3.1 adds StaticFinding.rung beside evidence_level rather than renaming it. The
existing evidence_level carries `static_corroboration`, emitted by the flat IR
overlay -- a path Req 4.4 demotes to the suspicion band. Restating that as
model_corroborated would claim a CPG arbitrated something it never saw, and
rewriting every legacy finding to suspicion would be a product-visible
regression nobody asked for. So `rung` defaults to suspicion and is raised only
by ladder.at_rung(finding, verdict), which is the structural form of Req 5.4:
nothing rises above suspicion without a Verdict behind it. The witness travels
with the rung, because a rung without its evidence is just a louder assertion.
It reaches markdown, JSON and SARIF.
3.2 is the judge, and it is defined as much by what it lacks. Three exhaustive
outcomes: the model entails (report it, never call the model), the model
contradicts (drop the claim, record why), the model cannot decide (report
suspicion). The LLM gets one bounded typed question with tools=[] so it cannot
search for the site, asked only about the residual the graph cannot settle --
whether a sanitizer on a REAL flow suffices. Its answer can only confirm a flow
the CPG already found; it can never conjure one.
Req 8.5 is asserted structurally: a test parses judge.py and fails on any AST
name like k_runs/majority/vote/average/acceptance/floor/budget, any for/while
loop, or an import from the deleted round machinery. That test first matched
the word "votes" in the module's own docstring, which is why it now inspects
code rather than text.
Verified live against a real CPG, not only scripted rows:
vuln rung=model_entailed request.args["name"] -> db.execute(...)
fixed rung=suspicion no source reaches this sink
model calls made: 0
Both sides arbitrated by the graph with the LLM never consulted -- the thing
the prior architecture could not do at any price.
678 passing, mypy/ruff clean, gates byte-identical, zero orphaned modules.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
The whole engine integration is one subprocess boundary: joern-parse builds a
cpg.bin, joern --script runs a shipped CPGQL query that prints its JSON between
fence markers, because Joern's stdout carries a banner and a REPL prompt around
whatever a script emits. Nothing is imported in-process, so the core install
keeps dependencies = [] -- a test walks the seam's AST to assert it imports
only the standard library and names no JVM binding.
Fail closed everywhere. A build or query that errors, times out, or prints
something unparseable yields no verdict and the caller reports suspicion. The
taint verdict distinguishes this from absence deliberately: a query returning
None means "the engine could not decide", which is not "there is no flow", and
conflating them is how a missing engine silently becomes a clean bill of health.
The verdict is where the ladder earns its keep. An unsanitized source->sink
path is model_entailed -- the graph establishes it and the LLM's claim is no
longer load-bearing. A path a sanitizer may break is model_corroborated: the
flow is real, but whether the sanitizer suffices is the semantic residual the
LLM answers, checked against this verdict rather than averaged over runs. The
chosen flow is picked by a total order (shortest, then lexicographic), so two
runs over one CPG cannot disagree -- Req 6.4 asserted directly.
The query itself is the part our flat IR could not do: reachableByFlows walks
the PDG, so `q = "..." + request.args["x"]; execute(q)` is found, which is
exactly the one-hop limit that held measured entailment at 2.2%.
Capability detection reuses semantic/engines.joern_available rather than
growing a second notion of "installed". The audit manifest is regenerated; the
new modules are named by Req 4/5/6 rather than counted as orphans.
Task 2.3, the go/no-go measurement, needs Joern installed and has not run.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
