What question did this study set out to answer?

The aim is to establish a framework for governance in AI-driven digital forensics and incident response systems.

February 20, 2026Open Access

Governance Primitives for AI‑Orchestrated DFIR

Key Points

The aim is to establish a framework for governance in AI-driven digital forensics and incident response systems.
Defined eight governance primitives essential for AI orchestration in digital forensics and incident response.
Conceptualized a non-operational repository focusing on the vocabulary and categories of governance.
Introduced governance primitives including Lineage Anchoring and Provenance Ledgers.
Outlined a framework to enhance understanding of AI orchestration in digital forensics.

Abstract

A conceptual framework defining the governance categories required for AI‑orchestrated digital forensics and incident response systems operating at machine speed. Defines eight governance primitives — Lineage Anchoring, Hybridization Boundaries, Drift Surfaces, Reversibility Zones, Semantic‑Intent Validation, Provenance Ledgers, Execution Sandboxing, and Operator Sovereignty — as the conceptual vocabulary for an emerging discipline. This repository is intentionally non‑operational: it contains no invariants, algorithms, implementations, or executable logic.

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