What is AI Security Assessment?

AI Security Assessment evaluates AI and ML model architecture and access controls, identifies training data integrity and supply chain risks, assesses API security and integration vulnerabilities, detects prompt injection and adversarial input risks, and identifies data privacy and regulatory compliance exposure.

What is AI Red Teaming?

AI Red Teaming simulates real-world attacks against AI and large language model (LLM) deployments. It tests for model extraction and intellectual property theft, identifies adversarial inputs designed to manipulate outputs, simulates prompt injection and jailbreaking attacks, detects sensitive data leakage through model responses, and assesses indirect attacks via third-party integrations.

What is AI Governance & Risk?

AI Governance & Risk involves designing and implementing an AI governance framework tailored to your organisation's risk appetite and industry context. This includes AI risk framework aligned to NIST AI RMF and ISO 42001, AI use case inventory and risk classification, third-party and vendor AI risk assessments, AI acceptable use policies and internal controls, and board and executive reporting templates.

AI Security

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AI Risk Assessment

Considering adopting AI but unsure where to start? Our AI Risk Assessment helps organisations understand the strategic, operational, and security risks of AI adoption before they commit. We evaluate your environment, use cases, and risk appetite to give you a clear picture of what AI means for your business - and what guardrails you'll need in place.

Identify AI-related risks across people, process, and technology
Evaluate proposed AI use cases against your risk appetites
Assess regulatory and compliance obligations for AI adoption in Australia
Develop a risk-informed AI adoption roadmap
Provide board and leadership-ready reporting on AI risk exposure

AI Security Assessment

Already using AI systems and want to know how secure they are? Our AI Security Assessment provides a technical evaluation of your AI and machine learning environments, identifying vulnerabilities that traditional security testing doesn't cover - from adversarial input risks to insecure integrations and data exposure.

Evaluate AI and ML model architecture and access controls
Identify training data integrity and supply chain risks
Assess API security and integration vulnerabilities
Test for prompt injection and adversarial input risks
Benchmark against OWASP Top 10 for LLMs and NIST AI RMF

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Secure AI Review

Already built or deployed an AI system? Our Secure AI Review is a post-deployment audit that examines your AI system for security and privacy gaps that may have been introduced during development or since go-live. We provide a clear findings report with prioritised recommendations your team can act on immediately.

Review AI system architecture for security and privacy weaknesses
Identify data handling and exposure risks post-deployment
Assess model outputs for unintended information disclosure
Review third-party integrations and vendor AI risk
Deliver a prioritised remediation report aligned to your risk profile

AI Security

AI Risk Assessment

AI Security Assessment

Secure AI Review

Stay ahead of cyber threats

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