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Defence Update Pipeline

DefenseUpdatePipeline is the reviewed promotion gate between three experimental hardening surfaces:

  • SelfImprovingGuardLoop proposes calibration or training changes from reviewed feedback
  • ContinualEngine mines recent failures into an adversarial suite and trained adversary scorer
  • DefenseRegistry hot-swaps the active defence only after the review and adversarial gates pass

The pipeline does not train, mine, or approve anything by itself. It checks that an already-created proposal is approved, checks that adversarial mining produced enough cases, checks the held-out score delta, then performs one atomic registry promotion with tenant-safe metadata.

from director_ai.core.defense_genome import DefenseRegistry, DefenseUpdatePipeline

registry = DefenseRegistry()
pipeline = DefenseUpdatePipeline(
    registry=registry,
    min_adversarial_cases=8,
    min_holdout_improvement=0.02,
)

report = pipeline.review_and_promote(
    proposal=approved_guard_loop_proposal,
    evolve_report=continual_engine_report,
    defense=candidate_defence,
    version=2,
    label="defence-v2",
    baseline_score=0.72,
    candidate_score=0.84,
)

Promotion metadata contains identifiers and metrics only:

  • proposal id, proposal type, approval id, manifest id, rollback id
  • continual suite version, mined pattern count, adversarial case count
  • baseline score, candidate score, and held-out delta

Raw prompts, responses, credentials, private evidence text, and tenant payloads remain in their owning stores and are not copied into registry metadata.

Full API

director_ai.core.defense_genome.update_pipeline.DefenseUpdatePipeline 

DefenseUpdatePipeline(*, registry: DefenseRegistry, min_adversarial_cases: int = 1, min_holdout_improvement: float = 0.0)

Promote a candidate defence only after review and adversarial gates.

The pipeline is deliberately narrow: it never trains a model, mines failures, or mutates proposals. It joins the already-reviewed GuardLoopProposal with a ContinualEngine report and then performs one atomic registry promotion if every gate passes.

review_and_promote 

review_and_promote(*, proposal: GuardLoopProposal, evolve_report: EvolveReport, defense: Defense, version: int, label: str, baseline_score: float, candidate_score: float) -> DefenseUpdateReport

Validate review, adversarial evidence, and holdout score, then promote.

director_ai.core.defense_genome.update_pipeline.DefenseUpdateReport dataclass 

DefenseUpdateReport(snapshot: DefenseSnapshot, proposal_id: str, suite_version: int, adversarial_case_count: int, promoted: bool, metadata: dict[str, str] = dict())

Tenant-safe report for one reviewed defence promotion.