AI Red Team · Module 3 · Identify

Asset Management for an Estate That Includes AI

The lesson treats ID.AM Asset Management for an estate that includes AI. Participants learn the seven asset classes, the minimum record for an AI asset, the discovery sources for each usage mode, AI-assisted classification, matching and enrichment at Level 1 Assisted, reconciliation into match, drift, orphan and unknown, proportionate discovery of shadow AI, and criticality that follows what an asset can do.

Lesson 9 of 28Chapter 975 minutes

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Learning objectives

After the lesson the participant can:

Key concepts

Seven asset classes
AI systems, models, agents, prompts and skills, connectors and tools, data, and security AI, each with its own owner and record. Security AI reads attacker-controlled content by design and often holds privileged access, so it is recorded with the same rigour as the systems it protects.
Last verification
The date and source of the record's last verification. The chapter calls it the field that matters most in practice, because it tells the SOC and the auditor whether the record describes the estate or a memory of it.
Four reconciliation outcomes
A match confirms the record; a drift is an asset in both lists that differs; an orphan is declared but no longer found; an unknown is discovered with no record. An unknown that acts or reads confidential data is escalated to the SOC as a potential security event.
The record as a control
At Hansa Mutual the gateway generates each agent's tool allow-list from its asset record, so a call to any unrecorded connector is refused and logged. The control followed a finding in which a vendor update had added a URL-reputation connector unnoticed.
Criticality by what the asset can do
Five factors decide the tier and the highest sets it: reach, identity, exposure to content an attacker can shape, data, and dependency. A move to Level 3 Bounded, a new write connector or a new source of untrusted input triggers reassessment.

Interactive exercises

Do them here and get feedback at once. Choose a card and then where it belongs, or drag it.

Interactive exercise 1 · Match

Discovery sources and what they reveal

Match each discovery source to the AI use the chapter says it reveals.

Interactive exercise 2 · Scenario

An unknown function in a cloud subscription

Apply the reconciliation rules to a discovery result at Hansa Mutual.

Teaching plan

15 minThe teacher presents what ID.AM asks for when the estate includes AI, the seven classes and the minimum record; participants note which classes their inventory lacks.
15 minMap discovery sources to usage modes and discuss what is proportionate: egress metadata and endpoint inventories versus the content of prompts.
10 minWork through the HM-SEC-001 record and the unexpected connector, from discovery to the closing control and the replay as evidence.
25 minExercise: groups write an asset record for an agent and reconcile it against a supplied list of discovered facts.
10 minGroups report their drifts and unknowns and the tier they assigned; the teacher links the records to SOC enrichment and red-team scoping.

Discussion

  1. Why must the AI register required for governance and the asset inventory required for security be the same list, or two lists reconciled automatically?
  2. The discovery AI itself reads content others control. What design choices keep a crafted resource description from hiding an unregistered agent?
  3. How would you explain to employee representatives the difference between finding assets and judging individuals in shadow AI discovery?

Written exercise

Exercise · 25 minutes

Write and reconcile an asset record for an agent

Write an asset record for an agent in your organisation, or for Hansa Mutual's IT-operations agent, in the structure of the HM-SEC-001 record: identifier, owner, asset class, usage mode, decision record, criticality with the factor that sets it, identity, current autonomy level and stop-path holders, hosting and jurisdiction, models with version, prompts and skills, connectors with access type, untrusted inputs, data classification and last verification. Then take three discovered facts the teacher provides, for example a newer model version, an unlisted connector and an unregistered function calling a model endpoint, classify each as match, drift, orphan or unknown, and set an owner and deadline using the chapter's defaults.

Deliverable: One agent asset record and a reconciliation table of three differences with outcome, owner, deadline and whether the SOC is notified.

Self-test

Choose an answer to see whether it is right, or open the answer below each question.

  1. In reconciliation, what is a drift?

    Show the answer

    B. An asset that exists in both the declared and the discovered inventory but differs
    The chapter defines drift as an asset in both inventories that differs, such as an agent with an unlisted connector or a newer model version than the one approved. An orphan is no longer found; an unknown has no record.

  2. At which autonomy level does the chapter recommend the discovery classifier works by default?

    Show the answer

    D. Level 1 Assisted, drafting proposals with evidence for the owner to confirm
    The discovery AI proposes and a person decides: it has read-only access to the evidence store, no write access to the inventory of record, and Level 1 Assisted is the recommended default.

  3. Why is security AI often tier-0 under the chapter's criticality factors?

    Show the answer

    A. It reads attacker-controlled content by design, sees telemetry estate-wide and may propose containment
    The factors of exposure, data, reach and dependency all apply: if manipulated, a SOC investigation agent can hide an intrusion or disrupt the business.