An independent security audit of your AI systems.
Traditional code reviews weren't built for systems that learn, generate and act. The OneNet AI Security Audit is a structured evaluation across the full AI lifecycle, data, models, applications, infrastructure and governance, surfacing the risks unique to AI and giving you a prioritised remediation plan you can actually run with.
- Lifecycle review across data, models and apps
- Adversarial red-teaming of your AI systems
- Shadow-AI discovery across the business
- Mapped to NIST AI RMF, ISO/IEC 42001 and OWASP LLM
- Prioritised, actionable remediation roadmap
Lifecycle-wide assurance for the AI you've already deployed.
Data integrity and privacy
We examine the data feeding your models, looking for personal information leakage, embedded bias and exposure to data-poisoning attacks across training, fine-tuning and retrieval pipelines.
Application and agent testing
Hands-on testing of LLM apps, RAG pipelines and agents for prompt injection, insecure output handling, tool-abuse paths and the OWASP Top 10 for LLMs.
Adversarial red-teaming
Simulated attacks against your AI surfaces, jailbreaks, model theft attempts and behavioural probes, to find what an actual adversary would find first.
Shadow-AI discovery
Inventory of every AI tool in play, including the unsanctioned ones quietly being used by teams. You can't secure what you can't see.
Governance and compliance
Your AI policies, vendor agreements and operating practices benchmarked against NIST AI RMF, ISO/IEC 42001, the EU AI Act and New Zealand privacy obligations.
Remediation and monitoring
Risk-scored findings with prioritised, costed remediation, plus the controls and telemetry needed to monitor model drift and emerging risks over time.
What you'll see.
Ready to move faster, safer, smarter?
Book a free 30-minute strategy call. No slides. No sales pitch. Just an honest conversation about your cloud and AI roadmap.
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