Governance Stress Surfaces in AI‑Orchestrated DFIR

AI‑orchestrated digital forensics and incident response (DFIR) systems introduce a new class of governance failure modes that operate at the orchestration layer rather than the tool layer. This document identifies seven governance stress surfaces — structural boundaries where AI‑orchestrated DFIR systems are vulnerable to misinterpretation, drift, provenance loss, or irreversible action. These surfaces are conceptual categories, not operational test procedures. They define where governance breaks down without specifying how to test for or exploit those failures. This document is a companion to Governance Primitives for AI‑Orchestrated DFIR (Truong, 2026; DOI: 10.5281/zenodo.18676126).

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Zenodo (CERN European Organization for Nuclear Research)
Published
2026-02-18
DOI
https://doi.org/10.5281/zenodo.18676449
Primary Topic
Digital and Cyber Forensics
Type
article
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article

Governance Stress Surfaces in AI‑Orchestrated DFIR

Narnaiezzsshaa Truong
Zenodo (CERN European Organization for Nuclear Research)
Digital and Cyber Forensics
article

Governance Stress Surfaces in AI‑Orchestrated DFIR

Narnaiezzsshaa Truong
article en

Abstract

AI‑orchestrated digital forensics and incident response (DFIR) systems introduce a new class of governance failure modes that operate at the orchestration layer rather than the tool layer. This document identifies seven governance stress surfaces — structural boundaries where AI‑orchestrated DFIR systems are vulnerable to misinterpretation, drift, provenance loss, or irreversible action. These surfaces are conceptual categories, not operational test procedures. They define where governance breaks down without specifying how to test for or exploit those failures. This document is a companion to Governance Primitives for AI‑Orchestrated DFIR (Truong, 2026; DOI: 10.5281/zenodo.18676126).

Zenodo (CERN European Organization for Nuclear Research)
American Rock Mechanics Association (US)
Peace, Justice and strong institutions
Openalex Percentile: Top 66%
Digital and Cyber Forensics
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