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Commits
| Author | SHA1 | Message | Date | |
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 Marius CiepluchandClaude Opus 5
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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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Marius CiepluchandClaude Opus 5
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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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Marius CiepluchandClaude Opus 5
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fe45081b43 |
fix(ci): run ruff format, and record run 5 at 90% pair-correct
CI was red on `ruff format --check`: 23 files. I ran `ruff check` after every
change this session and never once ran `ruff format --check`, though CI runs
both. Lint passing is not formatting passing, and I treated one as evidence for
the other for the whole session.
Formatting applied. The full CI sequence now reproduces locally: format, lint,
mypy over 94 files, 735 tests, three gates byte-identical, compileall, and the
semantic job's 16 marked tests.
Also records run 5 of the pipeline measurement, which the vampi fix lifted as
predicted:
hunter (K=5) pipeline (K=1)
pair-correct 76.7% 90.0%
leak 12.3% 6.7%
detection -- 96.7%
cost ~$0.69 $0.0068
27 of 30 pairs. Five runs, each step from a measurement contradicting an
assumption: 73.3 (no pipeline path) -> 73.3 (routing fixed, IDENTICAL, which
exposed the discarded verdict) -> 80.0 (residual question matched to its
arbiter) -> 86.7 (aiohttp settings) -> 90.0 (dominance question no longer
contradicting its own evidence).
One miss left: dsvpwa-dsvpwa-main, whose setting is an argparse --ssl default
rather than a security-setting call. Out of reach before the settings work and
still is; contorting the arbiter around one pair would be worse than the miss.
The caveat is recorded beside the number: 30 pairs of one slice, and the slice
iterated against all session. The +16% overfitting gap against vfc-js is why
contributor-scan Req 8.1/8.2 exist.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
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Marius CiepluchandClaude Opus 5
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3fe7b9ded7 |
fix(model-grounded-detection): the dominance question contradicted its own evidence
vampi-users-update-password scored both_silent while the arbiter returned model_corroborated on the vulnerable side and nothing on the fixed one -- so the finding existed and the pipeline threw it away. The residual question was written for the ENTAILED case, but entailed returns before the judge is ever consulted, so the question is only ever asked for CORROBORATED. It asserted "in a file where sibling handlers are guarded" and asked about "the guard its siblings have", printed directly above a witness reading "and no guarded sibling" -- because corroborated means precisely that no sibling is guarded. The judge was handed a prompt contradicting its own evidence line and reasonably answered no. The question now describes what corroborated actually is: an obligated operation no guard governs, with no sibling evidence either way, so the model cannot tell from consistency alone whether the guard is missing or the module is deliberately public. That is the real open question and the one worth asking. Verified end to end against a live endpoint: vuln model_corroborated, fixed silent, the pair splits. The taint and config questions were checked for the same defect and are correct -- each describes the corroborated case it is actually asked about. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |
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Marius CiepluchandClaude Opus 5
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db3db6056d |
feat(model-grounded-detection): widen the settings table, wire the weak-algorithm arm
Two things, and a finding that says neither fixes the pairs that prompted them.
The settings table was Flask/FastAPI-shaped (CORS, set_cookie, app.run) while
the corpus contains aiohttp and Django applications, so three config_secrets
pairs contained no modelled security setting at all. Added aiohttp's
session_setup and cookie storages and Django's SECURE_* / DEBUG settings: 8
calls to 24.
And config_secrets spans three abstractions while only one was wired -- a
permissive setting VALUE. Weak algorithm CHOICE (CWE-326/327) is a different
thing: the danger is the algorithm NAMED, not a flag left open. Its data has
been sitting on the sink facts as `weak_literals` since before this feature and
nothing read it. Both abstractions read the same literal, so the arm is small:
hashlib.new("md5") is now entailed and hashlib.new("sha256") is not.
The finding: the three silent config pairs are CORPUS DEFECTS, not model gaps.
Measured similarity 23%, 45% and 53% -- dsvpwa-dsvpwa-main pairs `def main()`
against `def run(self, handler)`, a different function entirely. No settings
table can make those split, and it is worth saying so rather than letting the
work imply otherwise. The table gap was real and worth closing on its own
merits; it just is not why those pairs are silent.
734 passing, mypy/ruff clean, 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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Marius CiepluchandClaude Opus 5
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52f2ab5b4d |
fix(model-grounded-detection): ask the residual question the arbiter actually raised
The corrected re-measure returned numbers IDENTICAL to the buggy one, which was the clue. Routing was fixed, the dominance arbiter was reached, and the finding was discarded anyway -- because every corroboration was put to the judge as a TAINT question: "a sanitizer appears on the path: yes, does it suffice?". For a missing authorization guard that question is meaningless. The judge answers no to something that does not apply and the claim is dropped. All three vibe-py access_control pairs scored both_silent this way even though the dominance arbiter had returned model_corroborated for each of them, which I had verified by hand earlier in the session. Fourth instance in this feature of one shape: taint-specific behaviour applied to every family. Sanitizer matching, config routing, family dispatch, now the residual question. Each was exposed by a measurement rather than by a check. The question is now phrased for the arbiter that raised it -- a guard asymmetry for dominance, a permissive setting for constant abstraction, sanitizer sufficiency only for taint. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |
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Marius CiepluchandClaude Opus 5
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7a76fcb028 |
fix(model-grounded-detection): the pipeline arbitrated only flow families
scan_region took a TaintSpec and called taint_verdict, so access_control and config_secrets -- whose dominance and constant-abstraction arbiters have worked since group 4 -- had no pipeline path at all. On the first end-to-end vibe-py run every one of their pairs scored `both_silent`, which reads as the model failing when in fact no code reached the arbiter. This is the same class as the ceiling harness routing config_secrets through taint: family routing fixed in one place and not carried to the other. Third time this shape has appeared in this feature, which is worth saying plainly. Dispatch is on the spec TYPE rather than a family name, so a family without an arbiter cannot be silently routed to the wrong one -- it simply has no spec and is skipped, visibly. Co-Authored-By: Claude Opus 5 (1M context) <[email protected]> Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG |
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Marius CiepluchandClaude Opus 5
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cdedb372dd |
feat(model-grounded-detection): wire the detector -- the enumerator proposes, the model disposes
Everything before this built an ARBITER: something that judges a flow taint
reachability had already found unaided. Nothing proposed to it. That is why its
recall was never comparable to a detector's, and why comparing 41.3% entailment
against the LLM hunter's 76.7% pair-correct was comparing two different kinds
of thing. model/judge.py and enumerate_candidates were called by no production
code at all; every number so far came from a measurement harness.
The wiring turns on a distinction judge() alone conflated:
the model CONTRADICTS it has coverage at this site and says no -- a
sanitizer on the path, or a declared-safe sink shape.
The claim is dropped (Req 8.2).
the model CANNOT DECIDE no modelled sink or source reaches the site at all.
The model is SILENT, not negative, so the claim is
reported at `suspicion` (Req 8.4).
Treating silence as refutation is the tempting mistake and would be wrong here:
23 of the 39 misses in the entailment ceiling were sinks simply absent from the
fact tables, so "no flow" usually means the model cannot see it rather than
that nothing is there. The rung carries that uncertainty on the finding's face
instead of a confidence score nobody can act on.
An entailed site still costs zero model calls. The candidate budget is bounded
so a dense region cannot become an unbounded spend.
Smoke-tested end to end against a live endpoint: 2 pairs, detection 100%,
$0.0024. The full vibe-py measurement -- the first like-for-like comparison
with the hunter's 76.7% pair-correct and 12.3% leak -- is running.
727 passing, mypy/ruff clean, zero orphaned modules.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
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