name	classification-policy
description	Risk-based data and asset classification framework: PUBLIC, INTERNAL, CONFIDENTIAL, RESTRICTED aligned with ISO 27001 A.5.12 and CIA triad

Data Classification Policy Skill

Purpose

This skill provides systematic guidance for implementing risk-based data and asset classification within the CIA platform, ensuring proper protection controls align with information sensitivity, business impact, and regulatory requirements per ISO 27001 A.5.12, A.5.13, and A.8.10.

When to Use This Skill

Apply this skill when:

✅ Designing data models with sensitive information (personal data, political records)
✅ Implementing access controls for classified information
✅ Defining encryption requirements for data at rest and in transit
✅ Creating data handling procedures (storage, transmission, disposal)
✅ Conducting privacy impact assessments (GDPR compliance)
✅ Establishing retention and disposal policies
✅ Labeling data assets in documentation or code
✅ Configuring security controls for different sensitivity levels

Do NOT skip for:

❌ "Internal-only" systems (still require classification)
❌ Development/test data (may contain production data copies)
❌ Temporary data stores (still subject to classification)
❌ Public APIs (may expose classified data)

4-Tier Classification Model

Classification Levels Overview

graph TD
    subgraph Classification["🏷️ Classification Tiers"]
        RESTRICTED["🔴 RESTRICTED<br/>Extreme Confidentiality<br/>National Security Level"]
        CONFIDENTIAL["🟠 CONFIDENTIAL<br/>High Confidentiality<br/>Business Sensitive"]
        INTERNAL["🟡 INTERNAL<br/>Moderate Confidentiality<br/>Company Use Only"]
        PUBLIC["🟢 PUBLIC<br/>No Confidentiality<br/>Publicly Accessible"]
    end
    
    subgraph CIA["🛡️ CIA Triad Mapping"]
        CONF["🔒 Confidentiality<br/>Data Secrecy"]
        INT["✅ Integrity<br/>Data Accuracy"]
        AVAIL["⏱️ Availability<br/>Data Access"]
    end
    
    subgraph Controls["🔐 Security Controls"]
        ENCRYPTION["🔐 Encryption Requirements"]
        ACCESS["🚪 Access Controls"]
        AUDIT["📊 Audit Logging"]
        RETENTION["📅 Retention Policy"]
    end
    
    RESTRICTED --> CONF
    RESTRICTED --> INT
    RESTRICTED --> AVAIL
    
    CONFIDENTIAL --> CONF
    CONFIDENTIAL --> INT
    CONFIDENTIAL --> AVAIL
    
    INTERNAL --> INT
    INTERNAL --> AVAIL
    
    PUBLIC --> AVAIL
    
    CONF --> ENCRYPTION
    CONF --> ACCESS
    INT --> AUDIT
    AVAIL --> RETENTION
    
    style Classification fill:#1565C0
    style CIA fill:#4CAF50
    style Controls fill:#FF9800

🔴 RESTRICTED - Extreme Confidentiality

Definition: Information requiring maximum protection due to severe business, legal, or regulatory consequences if disclosed.

CIA Triad Mapping:

Confidentiality: - Unauthorized disclosure causes catastrophic damage
Integrity: - Data tampering creates legal liability
Availability: - Authorized access required for compliance

Examples in CIA Platform:

Encryption keys and cryptographic secrets
Database credentials and connection strings
OAuth tokens and API keys
Personal Identity Numbers (Swedish personnummer)
Authentication credentials and password hashes

Mandatory Security Controls:

Control Type	Requirement	Implementation
Encryption at Rest	AES-256 or stronger	AWS KMS, encrypted EBS volumes
Encryption in Transit	TLS 1.3 minimum	HTTPS only, HSTS enabled
Access Control	Zero-trust, MFA required	RBAC, least privilege principle
Audit Logging	All access logged with retention	CloudWatch Logs, 1-year retention
Labeling	Explicit marking required	Code comments, doc headers
Retention	Minimum required, immediate disposal	Automated purging after expiry

Java Implementation Example:

/**
 * CLASSIFICATION: RESTRICTED
 * Contains database credentials - never log or expose
 * 
 * @see <a href="https://github.com/Hack23/ISMS-PUBLIC/blob/main/CLASSIFICATION.md">Classification Policy</a>
 * @see <a href="https://github.com/Hack23/ISMS-PUBLIC/blob/main/Cryptography_Policy.md">Cryptography Policy</a>
 */
@Configuration
public class DatabaseConfig {
    
    // RESTRICTED: Database password from encrypted secrets manager
    @Value("${spring.datasource.password}")
    private String databasePassword;
    
    @Bean
    public DataSource dataSource() {
        HikariConfig config = new HikariConfig();
        config.setJdbcUrl(System.getenv("DB_URL"));
        config.setUsername(System.getenv("DB_USERNAME"));
        
        // NEVER log or print RESTRICTED data
        config.setPassword(databasePassword);
        
        // Enable connection encryption (TLS 1.3)
        config.addDataSourceProperty("ssl", "true");
        config.addDataSourceProperty("sslmode", "verify-full");
        
        return new HikariDataSource(config);
    }
    
    @Override
    public String toString() {
        return "DatabaseConfig{password=***REDACTED***}";
    }
}

Handling Requirements:

❌ NEVER store in source code or version control
❌ NEVER log to application logs or console
❌ NEVER transmit over unencrypted channels
❌ NEVER store in plaintext configuration files
✅ Store in AWS Secrets Manager or Parameter Store
✅ Inject via environment variables at runtime
✅ Rotate regularly (minimum quarterly)
✅ Immediate revocation when compromised

🟠 CONFIDENTIAL - High Confidentiality

Definition: Business-sensitive information with significant financial, operational, or competitive impact if disclosed.

CIA Triad Mapping:

Confidentiality: - Disclosure causes major business harm
Integrity: - Unauthorized modification creates business risk
Availability: - Business continuity depends on access

Examples in CIA Platform:

Political party financial records (detailed budget data)
Ministerial expense reports (before public release)
Internal security vulnerability assessments
Business strategy and competitive analysis
System architecture diagrams with security details

Mandatory Security Controls:

Control Type	Requirement	Implementation
Encryption at Rest	AES-256 recommended	Database encryption, encrypted backups
Encryption in Transit	TLS 1.2 minimum	HTTPS, secure API calls
Access Control	RBAC with quarterly reviews	Spring Security, user roles
Audit Logging	Access events logged	Application logs, 90-day retention
Labeling	Classification marking recommended	Document headers, metadata
Retention	Business-driven retention	7 years for financial data

Java Implementation Example:

/**
 * CLASSIFICATION: CONFIDENTIAL
 * Contains business-sensitive political party financial data
 * 
 * Access restricted to authenticated users with PARTY_ANALYST role
 * All access logged per ISO 27001 A.8.15
 */
@Entity
@Table(name = "party_financial_record")
public class PartyFinancialRecord {
    
    @Id
    @GeneratedValue(strategy = GenerationType.IDENTITY)
    private Long id;
    
    @Column(name = "party_id", nullable = false)
    private String partyId;
    
    // CONFIDENTIAL: Detailed budget breakdown
    @Column(name = "budget_json", columnDefinition = "jsonb")
    @Convert(converter = JsonConverter.class)
    private Map<String, BigDecimal> detailedBudget;
    
    @Column(name = "fiscal_year")
    private Integer fiscalYear;
    
    @CreatedDate
    @Column(name = "created_at", nullable = false)
    private LocalDateTime createdAt;
    
    @CreatedBy
    @Column(name = "created_by")
    private String createdBy;
}

@Service
public class PartyFinancialService {
    
    private final AuditLogger auditLogger;
    
    @PreAuthorize("hasRole('PARTY_ANALYST') or hasRole('ADMIN')")
    @Audited(message = "Access to CONFIDENTIAL party financial data")
    public PartyFinancialRecord getFinancialRecord(Long recordId, String userId) {
        // Log access to CONFIDENTIAL data
        auditLogger.logDataAccess(
            "CONFIDENTIAL", 
            "party_financial_record", 
            recordId, 
            userId
        );
        
        return financialRepository.findById(recordId)
            .orElseThrow(() -> new ResourceNotFoundException("Record not found"));
    }
}

Handling Requirements:

❌ NEVER share with unauthorized external parties
❌ NEVER store on unencrypted removable media
❌ NEVER transmit via unencrypted email
✅ Encrypt before email transmission (if required)
✅ Access requires authentication and authorization
✅ Mark documents with "CONFIDENTIAL" header
✅ Securely dispose when no longer needed

🟡 INTERNAL - Moderate Confidentiality

Definition: Information intended for internal use only, with moderate business impact if disclosed externally.

CIA Triad Mapping:

Confidentiality: - External disclosure creates moderate risk
Integrity: - Modification affects business operations
Availability: - Business operations continue with delays

Examples in CIA Platform:

Internal project planning documents
System performance metrics and analytics
Employee directory and contact information
Internal training materials
Aggregated usage statistics (anonymized)

Security Controls:

Control Type	Requirement	Implementation
Encryption at Rest	Recommended for sensitive subsets	Database encryption optional
Encryption in Transit	TLS 1.2 for external access	HTTPS for web interfaces
Access Control	Authentication required	Standard user accounts
Audit Logging	Significant events logged	Basic application logs
Labeling	Classification marking optional	File metadata preferred
Retention	Standard business retention	3 years typical

Java Implementation Example:

/**
 * CLASSIFICATION: INTERNAL
 * System performance metrics for internal monitoring
 * 
 * Access requires authentication
 */
@Entity
@Table(name = "system_metrics")
public class SystemMetrics {
    
    @Id
    @GeneratedValue(strategy = GenerationType.IDENTITY)
    private Long id;
    
    @Column(name = "metric_name")
    private String metricName;
    
    @Column(name = "metric_value")
    private Double metricValue;
    
    @Column(name = "timestamp")
    private LocalDateTime timestamp;
    
    @Column(name = "server_id")
    private String serverId;
}

@RestController
@RequestMapping("/api/internal/metrics")
public class MetricsController {
    
    // INTERNAL: Requires authenticated user
    @GetMapping
    @PreAuthorize("isAuthenticated()")
    public ResponseEntity<List<SystemMetrics>> getMetrics(
            @RequestParam LocalDateTime startTime,
            @RequestParam LocalDateTime endTime) {
        
        List<SystemMetrics> metrics = metricsService.findByTimeRange(startTime, endTime);
        return ResponseEntity.ok(metrics);
    }
}

Handling Requirements:

❌ NEVER publish to public websites or repositories
❌ NEVER share with external parties without approval
✅ Share with authenticated internal users
✅ Use standard email for internal distribution
✅ Standard backup and retention procedures
✅ Dispose using normal deletion procedures

🟢 PUBLIC - No Confidentiality

Definition: Information approved for public disclosure with no confidentiality requirements.

CIA Triad Mapping:

Confidentiality: - Intended for public consumption
Integrity: - Accuracy important for reputation
Availability: - High availability expected by public

Examples in CIA Platform:

Public API documentation
Open-source code repositories (GitHub public repos)
Published voting records (already public from Riksdagen)
Press releases and marketing materials
Public data visualizations and dashboards

Security Controls:

Control Type	Requirement	Implementation
Encryption at Rest	Not required	Standard storage
Encryption in Transit	Recommended for integrity	HTTPS for web content
Access Control	None required	Public access allowed
Audit Logging	Optional	Basic web server logs
Labeling	Classification marking optional	Metadata optional
Retention	Indefinite or business need	Standard retention

Java Implementation Example:

/**
 * CLASSIFICATION: PUBLIC
 * Published voting records from Swedish Riksdagen
 * 
 * Data already public via Riksdagen API
 * No access restrictions required
 */
@Entity
@Table(name = "voting_record")
public class VotingRecord {
    
    @Id
    private String votingId;
    
    @Column(name = "politician_id")
    private String politicianId;
    
    @Column(name = "vote")
    @Enumerated(EnumType.STRING)
    private VoteType voteType; // YES, NO, ABSTAIN, ABSENT
    
    @Column(name = "voting_date")
    private LocalDate votingDate;
    
    @Column(name = "document_id")
    private String documentId;
}

@RestController
@RequestMapping("/api/public/voting-records")
public class VotingRecordController {
    
    // PUBLIC: No authentication required
    @GetMapping
    public ResponseEntity<List<VotingRecord>> getVotingRecords(
            @RequestParam(required = false) String politicianId,
            @RequestParam(required = false) LocalDate startDate,
            @RequestParam(required = false) LocalDate endDate) {
        
        List<VotingRecord> records = votingService.findPublicRecords(
            politicianId, startDate, endDate
        );
        
        return ResponseEntity.ok(records);
    }
}

Handling Requirements:

✅ Can be published to public websites
✅ Can be shared via any medium
✅ No special disposal requirements
⚠️ Verify data is truly public before classifying
⚠️ Ensure no embedded RESTRICTED/CONFIDENTIAL data

Classification Decision Tree

Use this decision tree to classify information:

graph TD
    START["🏷️ Start Classification"] --> Q1{"Contains credentials,<br/>encryption keys,<br/>or PII?"}
    
    Q1 -->|Yes| RESTRICTED["🔴 RESTRICTED"]
    Q1 -->|No| Q2{Business-sensitive or<br/>competitive advantage<br/>if disclosed?}
    
    Q2 -->|Yes| Q3{Significant financial<br/>or legal impact<br/>if disclosed?}
    Q2 -->|No| Q4{Already publicly<br/>available or<br/>approved for release?}
    
    Q3 -->|Yes| CONFIDENTIAL["🟠 CONFIDENTIAL"]
    Q3 -->|No| INTERNAL["🟡 INTERNAL"]
    
    Q4 -->|Yes| PUBLIC["🟢 PUBLIC"]
    Q4 -->|No| INTERNAL
    
    RESTRICTED --> R_CONTROLS["🔐 Maximum Security:<br/>• AES-256 encryption<br/>• MFA required<br/>• Never log<br/>• Immediate disposal"]
    
    CONFIDENTIAL --> C_CONTROLS["🛡️ High Security:<br/>• Encryption recommended<br/>• RBAC enforced<br/>• Access logging<br/>• Quarterly reviews"]
    
    INTERNAL --> I_CONTROLS["🚪 Standard Security:<br/>• Authentication required<br/>• Internal use only<br/>• Standard retention<br/>• Basic logging"]
    
    PUBLIC --> P_CONTROLS["🌐 Public Access:<br/>• No restrictions<br/>• Integrity focus<br/>• High availability<br/>• Public distribution OK"]
    
    style RESTRICTED fill:#D32F2F
    style CONFIDENTIAL fill:#FF9800
    style INTERNAL fill:#FDD835
    style PUBLIC fill:#4CAF50
    style START fill:#1565C0

Labeling Requirements

Code-Level Labeling

JavaDoc Comments:

/**
 * CLASSIFICATION: RESTRICTED
 * 
 * Contains authentication tokens and encrypted credentials.
 * 
 * Security Requirements:
 * - Never log token values
 * - Rotate tokens every 90 days
 * - Immediate revocation on compromise
 * 
 * @see <a href="https://github.com/Hack23/ISMS-PUBLIC/blob/main/CLASSIFICATION.md">Classification Policy</a>
 * @see <a href="https://github.com/Hack23/ISMS-PUBLIC/blob/main/Secrets_Management_Policy.md">Secrets Management</a>
 */
public class AuthenticationToken {
    // Implementation
}

SQL Table Comments:

-- CLASSIFICATION: CONFIDENTIAL
-- Party financial data with business-sensitive budget details
-- Access requires PARTY_ANALYST role
COMMENT ON TABLE party_financial_record IS 
'CLASSIFICATION: CONFIDENTIAL - Party financial data requiring access control';

COMMENT ON COLUMN party_financial_record.budget_json IS 
'Detailed budget breakdown - business sensitive';

Document-Level Labeling

Markdown Header:

---
title: Security Vulnerability Assessment
classification: CONFIDENTIAL
date: 2025-02-10
author: Security Team
retention: 7 years
---

# CONFIDENTIAL: Security Vulnerability Assessment

**Classification**: CONFIDENTIAL  
**Audience**: Internal Security Team Only  
**Distribution**: Do not forward externally

Configuration Files:

# CLASSIFICATION: INTERNAL
# Application configuration - internal use only
spring:
  application:
    name: citizen-intelligence-agency
  # ... configuration

GDPR and Privacy Classification

Special Category Personal Data (Art. 9 GDPR)

Definition: Sensitive personal data requiring explicit consent and enhanced protection.

Examples:

Political opinions and party membership (Art. 9.1.a GDPR)
Trade union membership
Health data
Biometric data for identification
Genetic data

Classification Mapping:

GDPR Category	Classification	Rationale
Political opinions	CONFIDENTIAL minimum	Business-sensitive + GDPR Art. 9
Health data	RESTRICTED	Special category + high risk
Biometric data	RESTRICTED	Unique identifier + irreversible

CIA Platform Handling:

/**
 * CLASSIFICATION: CONFIDENTIAL
 * GDPR: Special Category Personal Data (Art. 9.1.a - Political Opinions)
 * 
 * Political party membership requires:
 * - Explicit consent (GDPR Art. 9.2.a)
 * - Legal basis documentation
 * - Enhanced security controls
 * - Privacy by design
 */
@Entity
@Table(name = "politician_party_membership")
public class PoliticianPartyMembership {
    
    @Id
    private String membershipId;
    
    @Column(name = "politician_id", nullable = false)
    private String politicianId;
    
    // GDPR Art. 9 - Political opinion (special category)
    @Column(name = "party_id", nullable = false)
    private String partyId;
    
    @Column(name = "membership_start")
    private LocalDate membershipStart;
    
    @Column(name = "membership_end")
    private LocalDate membershipEnd;
    
    // GDPR compliance: Track consent basis
    @Column(name = "legal_basis")
    @Enumerated(EnumType.STRING)
    private GdprLegalBasis legalBasis; // PUBLIC_OFFICIAL, LEGITIMATE_INTEREST
    
    @Column(name = "data_source")
    private String dataSource; // "Riksdagen Public API"
}

Personal Data Classification

Data Type	GDPR Classification	Platform Classification	Security Controls
Direct Identifiers (name, SSN)	Personal Data	RESTRICTED	Encryption + MFA
Political Opinions	Special Category	CONFIDENTIAL	Enhanced access controls
Contact Information (email, phone)	Personal Data	CONFIDENTIAL	Access logging
IP Addresses	Personal Data	INTERNAL	Standard security
Aggregated Analytics	Anonymized	PUBLIC	Ensure irreversible anonymization

ISO 27001 Control Mapping

A.5.12 - Classification of Information

Control Objective: Ensure appropriate level of protection based on importance to organization.

Implementation in CIA Platform:

✅ Four-tier classification model defined (RESTRICTED, CONFIDENTIAL, INTERNAL, PUBLIC)
✅ Classification criteria documented in this skill
✅ Labeling procedures for code, data, and documents
✅ CIA triad mapping to security controls
✅ GDPR privacy level integration

Verification:

# Search for classification labels in codebase
grep -r "CLASSIFICATION:" --include="*.java" --include="*.sql" citizen-intelligence-agency/

# Verify database column comments include classification
psql -d cia_database -c "\
SELECT table_name, column_name, col_description(attrelid, attnum) \
FROM information_schema.columns \
JOIN pg_class ON relname = table_name \
JOIN pg_attribute ON attrelid = pg_class.oid AND attname = column_name \
WHERE table_schema = 'public' \
AND col_description(attrelid, attnum) LIKE '%CLASSIFICATION%';"

A.5.13 - Labelling of Information

Control Objective: Ensure information assets receive appropriate level of protection.

Implementation:

✅ Labeling standards for code comments, database tables, documents
✅ Automated labeling enforcement via code review
✅ Metadata tagging in version control systems

A.8.10 - Information Deletion

Control Objective: Information deleted when no longer required.

Retention by Classification:

/**
 * Automated data retention enforcement
 */
@Component
@Scheduled(cron = "0 0 2 * * *") // Daily at 2 AM
public class DataRetentionEnforcer {
    
    private final AuditLogger auditLogger;
    
    public void enforceRetention() {
        // RESTRICTED: Immediate disposal after expiry
        deleteExpiredRestrictedData();
        
        // CONFIDENTIAL: 7-year retention (financial data)
        deleteExpiredConfidentialData(Period.ofYears(7));
        
        // INTERNAL: 3-year retention (operational data)
        deleteExpiredInternalData(Period.ofYears(3));
        
        // PUBLIC: Indefinite retention (no automatic deletion)
    }
    
    private void deleteExpiredRestrictedData() {
        List<RestrictedData> expired = restrictedRepo.findExpired(LocalDateTime.now());
        
        for (RestrictedData data : expired) {
            // Secure deletion with audit trail
            auditLogger.logDataDeletion("RESTRICTED", data.getId(), "RETENTION_EXPIRED");
            restrictedRepo.secureDelete(data);
        }
    }
}

NIST Cybersecurity Framework Mapping

PR.DS-2: Data-in-transit is protected

✅ TLS 1.3 for RESTRICTED data
✅ TLS 1.2 minimum for CONFIDENTIAL data
✅ HTTPS recommended for INTERNAL/PUBLIC data

PR.DS-5: Protections against data leaks are implemented

✅ Access controls per classification level
✅ Audit logging for RESTRICTED/CONFIDENTIAL access
✅ Data loss prevention through classification awareness

CIS Controls Mapping

CIS Control 3: Data Protection

3.3: Configure data access control lists
- ✅ RBAC implementation per classification
3.11: Encrypt sensitive data at rest
- ✅ AES-256 for RESTRICTED
- ✅ Database encryption for CONFIDENTIAL
3.12: Segment data processing and storage
- ✅ Separate storage for different classification levels

Practical Implementation Checklist

For New Data Models

For Existing Systems

Inventory all data assets
Classify each asset using decision tree
Add classification labels to existing code
Verify current controls match classification requirements
Identify and remediate control gaps
Update documentation with classification markings
Conduct classification review (annual minimum)

Common Classification Mistakes

❌ Mistake 1: Over-Classification

Problem: Classifying all data as RESTRICTED/CONFIDENTIAL unnecessarily
Impact: Excessive security overhead, reduced operational efficiency
Solution: Use decision tree, classify based on actual business impact

❌ Mistake 2: Under-Classification

Problem: Classifying sensitive data as PUBLIC/INTERNAL
Impact: Inadequate protection, compliance violations, data breaches
Solution: When uncertain, classify higher and review with security team

❌ Mistake 3: No Classification

Problem: Leaving data unclassified
Impact: No clear security controls, inconsistent protection
Solution: Mandate classification for all new data models via PR reviews

❌ Mistake 4: Inconsistent Labeling

Problem: Same data classified differently across systems
Impact: Confusion, control gaps, audit findings
Solution: Centralized classification authority, regular reviews

AWS Implementation Examples

S3 Bucket Classification

# CloudFormation template for classified S3 bucket
Resources:
  ConfidentialDataBucket:
    Type: AWS::S3::Bucket
    Properties:
      BucketName: cia-confidential-party-data
      BucketEncryption:
        ServerSideEncryptionConfiguration:
          - ServerSideEncryptionByDefault:
              SSEAlgorithm: aws:kms
              KMSMasterKeyID: !Ref DataEncryptionKey
      PublicAccessBlockConfiguration:
        BlockPublicAcls: true
        BlockPublicPolicy: true
        IgnorePublicAcls: true
        RestrictPublicBuckets: true
      VersioningConfiguration:
        Status: Enabled
      LifecycleConfiguration:
        Rules:
          - Id: CONFIDENTIAL-7year-retention
            Status: Enabled
            ExpirationInDays: 2555 # 7 years
            NoncurrentVersionExpirationInDays: 30
      Tags:
        - Key: Classification
          Value: CONFIDENTIAL
        - Key: DataOwner
          Value: PartyAnalysisTeam
        - Key: GDPRCategory
          Value: BusinessSensitive

RDS Database Classification

  ConfidentialDatabase:
    Type: AWS::RDS::DBInstance
    Properties:
      DBInstanceIdentifier: cia-confidential-db
      Engine: postgres
      EngineVersion: "18.3"
      DBInstanceClass: db.t3.medium
      StorageEncrypted: true
      KmsKeyId: !Ref DataEncryptionKey
      BackupRetentionPeriod: 30
      EnableCloudwatchLogsExports:
        - postgresql
      DeletionProtection: true
      Tags:
        - Key: Classification
          Value: CONFIDENTIAL
        - Key: DataType
          Value: PoliticalFinancialRecords
        - Key: RetentionYears
          Value: "7"

Related Policies

Information Security Policy - Overall security framework
CLASSIFICATION.md - Detailed classification framework
Cryptography Policy - Encryption requirements
Secrets Management Policy - RESTRICTED credential handling
Data Protection Policy - GDPR compliance
Access Control Policy - RBAC implementation

References

ISO 27001:2022 - A.5.12 Classification of Information
ISO 27001:2022 - A.5.13 Labelling of Information
ISO 27001:2022 - A.8.10 Information Deletion
GDPR Article 9 - Processing of Special Categories of Personal Data
NIST SP 800-60 - Guide for Mapping Types of Information
CIS Controls v8 - Control 3: Data Protection

classification-policy

More from this repository

More from this repository

Data Classification Policy Skill

Purpose

When to Use This Skill

4-Tier Classification Model

Classification Levels Overview

🔴 RESTRICTED - Extreme Confidentiality

🟠 CONFIDENTIAL - High Confidentiality

🟡 INTERNAL - Moderate Confidentiality

🟢 PUBLIC - No Confidentiality

Classification Decision Tree

Labeling Requirements

Code-Level Labeling

Document-Level Labeling

GDPR and Privacy Classification

Special Category Personal Data (Art. 9 GDPR)

Personal Data Classification

ISO 27001 Control Mapping

A.5.12 - Classification of Information

A.5.13 - Labelling of Information

A.8.10 - Information Deletion

NIST Cybersecurity Framework Mapping

CIS Controls Mapping

Practical Implementation Checklist

For New Data Models

For Existing Systems

Common Classification Mistakes

❌ Mistake 1: Over-Classification

❌ Mistake 2: Under-Classification

❌ Mistake 3: No Classification

❌ Mistake 4: Inconsistent Labeling

AWS Implementation Examples

S3 Bucket Classification

RDS Database Classification

Related Policies

References

Data Classification Policy Skill

Purpose

When to Use This Skill

4-Tier Classification Model

Classification Levels Overview

🔴 RESTRICTED - Extreme Confidentiality

🟠 CONFIDENTIAL - High Confidentiality

🟡 INTERNAL - Moderate Confidentiality

🟢 PUBLIC - No Confidentiality

Classification Decision Tree

Labeling Requirements

Code-Level Labeling

Document-Level Labeling

GDPR and Privacy Classification

Special Category Personal Data (Art. 9 GDPR)

Personal Data Classification

ISO 27001 Control Mapping

A.5.12 - Classification of Information

A.5.13 - Labelling of Information

A.8.10 - Information Deletion

NIST Cybersecurity Framework Mapping

CIS Controls Mapping

Practical Implementation Checklist

For New Data Models

For Existing Systems

Common Classification Mistakes

❌ Mistake 1: Over-Classification

❌ Mistake 2: Under-Classification

❌ Mistake 3: No Classification

❌ Mistake 4: Inconsistent Labeling

AWS Implementation Examples

S3 Bucket Classification

RDS Database Classification

Related Policies

References