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6dc25d77e443632972051fcda91791a796548e5a
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6dc25d77e4 |
feat(model): let the project say what it ships, and rank that first
contributor-scan 2.10. Every one of libpng's twenty-five entry-point regions was a `main()` -- twenty-three under contrib/, plus example.c and pngtest.c -- and those regions carried the fifty interprocedural taint requests that dominated a 300s query phase. A library has no entry points, so entry-point-driven analysis had nothing to anchor to except its own example programs. The task said to derive this rather than hardcode `contrib/`, and a project already declares it. Makefile.am names installed targets in `lib_LTLIBRARIES` and `bin_PROGRAMS`, each target's `<target>_SOURCES` names its files, and `check_PROGRAMS`/`noinst_PROGRAMS` are automake's own word for "not installed" -- exactly the distinction wanted. Taking every `_SOURCES` would have called libpng's whole test suite shipped code, since contrib/libtests declares its sources the same way the library does. interprocedural regions 25 -> 1 taint query 300.1s -> 125.0s total query 311.9s -> 138.5s regions 121 -> 121, unchanged by design The surviving interprocedural region is contrib/tools/pngfix.c:main, which libpng genuinely installs. Two rules keep it honest. **Silence is not exclusion**: a project with no build file this can read gets None back and nothing changes, so vampi's numbers are untouched. **Not shipped is not unscanned**: those regions are still arbitrated function-locally, because a contributor editing a test must still get an answer -- what they lose is the expensive treatment and first claim on the budget. Entailed findings went 0 -> 3, and all three are false positives at contrib/gregbook/wpng.c:374, `strcpy(outname+len, ".png")`. It is safe: outname is char[256] and line 325 guards with `if ((len = strlen(inname)) > 250)`. They were not introduced so much as uncovered -- a different callDepth meant a different sink set, and the 26 fgets false positives were masking them. The structural cause is recorded as 2.12: c/injection and c/memory carry ZERO sanitizers, so no C flow can ever be discharged and every `argv -> strcpy` entails however carefully it is bounded. The discharge here is not a call but a guard that dominates the sink, which is precisely what dominance.sc already does for access control and is wired to that one family. Also adds Group 7, five tasks for stopping the same false positive twice. Two of today's three false-positive classes were one bug in three matchers -- `resolve` in `resolveUrl`, `user` in `users`, `gets` in `fgets` -- each fixed locally and each next one surviving because nobody carried the fix across. A model may group counter-examples by cause and draft an edit; only a split-respecting measurement may adopt one, because the predecessor's improve lever admitted shapes taught by the holdout pairs they then recovered and turned a -0.059 Youden into +0.059. Gates byte-identical. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |
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67497c4d68 |
fix(cpg): a sink is matched as a word, not as a substring
`fgets` contains `gets`. The sink matcher's last clause was an unbounded
`methodFullName.contains(n)`, so every bounded read in libpng matched the
sink for the unbounded one. All 26 entailed findings on that repository
were the same false positive:
*argv -> fgets(pnmline, 256, wpng_info.infile) (line 335, 8 steps)
which is the safe API being reported as the dangerous one -- and `fgets`
is in the fact tables as a SOURCE, never a sink. Verified against the CPG:
methodFullName is exactly "fgets", and .contains("gets") is true.
Third instance of one bug class in this codebase, after the sanitizer that
matched `resolve` inside `resolveUrl` and the discharger that matched
`user` inside `users`. The sink matcher had never been given the same
treatment. All four of its clauses now run through the shared bounded
matcher, and that matcher is the punctuation-tolerant version written for
task 2.6 -- so `input(`, which an unconditional lookahead had made
unmatchable in `input(x)`, works for the first time as well.
libpng entailed 26 -> 0
Zero is the right answer for a PNG library whose only known CVE is out of
family. Gates byte-identical, so no pair outcome depended on the substring
match.
What remains on that scan is recorded, not claimed: 113 `c-unsafe-*` rows
assert an API is present rather than misused, and 50 overlay-coverage rows
are annotations rather than findings. 82 of the 113 are under `contrib/`.
Task 2.11 covers whether that band is worth putting in front of a
contributor at all; 2.10 already covers not scanning example code.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
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68b4e551f3 |
feat(model): the envelope checkout, and no to Joern server mode
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 |
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d15985f695 |
fix(model): a guard discharges the obligation it is a guard of
contributor-scan 2.6. Access control entailed 7 of 9 VAmPI handlers,
including three that do authorize and three the OpenAPI spec declares
public. Five separate defects, each invisible to a corpus of one-function
excerpts and each found by asking the query what it actually matched.
**A trailing segment is not a match.** `query.get` was matched by its last
segment, so every `.get(` in the repository became a protected database
operation -- `request.headers.get('Authorization')` and
`request_data.get('username')` included. Four of the seven false positives
came from this, and so did the apparent detection of the known BOLA: it was
entailed because fetching the Authorization header had no dominating guard,
not because of the defect. A qualified token now requires its qualifier.
**Configuration is not authorization.** dominance_specs took every
obligation fact. `security_setting` operations are discharged by a VALUE,
which config_specs already claims them for; pooled in here they made
`app.run(...)` an operation requiring an authorization guard and put
thirteen tokens in BOTH lists -- an obligation that is its own discharge,
the same shape as the taint sink that used to sanitize itself.
**Input validation is not authorization.** `jsonschema.validate` was
counted as a guard, so handlers with no authorization check at all read as
guarded. No operation in the table requires validated_input.
**A guard discharges the obligation it is a guard of.** The largest one.
`orm-read` requires an identity_constraint or an ownership_check;
`token_validator` is a path_guard. Flattened into one list, authenticating
the caller discharged an object-level obligation -- a handler that
authenticates and then looks the record up by a PATH parameter read as
fully guarded. The facts state that relation and the spec was discarding
it; it is now carried and the engine asks per operation.
**A word boundary needs a word.** Found while fixing the above. Guard
matching wrapped every token in `(?<![A-Za-z0-9_])...(?![A-Za-z0-9_])`.
The identity token `['sub']` begins with `[`, and the character before it
in `resp['sub']` is `p` -- so the assertion could never hold. Every
identity token starting with punctuation was unmatchable, and the identity
constraint that separates a correct lookup from an IDOR was invisible.
Also: dominance rows were repository-wide, so the model's unguarded
`delete_user` was attributed to the API handler of the same name. Rows are
scoped to the region's file, which is what the rung's own justification
says -- the evidence is a file contradicting itself.
Measured against VAmPI's OpenAPI `security` blocks, which declare per
operation whether auth is required, and agree with the code:
vampi precision 28.6% (2/7) -> 50.0% (2/4)
known found 3 of 3, all model_entailed
And on the labelled access-control pairs, which nobody tuned this against:
all 9 pairs pair_correct 3 -> 3, leak 44.4% -> 11.1%
7 non-VAmPI pair_correct 2 -> 2, leak 42.9% -> 0.0%
Every detection lost was on a pair whose FIXED side was flagged too, which
scores nothing. No correct detection was traded for the precision.
get_by_title was flagged before it was in the recipe: its code carries the
comment "# Broken Object Level Authorization" and the README lists it, so a
real finding was being scored as a false positive. It is now the recipe's
third known vulnerability.
Both remaining false positives are endpoints the spec declares public.
Recorded as 2.8, with the reason the mapper's access_level cannot simply be
trusted: for decorator frameworks "public" means "no decorator found",
which is the bug itself.
Gates byte-identical.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
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0fcd5feade |
feat(model): a region for the code that is in no function
contributor-scan 2.5. VAmPI's `host='0.0.0.0'` is now reported exactly once, at app.py:17:<module>. Before task 2.2 it was reported eight times in eight files that do not contain it; after 2.2 it was reported nowhere. Two causes, one shape: nothing could ask about module-level code. **The main-guard marker is not a function.** `__main__` is what the mapper emits for `if __name__ == '__main__':`. Sent to the engine as a function name it matched nothing, because a CPG calls a file's top-level code `<module>` -- verified against the VAmPI CPG rather than assumed. The region model translates the marker, which is the one place that turns what the mapper meant into what the scanner asks. **A function-scoped file had no region for its module body.** Settings, route registration and globals live in no function, and every region's query filters by function name. A file-level region beside the handlers would report each handler's findings a second time, which is why the earlier rule dropped it as "a second full-file pass". A module-scope region PARTITIONS the file instead of overlapping it. That only became cheap after batching: before it, a region was a JVM. Two things this needed to be correct rather than merely present: - A module method spans its whole file, so the taint query's line-range containment made `<module>` the parent of every function in it. Under module scope, membership is direct -- otherwise the module region reports every handler's sinks again, which is the duplication the old rule was avoiding. - A module body is not a handler. The marker-derived region inherited the handler families and entailed a missing authorization check on the main guard: a finding with no possible remediation. Caught by the first repository run that had the region, and now covered by a test. bind address 8 wrong files -> 0 -> 1, at app.py:17:<module> regions 22 -> 25 entailed 8 -> 9 query time 37.4s -> 41.3s peak RSS 827MB -> 823MB cost $0.0067 -> $0.0068 Three more regions for four seconds and no more model calls: the budget is a total and was already spent, so regions_unasked rose 17 -> 20 -- those regions got the free pass and are reported as unasked, not as clean. `<module>` is Joern's Python name for a module body; JavaScript uses `:program`, so this is verified for Python only. Gates byte-identical. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |
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ca7b5ba370 |
feat(model): a region that spans the flow, not just a function
contributor-scan 2.4, closing the no-go task 2.2 recorded. VAmPI's SQL injection is a request parameter reaching `get_by_username` in api_views/users.py, passed to `User.get_user` in models/user_model.py, interpolated into a query string and executed there. Source and sink are in different functions and different modules. Regions were per-function, so neither region saw both ends and the engine was silent on the most ordinary shape a real injection bug has. `reachableByFlows` was never the limitation -- it follows calls already. The limitation was the QUESTION. Sinks were filtered to the labeled function's own body, so a crossing flow had no sink to end at. Three changes, each with a reason it is sound rather than convenient: **An entry point is the trust boundary.** parameter_sources was off for repository scans because a repository's parameters are not all attacker input. An entry point's are, by definition -- that is what makes it an entry point. The driver turns it on only for regions the mapper found and named, and leaves it off for walker fallbacks and for named functions that are not entry points. **Sinks may sit below the handler.** taint.sc admits sinks in methods reachable from the labeled method through the call graph, bounded at ENTRY_POINT_CALL_DEPTH = 3: handler -> service -> data access, which is where these bugs live. Unbounded would make the question about most of the repository rather than about this entry point, and make it unaffordable. **The finding names the sink, not the asker.** A crossing flow ends in another file and another function, so Verdict carries the evidence's own `path:line:function` and the site uses it. Reporting `models/user_model.py:73:get_by_username` would name a place that does not exist: line 73 is inside get_user. Also: labeled methods are now resolved by name AND file. `get_user` exists in more than one module of a real repository, which a corpus of one-file excerpts could never surface. Measured on the same checkout and budget as 2.2: VAmPI-SQLI missed -> model_entailed at models/user_model.py:73:get_user known found 0 of 2 before 2.2's fixes, 1 of 2 in 2.2, 2 of 2 now entailed 7 -> 8 query time 40.9s -> 37.4s peak RSS 869MB -> 827MB cost $0.0067, unchanged Asking the bigger question cost nothing measurable here: file scoping and call-graph following pull in opposite directions and roughly cancel at this size. That is one 520-line repository, and VAmPI is now the repository this change was developed against -- the exact overfitting shape Req 8 exists to catch. The depth bound and the entry-point rule mean nothing general until a checkout nobody tuned against says so. Gates byte-identical. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |
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177c7f3719 |
feat(model): first repository measurement, and the four things it found
contributor-scan 2.2. VAmPI at a pinned commit, scanned whole rather than as excerpts, with benchmarks/repos/measure.py recording build time, query time, arbitration time, peak memory, cost, unjudged regions, and whether each known vulnerability was found and at which rung. The corpus could not have found any of this. Every defect below needs a repository to become visible, and three of them were invisible behind a passing test suite. **The batch path was unreachable.** query_batch was implemented, tested and committed while CpgResult exposed only `run`, so the driver's capability check found nothing and fell back to one JVM per region-family: the first attempt at this measurement ran eighteen minutes on 520 lines, issuing `--param function=` one at a time. Every test called query_batch directly, so none of them noticed. CpgResult now carries run_batch and a test asserts the capability is reachable through the object the driver is handed. The earlier 275s->106s improvement attributed to batching came from region deduplication alone. **The budget stopped free work.** It bounds model calls, but was enforced by breaking the region loop -- spending a paid limit to stop unpaid CPG arbitration. 6 of 22 regions were examined and VAmPI's BOLA, which the graph entails for nothing, was never reached. It now withholds the judge only. 22 of 22 regions arbitrated, 17 counted as regions_unasked (silent because unaffordable is not silent because decided), and the BOLA is entailed by the model layer. **A region with no function asked about the whole repository.** Sending function="" matched every hit in the tree and the driver attributed that answer to whoever asked: one `host='0.0.0.0'` in app.py became eight identical entailed findings in eight files that do not contain it. Queries now carry the region's file. Entailed findings 14 -> 7, query time 70.9s -> 40.9s. The single-request form stays unscoped so the committed pair measurements remain reproducible. **The JVM had no heap bound.** Joern claimed a quarter of physical RAM and runs were killed under memory pressure at different points, so the numbers described the host rather than the engine. -J-Xmx2048m by default, OPENULTRASAST_CPG_HEAP_MB to raise it. Also: arbitrated findings carried `function:line` where the report layer read `path:line`, so every entailed finding reached a contributor with a function name where its file belonged; and the witness line was parsed by splitting on a comma, which produced sites like `config.py:17): permissive literal '0.0.0.0':?`. Reading: GO on one CPG per repository -- 6.2s to build, 177s end to end, 869MB, $0.0067, nothing infeasible. NO-GO on region-scoped taint as the only shape: VAmPI's SQL injection runs from a handler parameter into a function in another module, and a per-function region sees neither end. That is the ordinary shape of a real injection bug, so it is recorded as task 2.4 along with three smaller defects this run exposed. Gates byte-identical. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |
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8c387306be |
feat(repos): pinned known-vulnerable checkouts, offline by default
The pair corpus scores excerpts: a vulnerable function and its fixed twin, handed to the engine with the answer already narrowed down. Nothing in it exercises a repository -- region ranking, the budget, one CPG over thousands of files, or whether a verdict that holds on fifteen lines still holds when the source, the sink and the guard live in three modules. benchmarks/repos/<name>.toml names a real checkout: url, a full 40-char commit SHA, licence, and every known vulnerability with its file, function and line. `ousast repos` lists them; `--fetch` materialises one; CI does neither, and conftest clears the switch and redirects the cache so a developer with warm checkouts cannot read them by accident. Three rules the loader enforces rather than documents: - A branch or tag is rejected. Either would make the same recipe mean different code next month while the baseline it produced kept the old numbers. - `in_scope` must be stated per vulnerability, never defaulted. It decides whether "not found" is a miss or a non-question, which is the most important thing about the result. - A recipe that declares `detection` must name something in scope to detect. `ousast repos` does not trust a recipe either: against a materialised checkout it checks HEAD against the pin, that the licence file is there, and that each declared function appears above its declared line. That earned its place immediately -- the first libpng recipe named LICENSE.md, which is the filename at HEAD today and not at the pinned commit, where it is still LICENSE. Two checkouts, verified against the real repositories: - vampi (MIT, 520 lines) is the DETECTION checkout. Excerpts of it are already in the pair corpus, including the update_password miss diagnosed earlier, so a whole-repository run says directly whether a verdict survives the move off the excerpt. Its routes register through an OpenAPI operationId, so it exercises registration-based entry-point mapping rather than the decorator path. - libpng (libpng-2.0, 91k lines of C) is the ENVELOPE checkout, pinned at the parent of the commit that added the missing clamp. Its CVE is marked out of scope: an out-of-bounds read is not a family this engine arbitrates, and recording "not found" against it as a miss is the easiest way to make a measurement lie. Nothing is vendored; the recipe records the licence so an artifact can say what it ran against. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |
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c35426e186 |
perf(model): one Joern invocation per query kind, not one per region
JVM startup dominated a scan: a call per region per family put a ten-line file at 275s over three regions, and would have put a thousand regions at roughly fifty hours. The queries themselves are milliseconds once the CPG is loaded, so the cost was almost entirely process starts. scan_repository() is now collect -> batch -> arbitrate. The three .sc scripts accept a `requests` JSON map and answer all of them in one run, keeping the single-request form so the committed measurements stay reproducible byte-for-byte. Arbiters are untouched: each is handed a CpgResult whose `run` returns its own prefetched rows. The batcher builds parameters by calling request_params() extracted from taint.py, dominance.py and config_value.py rather than reconstructing them. A second copy that drifts from the arbiter's is the exact shape of the five family-assumption bugs the predecessor spec spent a session finding; there is now one definition per family and the batcher borrows it. Regions are also deduplicated by (path, function), collapsing the nameless entry-point rows that were producing `model:injection:?:10`. Measured on the same ten-line file: 275s -> 106s, three duplicate findings -> one `model:injection:ping:10`, rung unchanged at model_entailed. Gates byte-identical. Server mode is recorded as task 2.3, deliberately sequenced after the repository measurement: whether the remaining ~100s floor is worth a process model, a weakened subprocess seam and a Scala-evaluating HTTP endpoint depends on a build-time-to-query-time ratio only 2.2 produces. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |
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e67f3ee2f0 |
feat(contributor-scan): 1.3 the model layer reaches a user
`model-grounded-detection` finished 16/16 with the model layer having zero
production callers. This closes that. A real scan of a Flask file now reports:
by_rung: {"model_entailed": 3, "model_corroborated": 0, "suspicion": 0}
model:injection:ping:10 <- os.system("ping -c 1 " + request.args["host"])
The stage is the fifth MAP proposer, mirroring _check_obligations, and is
additive: pattern, overlay and obligation findings all keep working, and without
a CPG engine it records cpg_unavailable and changes nothing else. Two scan
integrity tests pin the exact degradation set and both broke -- correctly. Their
`requested == baseline` assertion, that findings are byte-identical, still
passed, so the only change is that the scan now SAYS the arbiter was absent
instead of being silently without one. The guards are updated to assert the
model degradation specifically rather than being loosened.
ModelLayerConfig, not ModelConfig: that name is already the [models] block, and
the type checker caught the collision immediately. Two meanings of one name is
how a scan silently reads the wrong settings.
Every payload carries the same shape, skipped ones included. A payload that is
sometimes a full record and sometimes a single "skipped" key is how a report
ends up quietly omitting a section.
unjudged_sample names the lowest-ranked regions the budget did not reach.
Counting them is the honesty requirement; naming them is what lets a maintainer
write a large-repository exclusion list from evidence rather than guesswork.
The run also produced the finding behind new task 1.4: 275 seconds for a
ten-line file. cost_usd is 0.0, so those 21 invocations were not model calls --
they were Joern query launches, one per region per family, each a JVM start.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
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8663c1a5b3 |
feat(contributor-scan): 1.1 regions from entry points, 1.2 the repository driver
Pair scoring could rely on a labelled function; a contributor cannot supply one -- which code is risky is the question they are asking. Regions now come from entry points, with a file-level fallback that says it is one, and each carries only the families its shape and language admit. Ranking uses what EntryPointRecord already decided (access_level, trust_boundary) rather than a second opinion computed from the same evidence. A family is offered only where its arbiter could answer: access_control needs a handler, so a library file with no entry point is not asked about obligations it has no siblings to be inconsistent with. The driver makes the two costs that were free at pair scale explicit. ONE CPG per repository, reused across regions -- a build is 5-30s on a forty-line excerpt and per-region builds would make this unusable. And a budget that is a TOTAL for the run rather than the enumerator's per-region cap of eight, spent highest-rank-first, with whatever it does not reach counted into regions_unjudged. A tool that silently analyses a tenth of a repository and reports a clean result is worse than one that says what it skipped. Two flaws the tests caught, both mine and both about ownership: the budget counted calls by reading a client's own usage log, so it silently never tripped for a client that keeps none -- the driver now counts its own spend through a wrapper; and the driver trusted its caller to have sorted, when the order the budget is spent in belongs to whoever holds the budget. The third was worse and only surfaced because a test failed for the right reason: the driver passed candidates=() and never enumerated, so a repository scan would have reported only what the arbiters establish unaided and never populated the suspicion band -- which supplied 15 of 26 findings in the pair measurement. It enumerates now. Sibling audit (Req 8.5) done before writing: family routing lives in exactly one production place, pipeline._arbitrate, dispatching on spec type. regions_for returns family names and the driver resolves specs, so that stays true. 750 passing, mypy clean over 96 files, gates byte-identical, zero orphans. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |
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4e4681f162 |
docs(contributor-scan): design and tasks -- wire it, then measure on a real repo
Requirements approved, design and tasks generated. 47 criteria, all traced; 13 tasks in 6 groups. The design is deliberately conservative. The model layer joins as ONE STAGE INSIDE MAP, beside the obligations checker it most resembles -- which already takes entry points, produces findings and merges them. Findings are added, never substituted; the pattern and overlay paths keep working; a machine without Joern scans exactly as it does today. Nothing here is allowed to make the tool worse for someone who does not have the engine. Two decisions carry the most weight. One CPG per scan rather than per region: a build is 5-30s on an excerpt and is the dominant cost at repository scale, so per-region builds would make this unusable. And one total budget rather than the enumerator's per-region cap of eight, which is meaningless across thousands of regions; the budget is spent highest-rank-first and whatever it does not reach is counted and reported, never silently truncated. Task 2.2 is a go/no-go and comes before shipping: the first scan of a pinned known-vulnerable checkout is a measurement nobody has taken, and if one CPG per repository proves infeasible the region and budget design changes shape. Better to learn that before groups 3-6 are built on it. Group 5 (corpus) is last on purpose. The binding constraint today is reachability, not corpus size -- 198 of 238 OWASP pairs went unvendored because volume without readability makes every number worse. The task preamble carries the predecessor's two hard-won habits: audit sibling paths in the same commit as any routing or matching change (five bugs shared that shape, each caught by a measurement rather than a check), and run the whole CI list rather than the parts one remembers (CI was red for a session because `ruff check` passing was taken as evidence for `ruff format --check`). Not approved for implementation. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |