auto-escaping at line 135, both inside the same function. The arbiter returned one verdict per
question, so the escaping defect that task 14.3 added was detected on every run and reported on
none: which of two real defects a contributor saw depended on where in the file it sat.
Configuration now returns one verdict per setting whose value the model could read. The pipeline
already emitted one finding per entailed answer, so this arbiter was the only place still folding
them to one.
Three boundaries are drawn rather than assumed.
- A setting whose value is COMPUTED stays one verdict per region. That band is a question for the
judge rather than a finding, and returning every undecided setting would multiply model calls
for claims the graph did not establish.
- A call carrying two permissive literals is one finding. cors({origin: true, credentials: true})
is one misconfiguration, not two.
- Config verdicts now carry a path:line:function location. Without one they shared the region's
identity and the deduplicator kept a single finding, so the plural answer collapsed straight
back to one. That is the same gap dominance carried until its findings stopped arriving with no
line at all.
Dominance is left answering once per region, and that is settled rather than pending: its claim is
that a region contradicts itself, so the region is the unit and a second verdict would restate the
same inconsistency. The pipeline now says so where it used to call this a known gap.
Measured: NodeGoat's config_secrets goes from one finding to two, server.js:78 for the session and
server.js:135 for the disabled escaping, with the applied marked.setOptions fix between them
staying silent. VAmPI is unchanged and no other family moved.
1,417 tests pass, seventeen skipped; thirteen Joern-gated query tests pass in the image.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
