AI Red Team · Module 2 · Govern

Organisational Context and Risk Strategy for AI in Cyber Defence

The lesson treats GV.OC Organizational Context and GV.RM Risk Management Strategy for security AI. Participants extend the context record with AI as asset and as adversary capability, write a risk appetite in three dimensions, error, autonomy and reversibility, set autonomy ceilings per usage mode, revise the risk assumptions that AI-enabled threats invalidate, and keep the whole as code with change-triggered review.

Lesson 5 of 28Chapter 575 minutes

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Learning objectives

After the lesson the participant can:

Key concepts

Three dimensions of appetite
For security AI the appetite covers error, autonomy and reversibility. The appetite is a short statement the management body can read; the tolerances are numbers a pipeline can check, measured on the organisation's own evaluation set and not a vendor's benchmark.
Autonomy ceiling
The highest autonomy level that any security AI in a given usage mode may reach without a decision of the management body. Within it the AI governance board or the CISO may raise a level on evidence; above it, a proposal is risk beyond appetite.
Automatic step down
The named action on a breach of error tolerance: the level falls automatically by one until the owner has investigated. The chapter's default is a missed-threat rate of at most 2 per cent for anything at Level 2 Supervised or above.
Recognition is not verification
The revised assumption on synthetic media: for decisions that move money, change payees, reset credentials or approve security exceptions, the strategy requires verification through a channel the requester does not control.
Change-triggered review
The statement names its triggers, such as a new system, a model version change, a mode or level change, an incident, a red-team finding or a supplier change, and the pipeline opens a review when one fires. The calendar backstop only catches triggers the organisation failed to define.

Interactive exercises

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

Interactive exercise 1 · Sort

Earlier and revised risk assumptions

Sort each assumption about the adversary or the tooling: is it the earlier basis or the revised basis in the chapter's table?

Interactive exercise 2 · Scenario

A tolerance breach at Level 3

Apply Hansa Mutual's risk-appetite statement HM-RAS-SECAI to an evaluation result.

Teaching plan

15 minThe teacher presents GV.OC with the four additions to the context record and the obligations table; participants list the security AI their own defence depends on, including ambient features.
15 minWalk through error tolerance, autonomy ceilings and reversibility, using the typical pattern of ceilings per mode and the two fixed limits.
10 minParticipants take the table of revised assumptions and mark which earlier basis their current strategy still rests on.
25 minExercise: groups write a risk-appetite statement for security AI following the seven steps and the Hansa Mutual statement HM-RAS-SECAI.
10 minGroups compare ceilings; the teacher shows how the chaos experiment verifies that a registered system or a supplier notice opens a review within one working day.

Discussion

  1. Why is an appetite that the CISO sets alone incomplete under the provisions of NIS 2 and DORA that the chapter cites?
  2. Hansa Mutual reports the tenth percentile of approval time as a risk indicator. What does it reveal, and what should the organisation do when it falls?
  3. The chapter records security AI as a strategic opportunity under GV.RM-07. How should a management body weigh the risk of using security AI against the risk of not using it?

Written exercise

Exercise · 25 minutes

Write a risk-appetite statement for security AI

For Nordvik Region or your own organisation, follow the practical guide. List the security AI in the context record, including Mode 0 features and a managed security service provider's AI, with usage mode, current level, owner and identity. Classify each one's actions as reversible within minutes on a single target, reversible with effort, or irreversible. State the appetite in one paragraph in terms of consequences, not technology. Set an autonomy ceiling per usage mode with the two fixed limits, set error tolerances for one use case with the step down on breach, and name the review triggers, the time within which a review opens and the calendar backstop.

Deliverable: A risk-appetite statement with an appetite paragraph, fixed limits, ceilings per usage mode, error tolerances for one use case, review triggers and the approving body.

Self-test

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

  1. What does the chapter mean by an autonomy ceiling?

    Show the answer

    C. The highest level security AI in a given mode may reach without a decision of the management body
    The chapter stresses that a ceiling is not the level a system runs at but the limit within which the AI governance board or the CISO may raise a level on evidence.

  2. Why does error tolerance measured only on benign inputs overstate the performance of security AI?

    Show the answer

    A. Because alert content can be crafted to steer the model, so behaviour under attack differs
    The chapter recalls that manipulation through content is a property of the architecture, so the evaluation set needs an adversarial share, which Chapter 13 supplies.

  3. In Hansa Mutual's statement, what does the entity override do?

    Show the answer

    D. It keeps the ceiling at Level 1 Assisted where employee representatives have not yet agreed
    The override keeps the ceiling at Level 1 Assisted in any entity where employee representatives have not yet agreed to a tool that can act on employees' accounts, so one group statement respects national labour law.