AI is moving faster than the controls built to govern it. We find the new class of risk it brings — and build the guardrails to keep it contained as you scale.
neuwork / perspectivesAI SECURITY, IN ORBIT
The difference between scaling AI with confidence and scaling exposure.
01 / practiceModels, prompts, pipelines and integrations mapped and tested end to end.
02 / practicePrompt injection, jailbreaks and exfiltration, run like a persistent adversary.
03 / practiceEU AI Act, NIST AI RMF and ISO/IEC 42001, made operable.
04 / practiceA validated detection map for AI-specific threats, built with your team.
05 / practiceVector databases, agent pipelines and AI cloud setups reviewed against real attack paths.
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The full practice
AI is moving faster than the controls built to govern it. As you embed AI into products, pipelines, and decision-making, you inherit a new class of risk — one that traditional security tooling wasn’t built to see and traditional governance frameworks weren’t built to cover. We help you find that risk before it finds you, and build the guardrails to keep it contained as you scale.
This isn’t a bolt-on audit. It’s a practice built specifically around how AI systems are attacked, misused, and mismanaged — informed by the same adversarial thinking we bring to every engagement, applied to the systems that matter most right now.
Every model you deploy, every agent you wire into a workflow, and every AI feature you ship expands your attack surface in ways that are easy to miss. We map that surface end to end — models, prompts, data pipelines, plugins, integrations, and the applications built on top of them — then test what an adversary could actually do with it.
Static test suites don’t hold up against adaptive systems. Our AI red team engagements simulate real adversarial behavior against your live models and AI-powered products — prompt injection, jailbreaking, data exfiltration, model manipulation, and misuse scenarios specific to your deployment. Our adaptive engagements go further, evolving session over session the way a persistent, motivated adversary would.
Regulators, customers, and boards are all asking the same question: how do you know your AI is safe, fair, and under control? We help you answer it — translating fast-moving AI regulation and emerging standards (EU AI Act, NIST AI RMF, ISO/IEC 42001) into governance frameworks your teams can actually operate, not just file away.
We work alongside your security and ML teams, not around them. In coordinated cycles, we execute AI-specific attack techniques while your team works to detect and respond — then debrief in real time. The result is a validated detection map for AI-specific threats, clear coverage gaps, and response playbooks your team will actually use.
Misconfiguration is still the most common way in — and AI environments add new layers of it: overly permissive model access, unsecured vector databases, exposed API keys in agent pipelines, unreviewed third-party model integrations. We review how your AI environments are built and configured, and deliver a prioritised remediation roadmap mapped to real attack paths.
Why this matters now: AI security and governance isn’t a future concern — it’s the difference between scaling AI with confidence and scaling exposure. We help you do the former.
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Not exposure.
AI security and governance isn’t a future concern. Let’s find your risk before it finds you.
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