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Author SHA1 Message Date
Marius CiepluchandClaude Opus 5 f59e0f5b5a fix(model-grounded-detection): two modelling bugs the first live Joern run exposed
Both were found by running the real engine, and neither was visible offline.

1. A sink was its own sanitizer. The shipped facts mark some sanitizers with a
   *shape* qualifier -- parameterized ("execute(sql, params) binds rather than
   interpolates") and literal_format_arg ("printf with a constant format string
   is safe"). These describe a safe FORM OF THE SINK CALL, not a call that
   cleans a value on the path. Flattening them into the sanitizer list made
   `execute` both the injection sink and its own sanitizer, so every SQL flow
   would have reported as already-clean and nothing could ever be entailed.
   Fixed as a class, not an instance: any fact carrying a shape qualifier is
   excluded from `sanitizers` and kept in `safe_shape_sinks` for the shape test
   task 4.2 will model properly. Fixing only the Python `parameterized` case
   would have left C's entire printf family -- which the generalised test then
   caught immediately.

2. labeled_family lost its deterministic derivation in group 1. The deleted
   classifier resolved a pair's family by declared label, else obligation, else
   mechanism, else CWE, and only asked an LLM when every link failed -- which
   for a labeled corpus was never. Group 1 reduced this to the declared label
   alone, which silently emptied every family whose pairs are labeled by CWE:
   the injection slice went to zero pairs. The chain is restored, still with no
   model call, and the family census again matches the committed entailment
   ceiling exactly (injection 50, memory 176, access_control 8, ...).

Also: the Joern seam now runs in the CPG's own scratch directory, because
`joern --script` writes a `workspace/` beside the working directory and would
otherwise leave one inside the repository being analysed.

The taint query itself was corrected against the live engine: the sink is the
call's ARGUMENTS (data flows into arguments, not into the call node) and
reachableByFlows is called on the sink with the source. With that, the
three-hop chain our flat IR could not resolve is found:
  request.args["cmd"] -> cmd -> "echo " + cmd -> full -> os.system(full)

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
2026-09-08 12:45:42 +02:00
Marius CiepluchandClaude Opus 5 2b973dc0db feat(model-grounded-detection): tasks 2.1-2.2, the Joern seam and the taint verdict
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
2026-09-08 12:23:40 +02:00