20 development pairs, one per repository, 4 per language, 5 per family; identities
in a gitignored manifest, counts and digest committed. Executor smoke drives one
executor task end to end without a model and fails loudly on an unread clone.
kube-ax operator constraints as steering.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Implemented with Codex; task 1.5 run by the coordinator against the real
sources (S3 memory read-only).
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Material for MkDocs site (mkdocs.yml, optional extra `docs`) with Mermaid via
the superfences custom fence. New pages: overview, scanning (modes, quick
rules, Joern engine, priors, pre-push delta), the plane on ax (one task as a
sequence, golden snapshot, Run DAGs), memory (row kinds, write/read paths,
FileStore vs S3, verify at startup), memory and detection, and RustFS setup
(admin steps, complete agent policy, .env, refusal messages, Select limit).
The ops READMEs are included at build time; evaluation gains the population
lifecycle and the fold layout. tests/test_docs_site.py runs the strict build
when mkdocs is importable and checks Mermaid blocks and the RustFS page.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
contributor-scan 2.2 for libpng and the 2.3 decision it exists to inform.
89,082 lines of C across 93 files, under a 2GB heap cap:
CPG build 16.1s (25s cold)
Joern queries 250.0s
arbitration 122.0s (105 calls, $0.0122)
whole scan 446s
peak RSS 911MB
regions 121, all arbitrated, 32 unasked
CVE-2025-66293 out_of_scope, as the recipe declares
Memory is not the constraint a fleet runner would hit: 911MB leaves room
for the rest of the job on a 2-vCPU/7GB runner. The memory pressure seen
while building this was concurrent JVMs on one desktop, not repository
size.
**Server mode: no.** The query phase splits taint 243.3s / config 10.7s
over two invocations, and fixed overhead measured on the same CPG is ~13s
per invocation. So ~26s of the 250s is JVM startup and ~224s is CPGQL
evaluation: a warm server removes 6% of the scan and none of the part that
costs. The driver now records query seconds per kind, because a single
total cannot tell startup from evaluation and the two answer this
oppositely.
The small repository pointed the other way. vampi's 34.3s over three kinds
is roughly three startups and almost no evaluation, which made a warm JVM
look worth having; the ratio inverts with size. That inversion is why the
task was sequenced after a real repository rather than decided on a
520-line file.
On whether one whole-repository CPG is the only shape for a horizontal
fleet: no, and it is also not where the pressure is. The build
parallelises and costs 16s; the query does not shard and costs 250s, so
splitting a repository across runners divides the cheap phase -- and after
2.4 a shard boundary hides exactly the cross-module flows that matter.
Scoping to a contributor's diff cuts the expensive phase instead. 911MB
for 89k lines extrapolates to roughly 5GB at a million lines, which would
exceed a standard runner, so the ceiling is real and further out than this
checkout can locate.
Two defects recorded rather than fixed, both invisible at vampi scale:
2.9, all 26 entailed findings are the same site reported 26 times, because
regions that share a sink each emit their own; and 2.10, 22 of the 30
highest-ranked regions are libpng's `contrib/` example programs rather than
the library.
Also ignores Joern's `workspace/`, which a maintainer querying a CPG by
hand from the repository root will create.
Gates byte-identical.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
Task 8.3 (Req 10.1-10.5).
- pairs.py: catalog rows with vendored = false carry their harvest recipe
and no excerpts; evaluate_catalog harvests them into
OPENULTRASAST_PAIR_CACHE (default ~/.cache/openultrasast/pairs) only
when `pairs --pointers` or OPENULTRASAST_PAIRS_NETWORK=1 allows the
network, otherwise records pointer_pair_skipped (a failed fetch is
pointer_pair_fetch_failed with detail); a warm cache never scores
without the switch. select_vendored for tests and gates.
- harvest.py: materialize_pointer harvests into the cache without the
license requirement (nothing is redistributed); redaction applies.
- catalog_gen.py: emits pointer rows with recipe fields; training
manifests skip them.
- pair_gate and improve/evolve.evaluate_profiles score vendored pairs
only; cli `pairs --pointers`; .gitignore covers the cache path.
- tests: loader, skip/degradation, cache hit, fetch failure, warm cache
with network off, profile gate exclusion, harvest and generator paths;
conftest keeps every test offline whatever the shell exports.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
