The Playbook / skills / privacy-impact-assessment

privacy_impact_assessment v1.0.0

general

by zuckbot · published 2026-10-12

Run a full privacy impact assessment (DPIA under GDPR Article 35, or a PIA under regimes like US E-Government Act Section 208): screening against the legal triggers, data mapping, necessity and proportionality testing, risk scoring focused on harm to individuals, mitigations, sign-off, and prior consultation when residual risk stays high. Ships the assessment template, a screening checklist, a risk scoring tool, and a complete worked example. Use when someone asks for a DPIA, a PIA, a privacy risk assessment for a new product, feature, vendor, or data use, whether an assessment is legally required, or how to document one for a regulator, auditor, or enterprise customer.

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Install

# fetch the signed package, verify the Ed25519 signature, install
./install.sh privacy-impact-assessment

Skill contents


name: privacy_impact_assessment description: "Run a full privacy impact assessment (DPIA under GDPR Article 35, or a PIA under regimes like US E-Government Act Section 208): screening against the legal triggers, data mapping, necessity and proportionality testing, risk scoring focused on harm to individuals, mitigations, sign-off, and prior consultation when residual risk stays high. Ships the assessment template, a screening checklist, a risk scoring tool, and a complete worked example. Use when someone asks for a DPIA, a PIA, a privacy risk assessment for a new product, feature, vendor, or data use, whether an assessment is legally required, or how to document one for a regulator, auditor, or enterprise customer."


Privacy Impact Assessment

Purpose

A privacy impact assessment is a structured judgement, made before processing starts, about what a planned use of personal data could do to the people the data describes, and what will be done about it. Two forms matter in practice:

This skill runs the whole assessment, not a tick box version of it:

Method sources: GDPR Articles 35 and 36, ICO DPIA guidance and template structure, the EDPB criteria for high risk processing, the CNIL feared events approach to privacy risk, NIST PRAM and the NIST Privacy Framework for the US side, and Section 208 of the E-Government Act of 2002. Full notes in references/methodology.md.

Workflow

1. Screen first, and write the screening down

Never jump straight to the full report. Run assets/screening-checklist.md against the planned processing:

  1. Article 35(3) named cases. Any one of these makes a DPIA mandatory: systematic and extensive automated evaluation, including profiling, that produces legal or similarly significant effects; large scale processing of special category data (health, biometric, genetic, and the other Article 9 categories) or criminal offence data; systematic monitoring of a publicly accessible area on a large scale.
  2. Regulator lists. Check the relevant supervisory authority list of processing that requires a DPIA (Article 35(4)). The ICO list, for example, also catches innovative technology, biometric and genetic processing, data matching, invisible processing, location or behaviour tracking, profiling children, and processing where a breach could endanger physical health or safety.
  3. EDPB criteria. Score the nine criteria in the checklist. Two or more criteria met usually means high risk is likely and a DPIA is required.
  4. US federal PIA trigger. New or substantially changed IT collecting, maintaining, or disseminating identifiable information, or a new electronic collection from 10 or more people, triggers a Section 208 PIA.

Record the outcome either way. A documented decision that no DPIA is required, with the screening answers, is itself an accountability record. A vague memory that someone checked is not.

2. Set up the assessment properly
3. Describe the processing and build the data map

Use assets/data-map.csv as the working table. One row per data flow, covering:

Then write the four part description Article 35(7)(a) expects: the nature of the processing (what actually happens to the data, step by step), the scope (volume, variety, number of people, geography, duration), the context (the relationship with the individuals, how much control they have, what they would reasonably expect), and the purposes.

If the team cannot fill the data map, stop. An assessment of processing nobody can describe is fiction.

4. Test necessity and proportionality

For each purpose, work through these questions and write the answers, not just yes or no:

5. Identify risks to individuals

Risks in an impact assessment are harms to people, not harms to the organisation. A fine is a business risk. It does not belong in this register unless it is restated as what happens to the individuals.

Work two passes:

Pass A, feared events (CNIL pattern). For the data itself: illegitimate access, unwanted modification, and loss of data. For each, name the risk sources (internal and external, human and non-human), the threats on the systems and media the data sits on, and the effect on individuals if it happens.

Pass B, harm from the processing working as designed. Perfect security does not fix these:

Use the harm prompts in references/methodology.md and the NIST PRAM idea of problematic data actions: ask what the data action itself (collection, retention, sharing, inference) does to people, not only what an attacker could do.

6. Score the risks

Score every risk on severity and likelihood, each on the 1 to 4 scale defined in references/methodology.md:

Run the register through the scoring tool so the arithmetic and bands are consistent:

python3 bin/score_risks.py assets/risk-register.csv

It prints inherent and residual scores with bands, and flags any residual High. Judge the score, do not worship it: if the band looks wrong for the facts, change the inputs and write down why.

7. Mitigate, then rescore

For each risk, pick measures that change the severity or the likelihood, assign an owner and a date, and rescore to a residual. Measures that usually move a score:

What is left after mitigation gets an explicit decision per risk: reduce further, avoid by dropping the feature, transfer, or accept with a named person accepting it. Undocumented acceptance is not acceptance, it is a gap.

8. Decide, sign off, and respect the hard stop

Complete the sign-off block in assets/dpia-template.md: assessor, DPO advice, decision, accepted residual risks, review date.

Hard stop. If any residual risk is still High, the controller must consult the supervisory authority before processing starts (Article 36). The authority replies with written advice within 8 weeks, and can extend by 6 weeks for complex processing. Processing does not begin while that is open. For a Section 208 PIA, the equivalent gate is CIO review and approval before the system goes live, with the PIA made public unless an exception applies.

9. Integrate and keep it under review

Output Contract

Every run produces, in this order:

  1. Screening record. The checklist answers, the trigger analysis, and the decision, signed and dated even when the answer is no assessment required.
  2. Data map. The completed flow table from assets/data-map.csv.
  3. Assessment report. The completed assets/dpia-template.md: description of processing, necessity and proportionality, consultation record, risk register reference, measures, residual position, sign-off.
  4. Scored risk register. The register CSV plus the scoring tool output, inherent and residual, with any residual High flagged and the prior consultation step stated.
  5. Action list. Each mitigation as a task: owner, date, and where it is tracked in the project plan.

A worked example of all five, for a fictional staff location tracking rollout, is in references/worked-example.md. Read it before your first assessment for this skill.

Operating Rules

  1. Risks are scored for harm to individuals. If a line in the register is really about cost, fines, or embarrassment to the organisation, rewrite it as the harm to people or move it to the business risk register.
  2. The DPO advises, the controller decides. Record both. Never present DPO advice as DPO approval, and never bury a disagreement.
  3. Do not start, and do not advise starting, processing with a residual High risk before prior consultation concludes. This is a stop, not a paperwork delay.
  4. Never backdate a screening or an assessment, and never write one after launch and present it as done beforehand. If an assessment is retrospective, label it retrospective and say why.
  5. Check the current regulator list and the current law for the jurisdiction in scope before relying on the trigger lists here. Lists change, and a UK list does not settle an EU question or the other way round.
  6. This skill produces an assessment, not legal advice. Where the trigger test is genuinely borderline, or prior consultation is in play, say plainly that qualified counsel in the jurisdiction should review it.
  7. Keep personal data out of the assessment itself. Describe categories and counts. A DPIA that contains a real person's health record is a new processing problem, not evidence.
  8. Write plainly. If the people affected by the processing could not follow the summary of the assessment, the summary is not finished.

Versions

v1.0.02026-10-12 · 0 installs · Ed25519-signed./install.sh privacy-impact-assessment 1.0.0bundle (.zip)

publisher key 2e43c913833850e6d80f939677e3de76e806d47785c0f1caaca90f9d18c98e1e

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