📚 Knowledge Base

NCA's Essential Cybersecurity Controls specify strict remediation timelines that organizations must follow: 1) Critical Vulnerabilities (CVSS 9.0-10.0) - must be remediated within 15 days of discovery; 2) High Vulnerabilities (CVSS 7.0-8.9) - within 30 days; 3) Medium Vulnerabilities (CVSS 4.0-6.9) - within 90 days; 4) Low Vulnerabilities (CVSS 0.1-3.9) - within 180 days. Prioritization should consider: exploitability in the wild, asset criticality to business operations, data sensitivity, internet exposure, and availability of patches. For systems that cannot be immediately patched, organizations must implement compensating controls such as network segmentation, access restrictions, or Web Application Firewalls (WAF). A formal exception process approved by senior management is required for vulnerabilities that cannot meet remediation timelines. Organizations should maintain a vulnerability management dashboard tracking remediation status, integrate with change management processes, and report quarterly to NCA on vulnerability metrics and remediation effectiveness for critical infrastructure sectors.

ISO/IEC 42001 is the international standard for Artificial Intelligence Management Systems (AIMS), published to help organizations develop, deploy, and use AI responsibly and ethically. For Saudi organizations, ISO/IEC 42001 provides a structured framework that aligns with Vision 2030's digital transformation objectives and supports compliance with emerging AI regulations. The standard addresses AI-specific risks including algorithmic bias, transparency, data quality, and accountability. It complements existing frameworks like SAMA CSF and NCA ECC by providing AI-focused controls covering the entire AI lifecycle—from design and development through deployment and monitoring. Key benefits for Saudi entities include: establishing clear AI governance structures with defined roles and responsibilities; implementing risk-based approaches to AI system classification and control; ensuring AI systems meet ethical principles and regulatory requirements including PDPL data protection obligations; providing assurance to stakeholders, regulators, and customers about responsible AI practices; and supporting interoperability with other management systems like ISO/IEC 27001 for information security. Organizations in regulated sectors such as financial services, healthcare, and critical infrastructure can leverage ISO/IEC 42001 to demonstrate due diligence in AI deployment while maintaining alignment with SAMA, NCA, and SDAIA requirements.

ISO/IEC 42001 provides comprehensive controls specifically designed for AI risk management that complement SAMA's Cybersecurity Framework requirements for financial institutions. Key controls relevant to SAMA-supervised entities include: AI Impact Assessment (Control 6.2.2) requiring organizations to evaluate AI systems' potential impacts on individuals, society, and the organization before deployment—critical for customer-facing AI applications in banking and insurance; Data Governance for AI (Control 6.2.3) ensuring training data quality, representativeness, and compliance with PDPL requirements, particularly important given SAMA's data localization and protection expectations; AI System Transparency and Explainability (Control 6.2.4) mandating documentation of AI decision-making processes, essential for regulatory reporting and customer rights under PDPL; Human Oversight (Control 6.2.5) requiring appropriate human involvement in AI-driven decisions, especially for high-risk applications like credit scoring, fraud detection, and automated trading; AI System Monitoring and Performance (Control 6.2.6) establishing continuous monitoring for model drift, bias, and performance degradation; Third-Party AI Management (Control 6.2.7) addressing risks from AI vendors and cloud AI services, aligning with SAMA's third-party risk management requirements; and Incident Management for AI (Control 6.2.8) covering AI-specific incidents like model failures, bias incidents, and adversarial attacks. Financial institutions should integrate these controls with SAMA CSF domains, particularly Risk Management, Third Party, and Data Management, creating a unified governance approach that addresses both traditional cybersecurity and AI-specific risks.

ISO/IEC 42001 is designed with a compatible structure to ISO/IEC 27001:2022, enabling Saudi organizations to create an integrated management system that addresses both information security and AI-specific risks. Integration approaches include: Unified Governance Structure—establish a combined governance committee overseeing both ISMS and AIMS, with AI-specific subcommittees reporting to existing information security governance bodies, ensuring alignment with NCA ECC and SAMA CSF requirements; Common Risk Management Framework—extend the ISO/IEC 27001 risk assessment methodology to include AI-specific risks such as training data poisoning, model inversion attacks, adversarial examples, and algorithmic discrimination, creating a single enterprise risk register; Shared Policy Framework—develop integrated policies covering both traditional security controls and AI-specific requirements, such as an AI Acceptable Use Policy that extends existing information security policies; Combined Asset Management—extend the ISO/IEC 27001 asset inventory to include AI-specific assets like training datasets, ML models, AI algorithms, and AI development environments, ensuring proper classification and protection under PDPL requirements; Integrated Incident Response—enhance existing security incident procedures to address AI-specific incidents including model failures, bias detection, and AI security breaches, with clear escalation paths to SAMA and NCA as required; Unified Audit and Compliance—conduct combined internal audits covering both frameworks, optimizing resources and reducing audit fatigue while ensuring comprehensive coverage of NCA ECC controls and SAMA requirements; and Consolidated Documentation—maintain integrated documentation systems, policies, and records that satisfy both standards while reducing duplication. Organizations already certified to ISO/IEC 27001 can leverage existing processes, controls, and documentation as a foundation, adding AI-specific controls incrementally as they expand AI adoption, creating efficiency while maintaining robust governance aligned with Saudi regulatory expectations.

SOC threat intelligence integration in Saudi Arabia should include: 1) Subscription to NCA's National Cybersecurity Center threat feeds and alerts specific to Saudi infrastructure, 2) Integration of regional threat intelligence covering Middle East threat actors and campaigns (APT groups targeting Gulf region), 3) Participation in Saudi sectoral ISACs (Information Sharing and Analysis Centers) for banking, energy, and healthcare, 4) Implementation of STIX/TAXII protocols for automated threat intelligence sharing, 5) Contextualization of global threat intelligence to Saudi environment and Arabic language indicators, 6) Monitoring of threats specific to Saudi technologies and vendors commonly used in the Kingdom, 7) Integration with MITRE ATT&CK framework mapped to threats observed in Saudi networks, 8) Regular threat briefings incorporating geopolitical context affecting Saudi Arabia, 9) Threat hunting programs based on intelligence about adversaries targeting Saudi organizations, and 10) Compliance with Saudi data sovereignty requirements when sharing threat intelligence internationally.

A comprehensive Saudi SOC technology stack should include: 1) SIEM platform with Arabic language support and local log retention compliant with Saudi data regulations (minimum 1 year), 2) Endpoint Detection and Response (EDR) solutions covering Windows, Linux, and mobile devices common in Saudi organizations, 3) Network Traffic Analysis (NTA) tools for east-west traffic monitoring, 4) Security Orchestration, Automation and Response (SOAR) platform to handle high alert volumes, 5) Threat intelligence platform integrated with regional feeds, 6) Vulnerability management system aligned with NCA-ECC vulnerability management requirements, 7) Case management system for incident tracking and NCA reporting, 8) Data Loss Prevention (DLP) tools to protect sensitive data under PDPL, 9) Cloud security monitoring for AWS, Azure, and local cloud providers, 10) Forensics tools for incident investigation, 11) Ticketing system integrated with ITSM processes, and 12) Dashboards and reporting tools for management visibility. All tools should support data residency requirements and be deployed in Saudi data centers where mandated by regulations.

According to the National Cybersecurity Authority's Essential Cybersecurity Controls (ECC), Saudi organizations should conduct security awareness training regularly and systematically. Best practices recommend: 1) Initial comprehensive training for all new employees during onboarding; 2) Annual refresher training for all staff members; 3) Quarterly or monthly security awareness updates covering emerging threats and recent incidents; 4) Immediate targeted training following security incidents or when new threats emerge; 5) Role-specific training for employees handling sensitive data or critical systems, conducted semi-annually; 6) Simulated phishing exercises at least quarterly to test and reinforce learning. Organizations in regulated sectors like banking, healthcare, and government should follow stricter schedules as mandated by their respective regulatory bodies such as SAMA (Saudi Central Bank) or the Ministry of Health.

Saudi organizations can measure security awareness training effectiveness through: 1) Pre and post-training assessments to measure knowledge improvement; 2) Simulated phishing campaign results tracking click rates, reporting rates, and trends over time; 3) Security incident metrics monitoring reduction in user-caused incidents like credential compromise or malware infections; 4) Training completion rates and time-to-completion analytics; 5) Employee feedback surveys evaluating content relevance and delivery quality; 6) Behavioral observations monitoring adherence to security policies; 7) Quiz and certification scores for compliance documentation required by NCA; 8) Incident reporting rates measuring employee engagement in security processes; 9) Regular security audits assessing practical application of training; 10) Benchmarking against industry standards and peer organizations in Saudi Arabia; and 11) Return on Investment (ROI) analysis comparing training costs against prevented incident costs. Organizations should report these metrics to management and adjust training programs based on results.

According to NCA's Essential Cybersecurity Controls (ECC-5), a comprehensive vulnerability management program in Saudi Arabia must include: 1) Asset Discovery and Inventory - maintaining an up-to-date inventory of all IT assets including hardware, software, and network devices; 2) Vulnerability Scanning - conducting regular automated scans (at least quarterly for general systems and monthly for critical systems) using approved tools; 3) Risk Assessment and Prioritization - evaluating vulnerabilities based on CVSS scores, asset criticality, and potential business impact; 4) Remediation - applying patches, implementing compensating controls, or accepting risks with documented justification within defined timeframes (critical vulnerabilities within 15 days, high within 30 days); 5) Verification - confirming successful remediation through rescanning; 6) Reporting - documenting findings and remediation status for NCA compliance audits. Organizations must also maintain vulnerability management policies in Arabic and English, conduct penetration testing annually, and report critical vulnerabilities affecting national infrastructure to NCA within 72 hours.

Saudi organizations should implement vulnerability scanning solutions that align with NCA requirements and international standards. Recommended tools include: Qualys, Tenable Nessus, Rapid7 InsightVM, and OpenVAS for network vulnerability scanning. For web applications, tools like Acunetix, Burp Suite, and OWASP ZAP are effective. Best practices include: 1) Deploying both authenticated and unauthenticated scans to identify different vulnerability types; 2) Scheduling scans during maintenance windows to minimize business disruption while meeting NCA's minimum frequency requirements; 3) Integrating scanning tools with SIEM solutions for centralized monitoring; 4) Using Arabic-language reporting capabilities for local stakeholders; 5) Ensuring scanners are updated with latest vulnerability signatures; 6) Conducting scans from both internal and external perspectives; 7) Implementing continuous monitoring for critical assets in sectors like banking, energy, and healthcare. Organizations should verify that scanning vendors comply with Saudi data residency requirements and can support Arabic documentation for NCA audits.

NCA's Essential Cybersecurity Controls mandate specific remediation timelines based on vulnerability severity. Organizations must: 1) Critical Vulnerabilities (CVSS 9.0-10.0) - remediate within 15 days, particularly those affecting internet-facing systems or critical infrastructure; 2) High Vulnerabilities (CVSS 7.0-8.9) - remediate within 30 days; 3) Medium Vulnerabilities (CVSS 4.0-6.9) - remediate within 90 days; 4) Low Vulnerabilities (CVSS 0.1-3.9) - remediate within 180 days or document risk acceptance. Prioritization should consider: asset criticality to business operations, exploitability in the wild, data sensitivity (especially for systems processing Saudi citizen data), regulatory impact, and threat intelligence. For systems that cannot be immediately patched, organizations must implement compensating controls such as network segmentation, WAF rules, IPS signatures, or access restrictions, and document these in Arabic and English for NCA audits. Critical vulnerabilities in national infrastructure sectors (energy, water, health, finance, telecommunications) require immediate notification to NCA's NCRC (National Cybersecurity Response Center) and expedited remediation with executive oversight.

When procuring AI systems or services in Saudi Arabia, organizations must address several critical vendor risk areas aligned with SAMA CSF, NCA ECC, and PDPL requirements:

Regulatory Compliance & Data Sovereignty:

• Verify vendor compliance with Saudi PDPL data protection requirements, including lawful processing bases, data subject rights, and breach notification obligations
• Ensure AI processing of personal data meets PDPL localization requirements where applicable, particularly for sensitive sectors under SAMA or NCA oversight
• Confirm vendor adherence to NCA ECC controls for cloud services (ECC-1 through ECC-6) if AI solutions involve cloud infrastructure
• For financial institutions, validate alignment with SAMA CSF domains, especially Technology and Cyber Security (Domain 11) and Third Party Service Provider Management (Domain 12)

AI-Specific Technical Risks:

• Assess model transparency, explainability capabilities, and documentation quality—critical for high-risk AI applications in regulated sectors
• Evaluate data quality, provenance, and potential biases in training datasets that could affect fairness and accuracy
• Review model validation methodologies, performance metrics, and ongoing monitoring capabilities
• Understand model update and versioning processes, including impact assessment procedures
• Verify security controls protecting AI models from adversarial attacks, data poisoning, and model extraction

Operational & Contractual Safeguards:

• Establish clear data ownership, usage rights, and restrictions on secondary use of organizational data for vendor model training
• Define service level agreements (SLAs) covering AI system availability, accuracy thresholds, and performance degradation
• Require regular third-party audits and certifications (ISO/IEC 27001:2022, ISO/IEC 42001 for AI management systems)
• Include contractual provisions for algorithm audits, bias testing, and explainability reporting
• Ensure exit strategies with data portability, model transition support, and knowledge transfer provisions

Continuous Monitoring:

• Implement ongoing vendor performance monitoring aligned with NIST AI Risk Management Framework principles
• Establish incident response protocols for AI failures, bias incidents, or security breaches
• Conduct periodic reassessments as AI capabilities evolve and regulatory requirements mature

These considerations support Vision 2030's digital transformation objectives while maintaining robust risk management aligned with Saudi Arabia's evolving AI governance landscape.

Banks must develop and maintain a comprehensive cybersecurity policy framework including: Information Security Policy, Access Control Policy, Incident Response Plan, Business Continuity and Disaster Recovery Plans, Data Classification and Protection Policy, Third-Party Risk Management Policy, Cryptography Policy, and Network Security Standards. All policies must be approved by the board or appropriate committee, reviewed annually, and include Arabic versions. Documentation must also include security procedures, control implementation evidence, audit trails, training records, incident logs, and compliance assessment reports. These documents must be readily available for SAMA inspections and demonstrate alignment with all applicable SAMA CSF domains and controls.

Technical implementation requires deploying multiple security layers: implementing multi-factor authentication (MFA) for all privileged access and remote connections, deploying next-generation firewalls and intrusion detection/prevention systems, establishing Security Operations Center (SOC) capabilities or engaging qualified Saudi-based providers, implementing data encryption for data at rest and in transit, deploying endpoint protection and mobile device management solutions, establishing secure network segmentation, implementing security information and event management (SIEM) systems, conducting regular vulnerability assessments and penetration testing, and ensuring secure configuration management. All technical controls must be configured according to SAMA requirements, with logging and monitoring enabled to detect and respond to security incidents within mandated timeframes.

Institutions must establish continuous compliance monitoring through: implementing automated compliance tracking tools, conducting quarterly internal security assessments, performing annual independent third-party audits by SAMA-recognized auditors, maintaining real-time security monitoring through SOC operations, tracking key risk indicators (KRIs) and key performance indicators (KPIs), and submitting mandatory reports to SAMA including cybersecurity incident reports (within specified timeframes), annual self-assessment reports, and audit findings. The institution must maintain an action plan for remediation of identified gaps, conduct regular management reviews, and ensure timely reporting of material changes to the cybersecurity posture. All monitoring activities and results must be documented and available for regulatory review.

The PDPL mandates comprehensive technical and organizational security measures appropriate to the risk level. Required measures include: (1) Encryption of personal data during transmission and storage; (2) Access controls and authentication mechanisms limiting data access to authorized personnel only; (3) Regular security assessments and vulnerability testing; (4) Data breach detection and response procedures with mandatory notification to SDAIA within 72 hours; (5) Employee training on data protection and security practices; (6) Data backup and disaster recovery plans; (7) Secure data disposal procedures; (8) Privacy by Design and Default principles in system development; (9) Vendor management ensuring third-party processors meet security standards; (10) Documentation of all security measures and regular audits. Organizations must conduct Data Protection Impact Assessments (DPIAs) for high-risk processing activities.

Saudi organizations should implement a risk-based vulnerability prioritization framework aligned with NCA guidelines. Prioritization should consider: (1) CVSS (Common Vulnerability Scoring System) scores, with scores 9.0-10.0 classified as critical; (2) Asset criticality - systems processing sensitive government data, financial transactions, or critical infrastructure receive higher priority; (3) Exploitability - whether active exploits exist in the wild; (4) Business impact - potential disruption to essential services or Saudi Vision 2030 initiatives; (5) Compliance requirements - vulnerabilities affecting NCA ECC compliance must be prioritized. Organizations should establish Service Level Agreements (SLAs): critical vulnerabilities remediated within 7-30 days, high within 30-90 days, medium within 90-180 days. Compensating controls (network segmentation, WAF, IPS) should be implemented when immediate patching isn't feasible. All remediation activities must be documented, tested in non-production environments first, and approved through change management processes. Regular reporting to executive management and NCA (when required) ensures accountability and compliance.

Saudi organizations should select vulnerability management tools that meet NCA requirements and support Arabic language interfaces. Recommended enterprise-grade solutions include: Qualys VMDR, Tenable.io/Nessus Professional, Rapid7 InsightVM, and OpenVAS (open-source option). These tools should provide: automated discovery and asset inventory, authenticated and unauthenticated scanning, integration with SIEM systems, compliance reporting for NCA ECC standards, API integration for automation, and support for cloud environments (AWS, Azure, Google Cloud). For government entities, tools must support air-gapped deployments and data residency within Saudi Arabia. Organizations should ensure vendors provide local support in Arabic and have presence in Saudi Arabia or authorized partners. Additional capabilities should include: vulnerability correlation and deduplication, patch management integration, risk scoring aligned with organizational context, executive dashboards in Arabic, and integration with ticketing systems (ServiceNow, Jira). All tools must undergo security assessment before deployment and comply with Saudi procurement regulations and CITC telecommunications standards.

LLM applications introduce unique security challenges that Saudi organizations must address to comply with SAMA CSF, NCA ECC, and PDPL requirements:

Prompt Injection Attacks: Malicious inputs can manipulate LLM behavior to bypass security controls, leak sensitive data, or execute unintended actions. Organizations must implement input validation, sanitization, and privilege separation between user prompts and system instructions.

Data Leakage and Privacy Violations: LLMs may inadvertently expose training data, personal information, or confidential business data in responses. Under PDPL, organizations processing personal data through LLMs must implement data minimization, anonymization, and access controls. SAMA CSF Domain 3 (Data Security and Privacy) requires encryption and classification of sensitive data before LLM processing.

Model Poisoning and Supply Chain Risks: Pre-trained models or fine-tuning datasets may contain backdoors or biased data. NCA ECC Control 5-2-1 mandates secure software development practices, requiring organizations to verify model provenance, audit training data sources, and implement model validation procedures.

Insecure Output Handling: LLM outputs may contain code injection, cross-site scripting (XSS), or SQL injection payloads if not properly sanitized before use in downstream systems. Organizations must treat LLM outputs as untrusted and apply output encoding and validation.

Excessive Agency and Permissions: LLMs with unrestricted access to APIs, databases, or system functions pose significant risk. Apply principle of least privilege, implement function-calling controls, and require human approval for high-risk operations.

Denial of Service and Resource Exhaustion: LLM queries can be computationally expensive. Implement rate limiting, query complexity analysis, and resource quotas to prevent abuse and ensure availability per NCA ECC Control 4-1-1.

Compliance Considerations: For financial institutions under SAMA supervision, LLM applications handling customer data must meet SAMA CSF requirements for AI governance, model risk management, and explainability. Vision 2030's digital transformation goals emphasize responsible AI adoption with robust security controls.

Secure development of LLM-integrated applications requires a comprehensive approach aligned with Saudi regulatory frameworks:

Security by Design (NCA ECC Control 5-2-1):

• Conduct threat modeling specific to LLM risks (OWASP Top 10 for LLM Applications provides a valuable reference framework)
• Implement security requirements during design phase, including input validation architecture, output sanitization, and privilege separation
• Document AI/ML model selection criteria, security controls, and risk assessments
• Establish secure coding standards addressing LLM-specific vulnerabilities

Data Governance and Privacy (SAMA CSF Domain 3 & PDPL):

• Classify data before LLM processing and apply appropriate protection measures
• Implement data minimization: only provide LLMs with necessary context, not entire databases
• Use techniques like differential privacy, data masking, and tokenization for sensitive data
• Maintain data lineage documentation showing how personal data flows through LLM systems
• Obtain explicit consent where required under PDPL for AI-driven processing of personal data
• Implement right to explanation mechanisms for automated decisions affecting individuals

Model Security and Validation:

• Verify provenance and integrity of pre-trained models and datasets
• Conduct security testing of models for bias, backdoors, and adversarial vulnerabilities
• Implement model versioning and change management procedures
• Establish baseline performance metrics and monitor for model drift or degradation
• For fine-tuned models, sanitize and validate training data to prevent poisoning

Access Control and Authentication (NCA ECC Control 1-1-1):

• Implement strong authentication for LLM API access
• Apply role-based access control (RBAC) limiting who can interact with LLM systems
• Separate user context from system prompts using technical controls
• Log all LLM interactions with sufficient detail for audit and incident response

Input/Output Security Controls:

• Implement input validation and sanitization to detect and block prompt injection attempts
• Use allowlisting for acceptable input patterns where feasible
• Apply output encoding and content security policies before rendering LLM responses
• Implement content filtering to detect and redact sensitive information in outputs
• Validate and sanitize LLM outputs before using them in downstream operations (database queries, API calls, code execution)

API Security and Rate Limiting:

• Implement API gateways with authentication, authorization, and rate limiting
• Monitor for abnormal usage patterns indicating abuse or attacks
• Apply cost controls and resource quotas to prevent denial of service
• Use circuit breakers to isolate LLM failures from critical business functions

Testing and Validation (SAMA CSF Domain 8):

• Conduct regular penetration testing including LLM-specific attack scenarios
• Perform red team exercises simulating prompt injection, jailbreaking, and data extraction attempts
• Implement automated security testing in CI/CD pipelines
• Validate security controls through independent third-party assessments

Incident Response and Monitoring:

• Establish monitoring for LLM-specific security events (unusual prompts, data leakage indicators, performance anomalies)
• Include LLM incidents in incident response plans with specific playbooks
• Implement audit logging meeting NCA ECC Control 4-4-1 requirements
• Establish procedures for model rollback in case of security incidents

Vendor Management (SAMA CSF Domain 2):

• For third-party LLM services, conduct due diligence on security practices and data handling
• Ensure contracts address data residency, privacy, security responsibilities, and incident notification
• Verify vendor compliance with relevant standards (ISO/IEC 42001 for AI management systems, ISO/IEC 27001)
• Maintain right to audit vendor security controls

These practices support Vision 2030's responsible AI adoption while ensuring compliance with Saudi cybersecurity and data protection regulations.