Commit Graph

4 Commits

Author SHA1 Message Date
Benjamin Admin 77459d06d6 fix(onboarding): apply hypothesis/vocabulary review decisions (ISO13485, patch-policy rationale, summary)
Two reviewed knowledge decisions (2026-06-28) + the deferred cosmetic counter, before #59.

1. ISO13485 removed from the incident_management hypothesis. ISO 13485 CAPA / quality-safety incident
   handling is NOT security incident management — the mapping was too broad and would seed false
   hypotheses for the empirical loop. A dedicated manage_quality_and_safety_incidents capability can come
   later IF a target needs it; not forced now. (ISO27001/TISAX/IEC62443 keep incident_management.)

2. patch_policy_doc -> secure_signed_update_distribution stays `partial`, but the curated rationale is
   sharpened: "indicates update governance, does not evidence signed distribution" (a patch policy is not
   proof of SIGNED distribution). New optional SignalMapping.rationale field carries the curated note.
   (github_actions_ci -> SDL and dependency_scanning -> vuln-mgmt reviewed and APPROVED as-is.)

3. Cosmetic (folded in since we touched the file): the silent-intake summary now counts detected and
   indications SEPARATELY ("N automatisch erkannt, M Indikation(en)") instead of lumping partial signals
   into "automatisch erkannt" — consistent with the three-state model just shipped.

Tests: ISO13485 no longer resolves to incident_management; summary counts split correctly. 29 onboarding
tests pass, mypy --strict clean, demo runs, check-loc 0. Runtime-visible (hypothesis resolution + summary
text) -> deploy + smoke.
2026-06-28 16:18:28 +02:00
Benjamin Admin 978052b5a2 fix(onboarding): decouple partial/indicative signals from detected — partial no longer removes a question
Fix B of the pre-#59 semantic correction. The Silent Pass had only TWO effective states though the data
carries three: a `detected` mapping (a concrete artifact) AND a `partial` mapping (an indicative signal,
e.g. a CI pipeline -> secure-development-lifecycle) both flowed through capability_ids() and were fed to
the Advisor as already-present — so a weak indication silently removed a question, exactly the Welt-1/
Welt-2 transparency we want to keep.

Now three distinct states:
  - detected   -> reduces the delta immediately (auto_detected, not asked).   [unchanged]
  - partial    -> raises assumption strength but does NOT replace the question (surfaced as `indications`,
                  the capability stays in the delta and is still asked).
  - requirement-> describes a target, never the present state (already handled by Fix A's kind split).

Changes (data + thin wiring, no new architecture):
  - SilentIntakeResult.capability_ids() returns only relationship==detected; new indicative_capability_ids()
    returns the partial ones.
  - advisor_start() gains indicative_capabilities (NOT fed into the profile) and surfaces result.indications
    = indicative ∩ required − auto_detected.
  - AdvisorResult / AdvisorResponse gain `indications` (additive, contract-safe); the service passes the
    indicative ids through.

Tests: a partial CI signal is indicative-not-detected and does NOT shrink the delta; end-to-end it appears
in `indications`, not `auto_detected`, and the gap is still asked. 28 onboarding tests pass, mypy --strict
clean on the onboarding modules, demo runs, check-loc 0. Runtime effect -> deploy + smoke.
2026-06-28 16:02:35 +02:00
Benjamin Admin c39787ad96 fix(onboarding): separate observation vs requirement signals — a demanded SBOM is not a present SBOM
Semantic correction of the knowledge base BEFORE the empirical loop (#59) is built — otherwise the
Observation Store would learn from already-misclassified signals. The Silent Pass conflated two kinds of
signal into one: an OBSERVATION ("I saw an SBOM in the repo") and a REQUIREMENT ("a tender DEMANDS an
SBOM"). They were aliased to the same canonical id, so a tender clause read as "SBOM already present" and
suppressed the very question that should have been asked.

Fix — make the kind explicit and authoritative (no new architecture, data + thin wiring):
  - `kind` ∈ {observation, requirement} on ProducedSignal (producer may declare) and on the canonical
    SignalVocabularyEntry (AUTHORITATIVE — a mislabelled producer cannot collapse the two).
  - Vocabulary split: sbom_file_found → sbom_present (obs) + sbom_required (req);
    security_txt_or_cvd_policy → cvd_policy_present (obs) + psirt_required (req); add signed_updates_required.
    requirement signals are intentionally UNMAPPED in intake_signal_map (they describe a target, not state).
  - silent_intake() consumes ONLY kind==observation; requirement signals are preserved in
    `requirements_seen` (visible/auditable) but NEVER become a detected capability.
  - normalize_signals() stamps the vocabulary's kind onto every IntakeSignal; unknown ids still pass through.

This is the same Observation-vs-Requirement split the Requirements Verification Platform rests on:
observations are reality, requirements are targets, and their comparison is the delta. A tender / OEM spec /
law now produces requirement signals; scanners / repos / documents produce observation signals.

Tests: rewrote the two test_signal_producer cases that previously ASSERTED the bug (tender == repo) to pin
the correct split; regression — `requires_sbom` yields no capability + stays in requirements_seen while
`cyclonedx_found` still detects sbom_creation; endpoint-level regression that a tender requirement does not
auto-detect and the gap stays asked; vocabulary-kind-overrides-mislabelled-producer. 25 onboarding tests
pass, mypy --strict clean, demo runs, check-loc 0. Runtime effect → deploy + smoke. (Fix A; partial-vs-
detected decoupling follows as Fix B before #59.)
2026-06-28 15:52:50 +02:00
Benjamin Admin 9c33582412 feat: Silent Knowledge Pass — recognise before asking (Phase 0, before the endpoint)
Not the endpoint yet — the bigger knowledge lever first. The Advisor can say "I need 5 answers" but
does not yet decide what it can find out by ITSELF. The Silent Knowledge Pass runs in front of the
Advisor and, from signals existing scanners/parsers already produce (website, repository, documents,
product data), deterministically derives capabilities the company demonstrably HAS + product facts
that drive scope — so every recognised item shrinks the delta and removes a question.

compliance/onboarding/silent_intake.py: silent_intake(signals, signal_map) -> detected_capabilities
(+ evidence already in hand) + product_facts. The signal->conclusion map is curated DATA
(knowledge/onboarding/intake_signal_map.yaml), signals are injected (scanners are upstream). Pure,
deterministic, no LLM. advisor_start gains detected_capabilities (folded into the profile at HIGH
confidence -> covered, not asked) and an auto_detected result + headline.

The experience flips from a question wall to "we already recognised 4 capabilities, 2 product facts
and have 4 pieces of evidence in hand — only these few remain". Order now: Silent Pass -> #58
endpoint/frontend -> #59 empirical loop. NOT new architecture, just an orchestration step in front.
Non-runtime (no app caller) -> no deploy. 15 onboarding tests pass, mypy --strict clean, check-loc 0.
2026-06-28 14:34:27 +02:00