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# LLMSecForge: AI Cybersecurity Governance & Policy Frameworks |
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## `/frameworks/governance/` |
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This directory provides comprehensive governance frameworks, policy templates, and compliance guidance for managing adversarial risks in AI systems, establishing best practices for LLM security governance. |
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``` |
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frameworks/governance/ |
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βββ README.md |
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βββ policy-frameworks/ |
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β βββ security-governance-model.md |
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β βββ risk-management-framework.md |
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β βββ incident-response-policy.md |
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β βββ compliance-integration.md |
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βββ implementation/ |
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β βββ governance-implementation.md |
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β βββ security-controls.md |
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β βββ monitoring-framework.md |
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β βββ testing-protocols.md |
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βββ roles/ |
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β βββ security-responsibilities.md |
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β βββ red-team-governance.md |
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β βββ disclosure-management.md |
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β βββ oversight-structure.md |
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βββ standards/ |
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β βββ testing-standards.md |
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β βββ documentation-requirements.md |
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β βββ evidence-collection.md |
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β βββ assessment-methodologies.md |
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βββ risk-analysis/ |
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β βββ threat-modeling.md |
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β βββ vulnerability-classification.md |
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β βββ impact-assessment.md |
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β βββ risk-quantification.md |
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βββ templates/ |
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βββ governance-policy-template.md |
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βββ risk-assessment-template.md |
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βββ testing-documentation.md |
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βββ compliance-checklist.md |
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``` |
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## README.md |
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# AI Cybersecurity Governance & Policy Frameworks |
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This framework provides a comprehensive approach to AI security governance, establishing structured methodologies for managing adversarial risks, implementing appropriate controls, and ensuring compliance with emerging regulatory requirements for AI systems. |
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## Governance Framework Purpose |
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This section of the repository addresses critical governance needs: |
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1. **Policy Framework Integration**: Structured approaches to embedding adversarial security within organizational governance |
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2. **Compliance Alignment**: Methodologies for aligning security practices with emerging AI regulations and standards |
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3. **Risk Management Structures**: Frameworks for systematically assessing and managing adversarial risks |
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4. **Organizational Implementation**: Guidance for implementing governance across different organizational structures |
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5. **Documentation Standards**: Templates and requirements for governance documentation |
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## Core Framework Components |
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### 1. Policy & Governance Frameworks |
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Comprehensive governance structures for AI security: |
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- **Security Governance Model**: Organizational structure and oversight frameworks |
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- **Risk Management Framework**: Structured approach to AI security risk management |
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- **Incident Response Policy**: Governance for security incidents and vulnerabilities |
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- **Compliance Integration**: Alignment with regulatory and industry standards |
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### 2. Implementation Guidance |
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Practical approaches to governance implementation: |
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- **Governance Implementation**: Step-by-step implementation methodologies |
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- **Security Controls**: Technical and procedural control frameworks |
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- **Monitoring Framework**: Continuous monitoring approaches |
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- **Testing Protocols**: Governance requirements for security testing |
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### 3. Roles & Responsibilities |
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Clear delineation of security governance roles: |
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- **Security Responsibilities**: Role-based security responsibilities |
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- **Red Team Governance**: Oversight and management of adversarial testing |
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- **Disclosure Management**: Responsible disclosure governance |
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- **Oversight Structure**: Board and executive-level oversight frameworks |
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### 4. Standards & Requirements |
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Detailed standards for security governance: |
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- **Testing Standards**: Requirements for adversarial testing |
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- **Documentation Requirements**: Standards for security documentation |
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- **Evidence Collection**: Requirements for evidence gathering and retention |
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- **Assessment Methodologies**: Standardized assessment approaches |
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### 5. Risk Analysis Frameworks |
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Structured approaches to AI security risk: |
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- **Threat Modeling**: Frameworks for AI-specific threat modeling |
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- **Vulnerability Classification**: Standardized vulnerability categorization |
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- **Impact Assessment**: Methodologies for evaluating security impact |
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- **Risk Quantification**: Approaches to quantifying AI security risk |
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## Applications of this Framework |
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This governance framework supports several critical organizational functions: |
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1. **Executive Leadership**: Provides governance structures for board and executive oversight |
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2. **Security Teams**: Establishes clear roles, responsibilities, and procedures |
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3. **Compliance Functions**: Aligns security practices with regulatory requirements |
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4. **Risk Management**: Provides frameworks for systematic risk management |
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5. **Audit Functions**: Establishes clear standards for security assessment and evidence |
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## For Security Leaders |
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If you're responsible for AI security governance: |
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1. Review the governance model to establish appropriate organizational structures |
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2. Implement the risk management framework to systematically address AI risks |
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3. Utilize the implementation guidance for practical governance rollout |
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4. Leverage the templates for efficient policy and procedure development |
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## For Compliance Teams |
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If you're responsible for AI compliance: |
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1. Use the compliance integration framework to align security with regulatory requirements |
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2. Implement the documentation standards to ensure adequate evidence collection |
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3. Leverage the assessment methodologies for compliance verification |
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4. Utilize the templates for creating compliance-aligned documentation |
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--- |
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## AI Security Governance Model |
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```markdown |
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# AI Security Governance |