Data_Classification_Policy.md

May 24, 2026 · View on GitHub

🏷️ Hack23 AB — Data Classification Policy

🛡️ Systematic Information Handling Through Classification-Driven Protection
🎯 Enterprise-Grade Data Security Demonstrating Cybersecurity Excellence

📋 Document Owner: CEO | 📄 Version: 2.3 | 📅 Last Updated: 2026-01-25 (UTC)
🔄 Review Cycle: Annual | ⏰ Next Review: 2027-01-25

🎯 Purpose Statement

🏢 Hack23 AB's data classification policy demonstrates how 🔧 systematic information handling directly enables both security excellence and operational transparency. Our 📊 classification-driven data protection serves as both operational necessity and 👥 client demonstration of our cybersecurity consulting methodologies.

This policy establishes comprehensive data classification and handling requirements based on our 🏷️ Classification Framework, ensuring information protection aligns with business value, regulatory obligations, and security objectives. Our 🌟 transparent approach to data classification showcases how methodical information management creates 🏆 competitive advantage through protected innovations and 🤝 customer trust via demonstrable privacy controls.

— 👨‍💼 James Pether Sörling, CEO/Founder

🔍 Purpose & Scope

Purpose

This policy establishes the framework for classifying, labeling, handling, and protecting all information assets at Hack23 AB, ensuring appropriate security controls are applied based on business impact, regulatory requirements, and organizational risk appetite.

Scope

This policy applies to:

All information in any format (digital, physical, verbal)
All systems documented in 💻 Asset Register
All data processed by applications and services
All information shared with third parties per 🤝 Third Party Management
All employees, contractors, and authorized users

Framework Integration

This policy implements the comprehensive classification methodology defined in 🏷️ Classification Framework, covering:

CIA Triad Assessment: Confidentiality, Integrity, and Availability requirements
Business Impact Analysis: Financial, operational, reputational, and regulatory impact
RTO/RPO Classifications: Recovery time and recovery point objectives
Risk Classifications: Systematic risk level determination

🏗️ Data Classification Framework Architecture

📊 Classification Methodology Integration

Our data classification directly implements the 🏷️ Classification Framework methodology:

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flowchart TD
    subgraph CIA["🔐 CIA Triad Assessment"]
        CONF["🔒 Confidentiality<br/>Public to Extreme"]
        INTEG["✅ Integrity<br/>Low to Critical"]
        AVAIL["⚡ Availability<br/>Standard to Mission Critical"]
    end
    
    subgraph IMPACT["📊 Business Impact Analysis"]
        FIN["💰 Financial Impact<br/>Negligible to Very High"]
        OPS["⚙️ Operational Impact<br/>No Impact to Critical"]
        REP["🤝 Reputational Impact<br/>No Impact to Critical"]
        REG["⚖️ Regulatory Impact<br/>No Impact to Critical"]
    end
    
    subgraph RECOVERY["🔄 Recovery Requirements"]
        RTO["⏰ Recovery Time<br/>Instant to Standard"]
        RPO["💾 Recovery Point<br/>Zero Loss to Extended"]
    end
    
    subgraph CONTROLS["🛡️ Security Controls"]
        ENCRYPTION["🔒 Encryption Level"]
        ACCESS["🔑 Access Control"]
        MONITORING["📊 Monitoring Level"]
        BACKUP["💾 Backup Strategy"]
    end
    
    CONF --> ENCRYPTION
    INTEG --> MONITORING
    AVAIL --> BACKUP
    FIN --> ACCESS
    OPS --> BACKUP
    REP --> MONITORING
    REG --> ACCESS
    RTO --> BACKUP
    RPO --> BACKUP
    
    style CIA fill:#1565C0
    style IMPACT fill:#4CAF50
    style RECOVERY fill:#FF9800
    style CONTROLS fill:#7B1FA2

🎯 Data Classification Levels

Based on 🏷️ Classification Framework confidentiality levels:

Business Justification	Example Data Types	Handling Requirements
Catastrophic damage if disclosed	HSM keys, critical authentication tokens	Hardware security modules, air-gapped systems
Severe business impact	Financial data, customer PII, security configurations	AES-256 + CMK, strict access control, audit logging
Significant business impact	Source code, business plans, internal communications	AES-256 encryption, role-based access, monitoring
Moderate business impact	System logs, operational metrics, vendor agreements	Standard encryption, basic access control
Minor business impact	Public documentation drafts, general communications	Basic protection, standard access
No confidentiality requirement	Marketing materials, public policies, open source code	Public disclosure appropriate, integrity protection

🔐 CIA Triad Implementation

🔒 Confidentiality Requirements

Implementation of confidentiality controls per 🏷️ Classification Framework:

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graph TD
    subgraph EXTREME["🔴 Extreme Classification"]
        HSM["🔐 Hardware Security Modules"]
        AIRGAP["🏝️ Air-Gapped Systems"]
        BIOMETRIC["👁️ Biometric Authentication"]
    end
    
    subgraph VERYHIGH["🔵 Very High Classification"]
        CMK["🔑 Customer Managed Keys"]
        MFA["🛡️ Multi-Factor Authentication"]
        AUDIT["📋 Comprehensive Audit Logging"]
    end
    
    subgraph HIGH["🟡 High Classification"]
        AES256["🔒 AES-256 Encryption"]
        RBAC["👥 Role-Based Access Control"]
        MONITORING["📊 Activity Monitoring"]
    end
    
    subgraph MODERATE["🟠 Moderate Classification"]
        STANDARD["🔐 Standard Encryption"]
        BASIC["🔑 Basic Access Control"]
        LOGGING["📝 Standard Logging"]
    end
    
    subgraph LOW["🟢 Low/Public Classification"]
        MINIMAL["🔓 Minimal Protection"]
        INTEGRITY["✅ Integrity Verification"]
        PUBLIC["🌟 Public Disclosure Ready"]
    end
    
    style EXTREME fill:#D32F2F
    style VERYHIGH fill:#1565C0
    style HIGH fill:#FF9800
    style MODERATE fill:#FFC107
    style LOW fill:#4CAF50

Confidentiality Control Matrix

Classification	Access Control	Encryption	Authentication	Monitoring	Retention
Extreme	Need-to-know only, hardware tokens	HSM-based, quantum-resistant prep	Hardware MFA + biometrics	Real-time alerts, tamper detection	Secure destruction, legal hold
Very High	Strict RBAC, manager approval	AES-256 + CMK, key rotation	Hardware MFA required	Comprehensive logging, SIEM alerts	Encrypted archives, compliance retention
High	Role-based, documented justification	AES-256, managed keys	MFA required	Activity monitoring, periodic review	Standard retention, secure deletion
Moderate	Group-based, supervisor approval	Standard encryption	Platform authentication	Basic monitoring, log retention	Business retention, standard deletion
Low	General access, self-service	Minimal encryption	Standard authentication	Minimal monitoring	Standard retention
Public	Open access appropriate	Integrity protection only	No authentication required	Optional logging

✅ Integrity Requirements

Data integrity controls aligned with 🏷️ Classification Framework:

Integrity Level Matrix

Control Requirements	Implementation	Validation Frequency
Immutable storage, digital signatures, real-time validation	Blockchain/tamper-evident systems	Continuous
Checksums, version control, audit trails	Database constraints, change logging	Daily
Basic validation, backup verification	File integrity monitoring	Weekly
Standard backup, basic validation	Standard file systems	Monthly

⚡ Availability Requirements

Availability controls per 🏷️ Classification Framework:

Availability Level Implementation

Uptime Target	Architecture	Backup Strategy	Recovery Testing
99.99%+	Multi-region, active-active	Real-time replication	Monthly
99.9%	Multi-AZ, load balanced	Hourly backups	Quarterly
99.5%	Standard redundancy	Daily backups	Semi-annual
99%	Basic deployment	Weekly backups	Annual
Best effort	Single instance	Manual backups	As needed

📊 Business Impact-Driven Classification

💰 Financial Impact Classifications

Based on 🏷️ Classification Framework:

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pie title 💰 Financial Impact Distribution by Data Category
    "Very High (>\$10K/day)" : 15
    "High (\$1K-5K/day)" : 25
    "Moderate (\$500-1K/day)" : 30
    "Low (<\$500/day)" : 20
    "Negligible" : 10

Financial Impact Control Requirements

Example Data Types	Protection Requirements	Incident Response
Banking credentials, payment processing data	HSM encryption, real-time monitoring	Immediate escalation, executive notification
Customer financial data, accounting records	Strong encryption, audit logging	<15 min response, stakeholder notification
Vendor contracts, pricing information	Standard encryption, access control	<1 hour response, management notification
General business correspondence	Basic protection	<4 hour response
Public information, marketing materials	Integrity protection only	Standard process

⚙️ Operational Impact Classifications

Implementation per 🏷️ Classification Framework:

Operational Impact Control Matrix

Service Disruption	Data Requirements	Recovery Priority
Complete service failure	Mission-critical systems data	Immediate recovery, all resources
Significant functionality loss	Core business process data	High priority, dedicated resources
Limited functionality impact	Supporting system data	Standard priority, available resources
Minor inconvenience	Non-essential system data	Low priority, scheduled recovery
No operational effect	Archive/reference data	Best effort recovery

🤝 Reputational Impact Classifications

Reputational protection per 🏷️ Classification Framework:

Reputational Impact Response Matrix

Exposure Risk	Communication Requirements	Media Response
Global media attention	Executive spokesperson, PR firm	Proactive media strategy
National news coverage	Official statement, customer notification	Reactive media response
Industry publication coverage	Stakeholder communication	Industry engagement
Limited public awareness	Internal communication	Monitor discussion
No reputational risk	Standard processes	No special action

⚖️ Regulatory Impact Classifications

Compliance requirements per 🏷️ Classification Framework:

Regulatory Impact Compliance Matrix

Legal Consequences	Compliance Actions	Reporting Requirements
Criminal prosecution risk	Legal counsel, immediate remediation	Mandatory breach notification, regulatory reporting
Significant financial penalties	Compliance review, process improvement	Formal reporting, corrective action plans
Administrative penalties	Policy review, staff training	Standard reporting, documentation
Warning notices	Process documentation	Routine compliance checks
No regulatory implications	Standard processes	No special requirements

🔄 Recovery Time and Point Objectives

⏰ RTO Classifications Implementation

Based on 🏷️ Classification Framework:

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gantt
    title ⏰ RTO Classification Timeline
    dateFormat X
    axisFormat %s
    
    section Critical
    Instant (0-5min)    :done, instant, 0, 5
    Critical (5-60min)  :done, critical, 0, 60
    
    section High Priority
    High (1-4hrs)       :active, high, 0, 240
    
    section Standard
    Medium (4-24hrs)    :medium, 0, 1440
    Low (24-72hrs)      :low, 0, 4320
    Standard (>72hrs)   :standard, 0, 10080

RTO Implementation Requirements

Technical Architecture	Staffing	Testing Frequency
Active-active, automatic failover	24/7 on-call	Weekly
Hot standby, rapid activation	On-call response	Monthly
Warm standby, documented procedures	Business hours response	Quarterly
Cold backup, standard recovery	Standard business processes	Semi-annual
Backup restoration, planned recovery	Scheduled maintenance	Annual
Best effort recovery	As resources available	As needed

💾 RPO Classifications Implementation

Based on 🏷️ Classification Framework:

RPO Data Protection Matrix

Backup Frequency	Replication Method	Validation
Synchronous replication	Real-time mirroring	Continuous
Every 15 minutes	Asynchronous replication	Real-time monitoring
Every hour	Log shipping	Hourly validation
Daily snapshots	Scheduled backups	Daily verification
Weekly/monthly	Archive backups	Periodic testing

🛡️ Data Handling Procedures

📋 Classification Process Workflow

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flowchart TD
    START["📝 Data Creation/Receipt"] --> IDENTIFY["🔍 Data Identification"]
    IDENTIFY --> CIA_ASSESS["🔐 CIA Assessment"]
    CIA_ASSESS --> IMPACT_ASSESS["📊 Business Impact Assessment"]
    IMPACT_ASSESS --> RECOVERY_ASSESS["🔄 Recovery Assessment"]
    RECOVERY_ASSESS --> CLASSIFY{"🏷️ Classification Decision"}
    
    CLASSIFY -->|Extreme/Very High| CRITICAL_HANDLE["🔴 Critical Handling"]
    CLASSIFY -->|High/Moderate| STANDARD_HANDLE["🟡 Standard Handling"]
    CLASSIFY -->|Low/Public| BASIC_HANDLE["🟢 Basic Handling"]
    
    CRITICAL_HANDLE --> LABEL["🏷️ Apply Labels"]
    STANDARD_HANDLE --> LABEL
    BASIC_HANDLE --> LABEL
    
    LABEL --> CONTROLS["🛡️ Apply Controls"]
    CONTROLS --> MONITOR["📊 Monitor & Review"]
    MONITOR --> REVIEW{"🔍 Periodic Review"}
    
    REVIEW -->|Changes Required| IDENTIFY
    REVIEW -->|No Changes| CONTINUE["✅ Continue Current Classification"]
    
    style START fill:#1565C0
    style CLASSIFY fill:#FFC107
    style CRITICAL_HANDLE fill:#D32F2F
    style STANDARD_HANDLE fill:#FF9800
    style BASIC_HANDLE fill:#4CAF50

🏷️ Labeling Standards

Digital Data Labeling

All digital files and databases must include classification metadata:

Classification_Metadata:
  confidentiality: "Very High"
  integrity: "High" 
  availability: "Mission Critical"
  financial_impact: "High"
  operational_impact: "Critical"
  reputational_impact: "Moderate"
  regulatory_impact: "High"
  rto: "Critical"
  rpo: "Near Real-time"
  owner: "James Pether Sörling"
  classification_date: "2025-08-31"
  review_date: "2026-08-31"
  retention_period: "7 years"
  legal_hold: false

Physical Document Labeling

Physical documents require clear classification markings:

Classification	Header/Footer Marking	Color Code	Handling Instructions
Extreme	`EXTREME - HSM ONLY`	Black	Hardware security required
Very High	`VERY HIGH CONFIDENTIAL`	Dark Blue	Restricted access, MFA required
High	`HIGH CONFIDENTIAL`	Blue	Controlled access, authorization required
Moderate	`MODERATE CONFIDENTIAL`	Orange	Standard business controls
Low	`LOW CONFIDENTIAL`	Yellow	Basic protection required
Public	`PUBLIC` or no marking	Green	Public disclosure appropriate

📦 Data Storage Requirements

Storage Controls by Classification

Classification	Storage Location	Encryption	Access Control	Backup Requirements
Extreme	Air-gapped systems, HSM	Hardware encryption	Biometric + token	Real-time mirroring
Very High	Encrypted cloud storage	AES-256 + CMK	MFA + approval	Cross-region replication
High	Secure cloud storage	AES-256	MFA required	Daily encrypted backups
Moderate	Standard cloud storage	Service encryption	RBAC	Standard backups
Low	Standard storage	Basic encryption	Group access	Weekly backups
Public	Public repositories	Integrity protection	Open access	Version control

🔄 Data Transmission Security

Transmission Controls Matrix

Classification	Transport Method	Encryption	Authentication	Logging
Extreme	Secure courier, air-gapped transfer	Physical security	Chain of custody	Complete audit trail
Very High	TLS 1.3, secure channels	End-to-end encryption	Certificate + MFA	Comprehensive logging
High	TLS 1.2+, VPN	Transport encryption	Certificate authentication	Standard logging
Moderate	TLS, secure protocols	Standard encryption	Platform authentication	Basic logging
Low	Standard protocols	Basic encryption	Standard authentication	Minimal logging
Public	Any method	Integrity protection	No authentication required	Optional logging

🗑️ Data Retention and Disposal

Retention Schedule by Data Type

Data Category	Legal Requirement	Business Need	Total Retention	Disposal Method
Financial Records	7 years (Swedish law)	7 years	7 years	Secure deletion, certificate
Customer Data	GDPR retention limits	Business relationship + 2 years	Per GDPR	GDPR-compliant deletion
Employee Records	3 years post-employment	5 years	5 years	Secure deletion
Contracts	Contract term + 7 years	Contract term + 7 years	Statute of limitations	Secure archiving
Security Logs	1 year minimum	3 years	3 years	Automated purging
Operational Data	No requirement	2 years	2 years	Standard deletion
Public Information	No requirement	Indefinite	Indefinite	No special disposal

Secure Disposal Procedures

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flowchart LR
    subgraph DIGITAL["💾 Digital Data Disposal"]
        CRYPTO["🔒 Cryptographic Erasure"]
        OVERWRITE["📝 Multi-Pass Overwrite"]
        PHYSICAL["🔨 Physical Destruction"]
    end
    
    subgraph PHYSICAL_DOC["📄 Physical Document Disposal"]
        SHRED["🗃️ Cross-Cut Shredding"]
        INCINERATE["🔥 Incineration"]
        PULP["♻️ Pulping"]
    end
    
    subgraph VERIFICATION["✅ Disposal Verification"]
        CERTIFICATE["📜 Disposal Certificate"]
        AUDIT["📋 Audit Trail"]
        COMPLIANCE["⚖️ Compliance Check"]
    end
    
    CRYPTO --> CERTIFICATE
    OVERWRITE --> CERTIFICATE
    PHYSICAL --> CERTIFICATE
    SHRED --> AUDIT
    INCINERATE --> AUDIT
    PULP --> AUDIT
    
    CERTIFICATE --> COMPLIANCE
    AUDIT --> COMPLIANCE
    
    style DIGITAL fill:#1565C0
    style PHYSICAL_DOC fill:#4CAF50
    style VERIFICATION fill:#FF9800

📋 Comprehensive Records Retention Matrix

Implementation of ISO 27001 A.5.33 (Protection of records) with systematic retention management:

Business Records Retention Schedule

Record Type	Category	Legal Basis	Business Retention	Total Retention	Storage Location	Disposal Method
📊 Financial Statements	Financial	Swedish Bookkeeping Act	7 years	7 years	Bokio + AWS Backup	Secure deletion + certificate
💰 Invoices & Receipts	Financial	Swedish Bookkeeping Act	7 years	7 years	Bokio + AWS Backup	Secure deletion + certificate
🏦 Bank Statements	Financial	Swedish Bookkeeping Act	7 years	7 years	SEB + AWS Backup	Secure deletion
📜 Tax Returns	Tax	Swedish Tax Agency requirements	7 years	10 years	Bokio + AWS Backup	Secure deletion + certificate
💳 Payment Records	Financial	PCI DSS + Swedish law	7 years	7 years	Stripe + AWS Backup	Secure deletion
📑 Contracts	Legal	Contract terms + Swedish law	Term + 7 years	As specified	AWS S3 encrypted	Secure deletion
👥 Employee Records	HR	Swedish labor law	3 years post-employment	5 years	Internal systems	Secure deletion
🔐 Access Logs	Security	ISO 27001 + NIS2	1 year minimum	3 years	AWS CloudTrail	Automated purging
🚨 Incident Reports	Security	ISO 27001 + NIS2	3 years	5 years	Incident response system	Secure archiving
📧 Email (Business)	Communication	GDPR + business need	2 years	3 years	AWS WorkMail	Standard deletion
📧 Email (Legal)	Legal	Statute of limitations	7 years	7 years	AWS WorkMail archive	Secure deletion
🔑 Credentials/Secrets	Security	Immediate rotation policy	90 days	1 year (audit)	AWS Secrets Manager	Cryptographic erasure
📝 Meeting Minutes	Governance	Companies Act	Permanent	Permanent	Internal systems	N/A - permanent record
🎫 Support Tickets	Operations	Business need	3 years	3 years	Support system	Standard deletion
📊 Compliance Evidence	Compliance	ISO 27001 + regulatory	3 years	7 years	Compliance management system	Secure archiving
🏗️ Architecture Docs	Technical	Business need	Active + 2 years	5 years	GitHub + AWS S3	Standard deletion
📚 Public Documentation	Public	No requirement	Indefinite	Indefinite	GitHub Pages	Version control only

Data Types	Legal Basis	Retention Period	Review Trigger	Disposal Action
Contact info, usage data	Art. 6(1)(f) Legitimate Interest	12-24 months after last activity	Inactivity + annual review	Standard secure deletion
Employee personal data	Art. 6(1)(b) Contract	3 years post-employment	Termination + period end	GDPR-compliant deletion + certificate
Financial data with PII	Art. 6(1)(c) Legal Obligation	7 years (Swedish law)	Legal retention expiry	Secure deletion + audit trail
Publicly shared info	Art. 6(1)(a) Consent	Until consent withdrawn	Withdrawal request	Standard deletion

Retention Implementation Procedures

Automated Retention Management:

AWS Backup Lifecycle Policies: Automatic transition to cold storage and deletion
S3 Lifecycle Rules: Automated expiration of temporary data
CloudWatch Logs Retention: Configured per log group based on retention matrix
Database Backups: Automated expiration per AWS Backup vault policies

Manual Review Triggers:

Annual Review: Q1 review of all retention policies against legal changes
Regulatory Updates: Ad-hoc review when laws change (GDPR, NIS2, CRA)
Incident-Driven: Review after data breaches or audit findings
Business Changes: Review when asset ownership or classification changes

Disposal Verification:

Deletion Certificates: Generated for High+ classified data disposal
Audit Trail: CloudTrail logs retain disposal actions for 3 years
Compliance Review: Quarterly verification of disposal procedures

🎭 Data Masking and Tokenization

Implementation of ISO 27001 A.8.11 (Data masking) for production data protection in non-production environments:

Data Masking Strategy

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flowchart TD
    PROD["🔒 Production Data<br/>Sensitive Information"]
    
    subgraph MASKING["🎭 Masking Techniques"]
        STATIC["📝 Static Masking<br/>Permanent replacement"]
        DYNAMIC["⚡ Dynamic Masking<br/>Runtime obfuscation"]
        TOKENIZE["🔑 Tokenization<br/>Reversible substitution"]
    end
    
    subgraph ENVIRONMENTS["🧪 Target Environments"]
        DEV["💻 Development<br/>Fully masked"]
        TEST["🧪 Testing<br/>Format-preserved"]
        STAGE["📊 Staging<br/>Realistic but fake"]
        ANALYTICS["📈 Analytics<br/>Anonymized"]
    end
    
    PROD --> STATIC
    PROD --> DYNAMIC
    PROD --> TOKENIZE
    
    STATIC --> DEV
    DYNAMIC --> TEST
    TOKENIZE --> STAGE
    STATIC --> ANALYTICS
    
    style PROD fill:#D32F2F
    style MASKING fill:#1565C0
    style ENVIRONMENTS fill:#4CAF50

Masking Rules by Data Type

Data Type	Masking Method	Format Preservation	Example Transformation	Use Case
Email Addresses	Static + Format	Yes	user@example.com → test123@example.com	Development/Testing
Names	Dictionary Replacement	No	"John Smith" → "Jane Wilson"	Realistic test data
Phone Numbers	Randomization + Format	Yes	+46701234567 → +46709876543	Format validation testing
Credit Cards	Tokenization	Yes (Luhn-valid)	4532-1234-5678-9010 → 4532---TEST	Payment testing
Swedish Personal Numbers	Format-preserved random	Yes	19850315-1234 → 19900101-0000	Identity validation
IP Addresses	Subnet preservation	Partial	192.168.1.100 → 192.168.255.XXX	Network testing
Financial Amounts	Range-preserved random	Yes	12,345.67 SEK → Random 1,000-99,999	Financial calculations
Addresses	Dictionary replacement	No	Real address → Fake but valid address	Shipping logic testing
Passwords/Secrets	Never copied	N/A	Excluded from non-prod	Security compliance

Data Masking Implementation Matrix

Environment	Classification Allowed	Masking Required	Tokenization Allowed	Real Data Prohibition
🔒 Production	All levels	No (real data)	Yes (for PCI DSS)	N/A - real data
📊 Staging	Up to Moderate	Yes for High+	Yes	Prohibited: Very High, Extreme
🧪 Testing	Up to Low	Yes for Moderate+	No	Prohibited: High, Very High, Extreme
💻 Development	Public only	Yes for all	No	Prohibited: All classified data
📈 Analytics	Anonymized only	Yes (irreversible)	No	Prohibited: All PII

Masking Techniques Standards

🔐 Static Data Masking (SDM):

Purpose: Create realistic but non-sensitive test datasets
Implementation: Pre-processing before environment deployment
Tools: Custom masking scripts + AWS Data Pipeline
Verification: Automated scanning for PII patterns post-masking
Use Cases: Development environments, training databases

⚡ Dynamic Data Masking (DDM):

Purpose: Real-time data obfuscation based on user role
Implementation: Database view-layer masking
Tools: RDS row-level security + application middleware
Verification: Access control testing + role validation
Use Cases: Production data access for non-privileged users

🔑 Tokenization:

Purpose: Reversible data protection for operational needs
Implementation: AWS Secrets Manager for token vault
Tools: Custom tokenization service + audit logging
Verification: Token-to-data mapping validation
Use Cases: Payment processing, temporary data sharing

Test Data Generation Standards

Per ISO 27001 A.8.33 (Test information), production data MUST NOT be used in non-production environments:

Test Data Type	Generation Method	Characteristics	Compliance
Synthetic Data	Algorithmically generated	Statistically similar, no real PII	✅ Preferred
Anonymized Data	Irreversible PII removal	Real patterns, no identifiable info	✅ Acceptable
Masked Data	Substitution with fake values	Format-preserved, fake content	✅ Acceptable
Scrambled Data	Randomized real data	Real patterns, shuffled relationships	⚠️ Risk assessment required
Production Copy	Direct copy of real data	Real PII and sensitive data	❌ Prohibited

Data Masking Governance

Review and Approval:

Masking Rule Changes: Security team approval required
New Data Types: Classification assessment before masking rules created
Tokenization Keys: CEO approval for token vault access
Test Data Refresh: Quarterly review of test dataset currency

Monitoring and Compliance:

PII Scanning: Weekly automated scans of non-production environments
Access Auditing: Quarterly review of data access patterns
Breach Detection: Real-time alerts for unmasked PII in non-production
Training: Annual data masking training for developers

Integration with Other Controls:

Secure Development Policy: Test data handling requirements (§ Protection of Test Data)
Access Control Policy: Role-based data access including masked views
Change Management: Masking rule changes via standard change process
Incident Response: Unmasked PII in non-production triggers security incident

🔍 Data Loss Prevention (DLP)

🛡️ DLP Strategy Implementation

Content Discovery and Classification

Automated tools and processes for identifying and classifying sensitive data:

Detection Method	Scope	Classification Trigger	Response
Pattern Matching	Email, documents, databases	PII, financial data, credentials	Auto-classification, alert
ML Classification	Unstructured content	Sensitive context	Risk scoring, review
Database Scanning	Structured data	Column patterns, data types	Schema classification
Network Monitoring	Data in transit	Transmission patterns	Real-time blocking

DLP Control Matrix

Data Type	Detection Method	Prevention Action	Notification
Credit Cards	Luhn algorithm + patterns	Block transmission	Immediate alert
Personal Data	PII patterns + context	Encrypt/quarantine	Compliance team
Financial Data	Account patterns + context	Access control	Security team
Source Code	Syntax detection	Repository control	Development team
Credentials	Secret scanning	Immediate revocation	Security incident

📊 DLP Monitoring and Metrics

Key Performance Indicators

Metric	Target	Measurement	Review Frequency
False Positive Rate	<5%	DLP alerts vs. confirmed incidents	Weekly
Detection Coverage	95%	Sensitive data identified	Monthly
Response Time	<15 minutes	Alert to action	Daily
Policy Compliance	98%	Successful policy enforcement	Monthly
User Training Effectiveness	<2% repeat violations	Incident recurrence rate	Quarterly

Based on 🤝 Third Party Management classifications:

Supplier Risk Tier	Data Classification Allowed	Contract Requirements	Monitoring Level
🔴 Critical Suppliers	Up to Very High	Comprehensive DPA, audit rights	Real-time monitoring
🟠 High Risk Suppliers	Up to High	Standard DPA, compliance verification	Daily monitoring
🟡 Medium Risk Suppliers	Up to Moderate	Basic agreement, attestation	Weekly monitoring
🟢 Low Risk Suppliers	Public + Low only	Standard terms	Monthly review

Data Processing Agreement (DPA) Requirements

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  }
}%%
flowchart TD
    subgraph ASSESSMENT["📊 Risk Assessment"]
        CLASSIFY["🏷️ Data Classification"]
        SUPPLIER["🤝 Supplier Risk Rating"]
        LEGAL["⚖️ Legal Requirements"]
    end
    
    subgraph CONTRACT["📝 Contract Terms"]
        PURPOSE["🎯 Processing Purpose"]
        CONTROLS["🛡️ Security Controls"]
        RETENTION["📅 Retention Limits"]
        AUDIT["🔍 Audit Rights"]
    end
    
    subgraph MONITORING["📊 Ongoing Monitoring"]
        COMPLIANCE["✅ Compliance Checks"]
        INCIDENTS["🚨 Incident Reporting"]
        REVIEWS["🔄 Regular Reviews"]
    end
    
    CLASSIFY --> PURPOSE
    SUPPLIER --> CONTROLS
    LEGAL --> RETENTION
    PURPOSE --> COMPLIANCE
    CONTROLS --> INCIDENTS
    RETENTION --> REVIEWS
    AUDIT --> REVIEWS
    
    style ASSESSMENT fill:#1565C0
    style CONTRACT fill:#4CAF50
    style MONITORING fill:#FF9800

🌍 Cross-Border Data Transfers

International Transfer Framework

Destination	Legal Basis	Additional Safeguards	Approval Required
🇪🇺 EU/EEA	Adequacy decision	Standard contractual clauses	Standard process
🇺🇸 USA	Adequacy framework	Data Privacy Framework compliance	Enhanced due diligence
🇨🇦 Canada	Adequacy decision	Standard contractual clauses	Standard process
Other Countries	Standard contractual clauses	Additional security measures	Executive approval

🔒 Privacy Data Classification

All personal data is classified using the comprehensive 🏷️ Privacy Levels framework, ensuring appropriate protection measures and GDPR compliance.

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}%%
flowchart TD
    START["📊 Data Received/Created"] --> IDENTIFY["🔍 Identify Data Type"]
    
    IDENTIFY --> GDPR_CHECK{"🇪🇺 Contains Personal Data?"}
    
    GDPR_CHECK -->|❌ No| NON_PERSONAL["🟢 Non-Personal Data<br/>Privacy: NA"]
    GDPR_CHECK -->|✅ Yes| PERSONAL_CHECK{"👤 Type of Personal Data?"}
    
    PERSONAL_CHECK --> SPECIAL{"🚨 Art. 9 Special Category?"}
    PERSONAL_CHECK --> IDENTIFIER{"🆔 Direct Identifier?"}
    PERSONAL_CHECK --> BEHAVIORAL{"📊 Behavioral/Preference?"}
    
    SPECIAL -->|✅ Yes| SPECIAL_CAT["🔴 Special Category Data<br/>Health, Biometric, etc."]
    IDENTIFIER -->|✅ Yes| PERS_ID["🔴 Personal Identifier<br/>Name, Email, SSN, IP"]
    BEHAVIORAL -->|✅ Yes| PERSONAL["🟠 Personal Data<br/>Activity, Preferences"]
    
    SPECIAL_CAT --> PROTECT_SPECIAL["🛡️ Highest Protection<br/>Explicit Consent + Legal Basis"]
    PERS_ID --> PROTECT_HIGH["🛡️ High Protection<br/>Encryption, Access Control"]
    PERSONAL --> PROTECT_STANDARD["🛡️ Standard Protection<br/>GDPR Compliance"]
    
    IDENTIFY --> PSEUDO_CHECK{"🎭 Can Pseudonymize?"}
    PSEUDO_CHECK -->|✅ Yes| PSEUDO["🟡 Pseudonymized Data<br/>Key Separation"]
    PSEUDO_CHECK -->|❌ Keep Anonymous| ANON["🟢 Anonymized Data<br/>Aggregated/Statistical"]
    
    classDef startStyle fill:#1565C0,stroke:#0D47A1,color:#fff
    classDef decisionStyle fill:#FF9800,stroke:#F57C00,color:#fff
    classDef criticalStyle fill:#D32F2F,stroke:#B71C1C,color:#fff
    classDef highStyle fill:#FF9800,stroke:#F57C00,color:#fff
    classDef standardStyle fill:#FF9800,stroke:#F57C00,color:#fff
    classDef lowStyle fill:#FFC107,stroke:#FFA000,color:#000
    classDef safeStyle fill:#4CAF50,stroke:#388E3C,color:#fff
    
    class START startStyle
    class GDPR_CHECK,PERSONAL_CHECK,SPECIAL,IDENTIFIER,BEHAVIORAL,PSEUDO_CHECK decisionStyle
    class SPECIAL_CAT criticalStyle
    class PERS_ID highStyle
    class PERSONAL standardStyle
    class PSEUDO lowStyle
    class ANON,NON_PERSONAL safeStyle

📋 Privacy Classification Matrix

GDPR Article	Data Examples	Protection Requirements	Data Subject Rights
Art. 9	Health data, biometric, genetic, racial origin, political opinions, religious beliefs	Explicit consent + Art. 9(2) legal basis, enhanced encryption, audit all access	Full rights + special protections
Art. 4(1)	Name, email, SSN, IP address, device ID, biometric identifiers	AES-256 encryption, MFA access, comprehensive audit logging	Full GDPR rights (Art. 15-22)
Art. 4(1)	User preferences, activity logs, location history, contacts	Standard encryption, RBAC, access logging	Full GDPR rights (Art. 15-22)
Art. 4(5)	Hashed user IDs, tokenized data with key separation	Key isolation, standard encryption	Limited rights (re-identification possible)
Outside GDPR	Aggregated statistics, anonymized analytics	Integrity protection, access control	No GDPR rights (not personal data)
N/A	Public information, system configuration, non-personal metadata	Standard information security controls	No GDPR rights (not personal data)

Implementation of GDPR Article 5 principles through data classification:

GDPR Principle (Art. 5)	Classification Implementation	Validation Method
Lawfulness, Fairness, Transparency	Legal basis documented in 🔐 Privacy Policy	Privacy notices, consent records
Purpose Limitation	Processing purposes defined per classification	Purpose-to-classification mapping
Data Minimization	Only collect data matching classification requirements	Regular data audits
Accuracy	Rectification procedures per privacy level	Data quality metrics
Storage Limitation	Retention periods per classification level (see below)	Automated deletion workflows
Integrity & Confidentiality	Security controls per privacy classification	Security assessments, penetration testing
Accountability	Classification audit trail, DPIA for High+	Compliance audits, documentation reviews

⏱️ Privacy-Based Retention Schedule

Retention Period	Legal Basis	Deletion Method
Purpose limited + 0 days	Art. 9(2) specific basis	Cryptographic erasure + secure wipe
Contract + 2 years OR Legal obligation (7 years for financial)	Art. 6(1)(b) or 6(1)(c)	Cryptographic erasure + backup purge
12-24 months after last activity	Art. 6(1)(f) Legitimate Interest	Standard secure deletion
12-14 months (analytics)	Art. 6(1)(f) Legitimate Interest	Key deletion + data retention
Indefinite (no longer personal data)	N/A (outside GDPR)	Standard deletion when no longer needed

🛡️ Data Subject Rights Implementation

Rights enforcement procedures per privacy classification:

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}%%
flowchart LR
    REQUEST["📧 Data Subject Request"] --> VERIFY["🔍 Identity Verification"]
    
    VERIFY --> CLASSIFY{"🏷️ Data Classification?"}
    
    CLASSIFY -->|🔴 Special/Identifier| PRIORITY["⚡ High Priority<br/>15 day target"]
    CLASSIFY -->|🟠 Personal| STANDARD["📅 Standard Process<br/>30 day target"]
    CLASSIFY -->|🟡 Pseudonymized| COMPLEX["🔍 Re-identification Check<br/>30-60 day target"]
    
    PRIORITY --> FULFILL["✅ Fulfill Request"]
    STANDARD --> FULFILL
    COMPLEX --> FULFILL
    
    FULFILL --> ACCESS{"📋 Request Type?"}
    
    ACCESS -->|📥 Access| EXPORT["📦 Data Export"]
    ACCESS -->|✏️ Rectification| UPDATE["🔄 Data Update"]
    ACCESS -->|🗑️ Erasure| DELETE["❌ Data Deletion"]
    ACCESS -->|⏸️ Restriction| RESTRICT["🔒 Processing Restriction"]
    ACCESS -->|📤 Portability| PORT["📊 Machine-Readable Export"]
    ACCESS -->|❌ Object| STOP["🛑 Stop Processing"]
    
    EXPORT --> RESPOND["📧 Response to Data Subject"]
    UPDATE --> RESPOND
    DELETE --> RESPOND
    RESTRICT --> RESPOND
    PORT --> RESPOND
    STOP --> RESPOND
    
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    classDef verifyStyle fill:#FF9800,stroke:#F57C00,color:#fff
    classDef priorityStyle fill:#D32F2F,stroke:#B71C1C,color:#fff
    classDef standardStyle fill:#FFC107,stroke:#FFA000,color:#000
    classDef actionStyle fill:#4CAF50,stroke:#388E3C,color:#fff
    classDef respondStyle fill:#1565C0,stroke:#1565C0,color:#fff
    
    class REQUEST requestStyle
    class VERIFY,CLASSIFY,ACCESS verifyStyle
    class PRIORITY priorityStyle
    class STANDARD,COMPLEX standardStyle
    class FULFILL actionStyle
    class EXPORT,UPDATE,DELETE,RESTRICT,PORT,STOP,RESPOND respondStyle

GDPR Right	Privacy Levels Applicable	Response Time	Implementation
Right to Access (Art. 15)	All (except NA)	30 days	Automated data export, manual compilation for complex requests
Right to Rectification (Art. 16)	Personal Identifier, Personal	30 days	Self-service updates + admin verification for identifiers
Right to Erasure (Art. 17)	All (except legal obligation)	30 days	Cryptographic erasure, cascade deletion, backup purge
Right to Restriction (Art. 18)	All	30 days	Processing flag, access restriction, retention-only mode
Right to Data Portability (Art. 20)	Personal Identifier, Personal	30 days	JSON/CSV export, structured format, machine-readable
Right to Object (Art. 21)	Legitimate Interest basis	Immediate for marketing	Opt-out mechanism, processing cessation

🔍 Data Protection Impact Assessment (DPIA)

DPIA required per GDPR Article 35 for:

Trigger Condition	Privacy Classification	When Required	Review Frequency
High risk to rights and freedoms	Special Category data processing	Before deployment	Annual
Large-scale systematic monitoring	Personal Identifier tracking at scale	New feature/service	Annual
Automated decision-making with legal effect	Any with automated profiling	Before implementation	Per change
Sensitive data processing	Special Category + Personal Identifier combined	New processing activity	Annual
Cross-border data transfers outside EU	Personal+ outside adequate countries	Before transfer	Per transfer assessment

DPIA Process:

📋 Identify necessity and proportionality
🔍 Assess risks to data subjects
🛡️ Identify mitigation measures
📊 Document findings and decisions
✅ DPO review and approval
📅 Ongoing monitoring and review

📊 Privacy Classification Examples from Hack23 Projects

Based on the SQL comment classification system used in CIA project:

Data Element	SQL Comment Example	Rationale
Public parliamentary data	`COMMENT ON COLUMN document_data.title IS 'DATA.Public GDPR.NA'`	Public government information, not personal data
Politician assignments	`COMMENT ON COLUMN assignment_data.intressent_id IS 'DATA.Public GDPR.Personal_Identifier'`	Public official information, identifiable natural person
User session data	`COMMENT ON COLUMN application_session.ip_information IS 'DATA.Sensitive GDPR.Personal'`	User activity tracking, identifiable
Application user ID	`COMMENT ON COLUMN application_action_event.user_id IS 'DATA.Sensitive GDPR.Personal_Identifier'`	Direct user identifier
System configuration	`COMMENT ON COLUMN application_configuration.property_value IS 'DATA.Sensitive GDPR.NA'`	System metadata, not personal

Column Comment Format Standard:

COMMENT ON COLUMN schema.table.column IS 'DATA.[Confidentiality] GDPR.[Privacy_Level]';

-- Examples:
-- 'DATA.Public GDPR.NA' - Public, non-personal
-- 'DATA.Sensitive GDPR.Personal' - Sensitive, personal data
-- 'DATA.Sensitive GDPR.Personal_Identifier' - Sensitive, direct identifier

✅ Compliance Integration

⚖️ Regulatory Framework Alignment

Integration with ✅ Compliance Checklist:

GDPR Article	Data Classification Impact	Implementation	Validation
Article 5 (Principles)	All classifications	Data minimization, purpose limitation	Quarterly review
Article 25 (Data Protection by Design)	High+ classifications	Technical/organizational measures	Architecture review
Article 32 (Security)	All classifications	Appropriate technical measures	Security assessment
Article 33 (Breach Notification)	Moderate+ classifications	72-hour notification	Incident procedures
Article 35 (DPIA)	High risk processing	Impact assessment	Legal review

NIS2 Alignment

NIS2 Requirement	Data Category	Classification Threshold	Implementation
Risk Management	Operational data	Moderate+	Risk register integration
Incident Reporting	Security events	High+	Incident response procedures
Business Continuity	Critical systems	Mission Critical availability	BCP integration
Supply Chain Security	Supplier data	Supplier risk assessment	Third-party management

📋 Audit and Evidence Management

Classification Audit Trail

Audit Event	Data Captured	Retention Period	Review Frequency
Classification Assignment	Data type, rationale, approver	7 years	Annual
Access Events	User, timestamp, data accessed	3 years	Monthly
Reclassification	Old/new classification, justification	7 years	Quarterly
Disposal Actions	Date, method, verification	Permanent	Annual
Incident Events	Classification impact, response	7 years	Per incident

🎯 Strategic & Governance

📈 Information Security Strategy — AI-first operations, Pentagon framework, and strategic data classification direction
🏷️ Classification Framework — Comprehensive classification methodology and business impact analysis
🔐 Information Security Policy — Overall security governance with AI-First Operations Governance
🤖 AI Policy — AI-assisted data classification and handling automation
📉 Risk Register — Data-related risk identification and treatment tracking
✅ Compliance Checklist — Regulatory compliance tracking including data protection laws

🔐 Security Policies & Controls

🔐 Privacy Policy — User-facing privacy notices and GDPR compliance for products
🔒 Cryptography Policy — Encryption standards and key management for classified data
🔑 Access Control Policy — Identity management and authorization controls for data access
🛠️ Secure Development Policy — Application security with data protection requirements

⚙️ Operational Integration

💾 Backup Recovery Policy — Data protection and recovery procedures based on classification
🤝 Third Party Management — Supplier risk management and data sharing governance
💻 Asset Register — Information asset inventory with classification assignments
🚨 Incident Response Plan — Data breach and security incident response procedures
🔄 Business Continuity Plan — Business resilience with classification-based recovery priorities

📋 Document Control:
✅ Approved by: James Pether Sörling, CEO
📤 Distribution: Public
🏷️ Classification:
📅 Effective Date: 2026-01-25
⏰ Next Review: 2027-01-25
🎯 Framework Compliance: