📚 Knowledge Base
Comprehensive cybersecurity Q&A covering Saudi regulatory compliance
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.