AI & LLM Security in Australia

AI & LLM security in Australia protects AI and Large Language Model applications from prompt injection, data leakage, model poisoning and excessive agency. Australia published a Voluntary AI Safety Standard built around 10 guardrails and is consulting on mandatory guardrails for high-risk AI, while the Privacy Act reforms tighten rules on automated decision-making. CyberSigma delivers LLM red-teaming and AI governance mapped to the Office of the Australian Information Commissioner (OAIC) 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 Australia organisations

Australia published a Voluntary AI Safety Standard built around 10 guardrails and is consulting on mandatory guardrails for high-risk AI, while the Privacy Act reforms tighten rules on automated decision-making. That momentum means Australia 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 Office of the Australian Information Commissioner (OAIC) 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 Office of the Australian Information Commissioner (OAIC).
• Secure AI adoption — GenAI usage policy, shadow-AI and data-leak controls.

Australia's 10 AI guardrails and the Essential Eight

Australian organisations are increasingly measured against the Voluntary AI Safety Standard's guardrails (testing, transparency, human oversight, records) and, for the underlying systems, the ACSC Essential Eight. AI used for automated decisions also faces tightening Privacy Act obligations.

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 Australia 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 Australia

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

• Privacy Act & Australian Privacy Principles (APPs) for AI and automated decisions.
• Voluntary AI Safety Standard (10 guardrails) — and readiness for proposed mandatory ones.
• ACSC Essential Eight as the security baseline.
• ISO/IEC 42001 + NIST AI RMF.

What are Australia's AI guardrails?

Australia's Voluntary AI Safety Standard defines 10 guardrails covering accountability, risk management, testing, transparency, human oversight and records. We help you implement and evidence them ahead of likely mandatory rules for high-risk AI.

How do the Privacy Act reforms affect AI?

Reforms strengthen rules around automated decision-making and transparency. AI that makes or significantly informs decisions about individuals needs clear notice and safeguards — which we assess and document.

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.