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The GDPR Compliance Pack provides 15 production-ready rules based on the EU General Data Protection Regulation, covering consent management, encryption, DPO requirements, data subject rights, and cross-border data transfers. Each rule includes historical fines, breach examples, and GDPR article references.

Rule Categories

Rules are organized into 14 categories aligned with GDPR principles:
Designation, position, and tasks of the DPO.
  • DPO Designation Check (Article 37)
Opt-out mechanisms and lawfulness of marketing communications.
  • Marketing Opt-Out Mechanism (Article 21)
Security of processing and encryption of personal data.
  • At-Rest Encryption Requirement (Article 32)
  • In-Transit Encryption (TLS) (Article 32)
Definition and processing of personal and special category data.
  • Special Category Data Protection (Article 9)
Data protection by design and by default.
  • Privacy by Design Default (Article 25)
Data protection impact assessments (DPIA) and prior consultation.
  • DPIA Requirement Validation (Article 35)
Principles, lawfulness, and conditions of processing.
  • Lawful Basis Documentation (Article 6)
Maintenance of records of processing activities (ROPA).
  • Records of Processing (ROPA) (Article 30)
Right of access by the data subject and information to be provided.
  • Right to Data Access (DSAR) (Article 15)
Right to erasure and restriction of processing.
  • Data Retention Period Enforcement (Article 5)
  • Right to Be Forgotten (Erasure) (Article 17)
Transparency and information provided to data subjects.
Transfers of personal data to third countries or international organizations.
  • Third Country Transfer Basis (Articles 44-49)

Detailed Rule Reference

Severity: CRITICAL
Threshold: Age < 16
Article: 8 — Child’s Consent
What it detects:Flags records where the data subject is under 16 years old (requires parental consent).Conditions:
{ "field": "age", "operator": "less_than", "value": 16 }
Policy Excerpt:
Children’s data requires parental consent.
Historical Context:
  • Average Fine: €345M (TikTok — failing to protect children’s data)
  • Breach Example: Gaming site collecting emails of 12-year-olds without age verification

Encryption

Severity: CRITICAL
Article: 32 — Security of Processing
What it detects:Identifies tables or columns containing personal data that are not encrypted at rest.Conditions:
{ "field": "encrypted", "operator": "equals", "value": false }
Policy Excerpt:
Personal data must be encrypted at rest.
Historical Context:
  • Average Fine: €18M (British Airways breach — lack of security measures)
  • Breach Example: Hospital database leaked patient records because PII was stored in plain text
Severity: HIGH
Article: 32 — Security of Processing
What it detects:Flags data transmission channels where TLS is not enabled (HTTP instead of HTTPS).Conditions:
{ "field": "tls_enabled", "operator": "equals", "value": false }
Policy Excerpt:
Personal data in transit must be encrypted.
Historical Context:
  • Average Fine: €10M (Telecom company — lack of encryption for subscriber data packets)
  • Breach Example: Web form submitting PII via HTTP instead of HTTPS

Personal Data

Severity: CRITICAL
Article: 9 — Processing of Special Categories
What it detects:Flags records containing special category data (health, biometric, political affiliation) that require explicit consent.Conditions:
{ "field": "data_category", "operator": "contains", "value": "special_category" }
Policy Excerpt:
Special category data requires explicit consent.
Historical Context:
  • Average Fine: €35M (H&M case for processing sensitive employee data)
  • Breach Example: Health app sharing biometric data with third parties without specific Art 9 consent

Data Subject Rights

Severity: HIGH
Article: 5(1)(e) — Storage Limitation
What it detects:Identifies records marked for deletion that have exceeded the retention period.Conditions:
{
  "AND": [
    { "field": "deletion_requested", "operator": "equals", "value": true },
    { "field": "created_at", "operator": "exists", "value": null }
  ]
}
Policy Excerpt:
Personal data must not be retained beyond necessary period.
Historical Context:
  • Average Fine: €14.5M (Average for systemic retention failure)
  • Breach Example: Real estate company fined for storing tenant data indefinitely
Severity: MEDIUM
Article: 15 — Right of Access
What it detects:Identifies data that should be retrievable for data subject access requests but is not properly indexed or exportable.Conditions:
{ "field": "is_retrievable", "operator": "equals", "value": false }
Policy Excerpt:
Data subjects have right to access their data.
Historical Context:
  • Average Fine: €1M (Amazon — failing to provide full access to data)
  • Breach Example: SaaS provider unable to export all user data during access request
Severity: HIGH
Article: 17 — Right to Erasure
What it detects:Checks for records marked for deletion but not yet erased (should be deleted within 30 days).Conditions:
{ "field": "deletion_requested", "operator": "equals", "value": true }
Policy Excerpt:
Check for records marked for deletion but not yet erased.
Historical Context:
  • Average Fine: €600k (Google Spain — “Right to be Forgotten” in search results)
  • Breach Example: Bank failed to delete marketing profile after user closed account

Processing & Documentation

Severity: HIGH
Article: 6 — Lawfulness of Processing
What it detects:Flags data processing operations that do not have a documented lawful basis (Consent, Contract, Legal Obligation, etc.).Conditions:
{ "field": "lawful_basis", "operator": "not_exists", "value": null }
Policy Excerpt:
All processing must have documented lawful basis.
Historical Context:
  • Average Fine: €20M (General fine for lack of Art 6 justification)
  • Breach Example: Company processing payroll data without defining a legal basis in their ROPA
Severity: MEDIUM
Article: 30 — Records of Processing Activities
What it detects:Flags processing activities that do not have a corresponding ROPA entry.Conditions:
{ "field": "ropa_entry_exists", "operator": "equals", "value": false }
Policy Excerpt:
Maintain a record of processing activities.
Historical Context:
  • Average Fine: €30k (Incomplete or missing ROPA)
  • Breach Example: Logistics firm unable to provide processing logs during audit

Organizational Requirements

Severity: MEDIUM
Article: 37 — Designation of the DPO
What it detects:Flags organizations processing sensitive data at scale that have not designated a Data Protection Officer.Conditions:
{ "field": "dpo_assigned", "operator": "equals", "value": false }
Policy Excerpt:
Organizations must designate a DPO in specific cases.
Historical Context:
  • Average Fine: €50k (Average for failing to appoint DPO when required)
  • Breach Example: Security firm fined for not appointing DPO despite large-scale monitoring
Severity: HIGH
Article: 35 — Data Protection Impact Assessment
What it detects:Flags high-risk processing activities (e.g., facial recognition, large-scale profiling) that lack a completed DPIA.Conditions:
{ "field": "dpia_completed", "operator": "equals", "value": false }
Policy Excerpt:
Impact assessment required for high-risk processing.
Historical Context:
  • Average Fine: €200k (Failing to conduct DPIA for facial recognition)
  • Breach Example: Retailer deploying AI tracking without preliminary impact study

Marketing & Privacy Design

Severity: MEDIUM
Article: 21 — Right to Object
What it detects:Checks that all marketing communications include a one-click unsubscribe mechanism.Conditions:
{ "field": "marketing_consent", "operator": "equals", "value": true }
Policy Excerpt:
Email communications require opt-out mechanism.
Historical Context:
  • Average Fine: €400k (Deliveroo — lack of opt-out in promotional emails)
  • Breach Example: E-commerce site ignoring unsubscribes for its weekly newsletter
Severity: MEDIUM
Article: 25 — Privacy by Design
What it detects:Flags systems that do not use maximum privacy settings by default (e.g., profiles set to “public” on registration).Conditions:
{ "field": "privacy_by_default", "operator": "equals", "value": false }
Policy Excerpt:
Implement data protection by design and default.
Historical Context:
  • Average Fine: €100k (Software vendor — settings not private by default)
  • Breach Example: Social app making profiles public automatically upon registration

Cross-Border Transfers

Severity: CRITICAL
Article: 44–49 — Transfers to Third Countries
What it detects:Flags data transfers to countries outside the EEA that lack a valid legal basis (Standard Contractual Clauses, Adequacy Decision, etc.).Conditions:
{ "field": "transfer_basis", "operator": "not_exists", "value": null }
Policy Excerpt:
Transfers to third countries require legal basis.
Historical Context:
  • Average Fine: €1.2B (Meta — transferring data to US without valid basis)
  • Breach Example: Cloud provider moving backup data to non-compliant region

Rule Summary Table

Rule IDNameSeverityArticleCategory
GDPR-001Data Retention Period EnforcementHIGH5(1)(e)Right to be Forgotten
GDPR-002Consent Status ValidationCRITICAL6(1)(a)Consent
GDPR-003At-Rest Encryption RequirementCRITICAL32Encryption
GDPR-004Special Category Data ProtectionCRITICAL9Personal Data
GDPR-005Right to Data Access (DSAR)MEDIUM15Right of Access
GDPR-006Right to Be Forgotten (Erasure)HIGH17Right to be Forgotten
GDPR-007Children Data ProtectionsCRITICAL8Consent
GDPR-008Marketing Opt-Out MechanismMEDIUM21Email Marketing
GDPR-009Lawful Basis DocumentationHIGH6Processing
GDPR-010In-Transit Encryption (TLS)HIGH32Encryption
GDPR-011DPO Designation CheckMEDIUM37DPO
GDPR-012DPIA Requirement ValidationHIGH35Privacy Impact Assessment
GDPR-013Records of Processing (ROPA)MEDIUM30ROPA
GDPR-014Privacy by Design DefaultMEDIUM25Privacy by Design
GDPR-015Third Country Transfer BasisCRITICAL44–49Third Countries

Using the GDPR Pack

  1. Select GDPR Framework — Choose “GDPR” when creating a new audit
  2. Review Rules — All 15 rules are loaded and active by default
  3. Toggle Rules — Disable any rules not applicable to your data processing activities
  4. Upload Data — Upload your dataset (must include fields like consent_status, encrypted, age, etc.)
  5. Confirm Mapping — Approve the AI-suggested column mappings
  6. Run Scan — Execute the compliance scan
  7. Review Violations — Violations include GDPR article references, historical fines, and remediation steps
All GDPR rules use deterministic logic — no AI models are used during enforcement. Explanations reference specific GDPR articles and are generated from templates.

Next Steps

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SOC2 Compliance Pack

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Custom PDF Upload

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Explainability

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