AI & LLM Security in Singapore

AI & LLM security in Singapore protects AI and Large Language Model applications from prompt injection, data leakage, model poisoning and excessive agency. Singapore leads practical AI governance: IMDA/PDPC's Model AI Governance Framework (with a 2024 edition for generative AI), the AI Verify testing toolkit and foundation, and Project Moonshot for LLM evaluation and red-teaming. CyberSigma delivers LLM red-teaming and AI governance mapped to the Personal Data Protection Commission (PDPC) and IMDA 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 Singapore organisations

Singapore leads practical AI governance: IMDA/PDPC's Model AI Governance Framework (with a 2024 edition for generative AI), the AI Verify testing toolkit and foundation, and Project Moonshot for LLM evaluation and red-teaming. That momentum means Singapore 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 Personal Data Protection Commission (PDPC) and IMDA 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 Personal Data Protection Commission (PDPC) and IMDA.
• Secure AI adoption — GenAI usage policy, shadow-AI and data-leak controls.

AI Verify and Project Moonshot

Singapore's approach is test-driven: AI Verify lets organisations validate AI against governance principles, and Project Moonshot provides LLM red-teaming and benchmarking. This makes independent AI testing — exactly what we provide — a natural fit for demonstrating trustworthy AI to regulators and customers.

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 Singapore 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 Singapore

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

• PDPA for AI and training data, including the advisory guidelines on AI use.
• Model AI Governance Framework (incl. the generative-AI edition).
• AI Verify / Project Moonshot-aligned testing and red-teaming.
• ISO/IEC 42001 + NIST AI RMF.

What is Singapore's Model AI Governance Framework?

It is PDPC/IMDA's practical framework for responsible AI, with a dedicated edition for generative AI covering accountability, data, testing and incident management. We help you operationalise it.

What is AI Verify and how does testing help?

AI Verify is Singapore's AI governance testing framework and toolkit; Project Moonshot adds LLM red-teaming. Independent testing against these demonstrates your AI is trustworthy — we run that testing and map the results.

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.