AI & LLM Security in Qatar

AI & LLM security in Qatar protects AI and Large Language Model applications from prompt injection, data leakage, model poisoning and excessive agency. Qatar's National AI Strategy and NCSA guidance drive responsible AI adoption, building on the digital infrastructure expanded for major national events and the country's National Vision 2030. CyberSigma delivers LLM red-teaming and AI governance mapped to the National Cyber Security Agency (NCSA) and the global frameworks (OWASP LLM Top 10, NIST AI RMF, ISO/IEC 42001, MITRE ATLAS). We are CERT-In empanelled and PCI QSA (CEMEA) authorised.

Secure AI adoption for Qatar organisations

Qatar's National AI Strategy and NCSA guidance drive responsible AI adoption, building on the digital infrastructure expanded for major national events and the country's National Vision 2030. That momentum means Qatar organisations must now show their AI is secure, governed and compliant — not just functional.

AI introduces failure modes traditional testing misses: chatbots manipulated into leaking data, AI agents coaxed into unauthorised actions, and poisoned models or datasets from public hubs. CyberSigma secures the full AI lifecycle — model, data, application, prompts, plugins and agents — and maps every finding to the National Cyber Security Agency (NCSA) and recognised global frameworks.

• LLM & GenAI application penetration testing and red-teaming (OWASP LLM Top 10).
• AI/ML model, pipeline and MLOps security assessment (MITRE ATLAS, Google SAIF).
• AI governance — ISO/IEC 42001 AI Management System and NIST AI RMF.
• Local alignment with the National Cyber Security Agency (NCSA).
• Secure AI adoption — GenAI usage policy, shadow-AI and data-leak controls.

National AI Strategy and the NCSA

Qatari entities in government, finance and energy are adopting AI on modern cloud and data infrastructure. The Personal Data Privacy Protection Law (PDPPL) governs personal data in AI, while the NCSA sets cybersecurity expectations for the systems that run it.

What we test (OWASP Top 10 for LLMs + MITRE ATLAS)

We adversarially test your LLM and GenAI applications the way a real attacker targeting a Qatar organisation would:

• Prompt injection — direct and indirect (documents, web pages, tools).
• Sensitive information disclosure — PII, secrets and system-prompt leakage.
• Insecure output handling — XSS, SSRF and code execution from model output.
• Excessive agency — agents/plugins taking unauthorised or destructive actions.
• Training-data poisoning and model/data supply-chain risks.
• Jailbreaks, guardrail bypass, model extraction and denial-of-wallet.

AI governance & compliance in Qatar

We turn the applicable frameworks into a prioritised, evidenced programme:

• Qatar Personal Data Privacy Protection Law (PDPPL) for AI and training data.
• NCSA cybersecurity guidance for the underlying systems.
• National AI Strategy alignment for responsible adoption.
• ISO/IEC 42001 + NIST AI RMF.

Does Qatar's PDPPL cover AI systems?

Yes. The PDPPL governs personal data processed by AI, including consent, purpose limitation and security. We assess your AI's handling of personal data against it.

Who regulates cybersecurity for AI in Qatar?

The National Cyber Security Agency (NCSA) sets cybersecurity expectations. We map your AI system security and red-teaming evidence to that guidance.

How does AI red-teaming differ from normal penetration testing?

Traditional pen testing targets code and infrastructure; AI red-teaming additionally targets the model's behaviour via prompts, poisoned context and connected tools to make it leak data or act without authorisation. Mature programmes use both — we provide each and can combine them.