AI threat modelling
We map how your AI system could be attacked or misused, from prompt injection and data exfiltration to model theft and unsafe actions, and prioritise the risks that matter.
AI Security Services
AI Security Services
Trusted across 20+ countries by Fortune 500 companies and growth-stage brands
Secure the AI systems your business depends on. Noseberry threat-models your LLM, RAG and agent systems, builds in the guardrails and controls they need, and protects the data and models behind them, against the attack surfaces traditional security misses. Engineering-led work that supports your security and compliance obligations.
Book a free AI security reviewDefinition
What are AI security services?
AI security services protect AI systems and the data they handle across four layers: the model, the data, the pipeline and the application. They address the attack surfaces that are unique to AI, prompt injection, training-data and model attacks, data leakage through prompts or outputs, and unsafe or over-privileged actions, on top of standard application security. The work is technical engineering and testing that supports your security and compliance responsibilities; it is not a certification or a guarantee.
Key takeaways
- AI security services protect AI systems and the data they touch, across the model, the data, the pipeline and the application.
- AI adds new attack surfaces traditional security misses: prompt injection, training-data and model risks, and unsafe outputs.
- The work spans threat modelling, secure architecture, guardrails, and monitoring once the system is live.
- This is technical engineering and testing. It supports your security and compliance obligations; it is not a certification or a guarantee.
2M+Lives touched
15+Fortune 500 clients
20+Countries served
250+Digital solutions delivered
Scope
What AI security services include
We secure the whole AI system, not just the model, and build the controls in rather than bolting them on later.
Secure LLM and RAG architecture
We design the system so untrusted input, retrieval sources and tool access are isolated and controlled, and secrets and data never leak through prompts or outputs.
Guardrails and input/output controls
Content filtering, allow-lists, rate limits and output validation that keep the system inside safe boundaries.
Data and model protection
Encryption, access control, PII handling and safeguards around training data and model artefacts, so sensitive data stays protected end to end.
Identity, access and secrets
Least-privilege access for models, agents and tools, with proper secrets management so an AI component cannot reach beyond its remit.
Monitoring and incident response
Logging, anomaly detection and a response plan, because AI systems drift and are probed after launch, not only before.
Who this is for
Built for teams putting AI into production
Engineering, security and product leaders deploying LLM, RAG or agent systems that touch real users, sensitive data or internal systems, and who need those systems to be secure and to fit their existing security posture.
Signs you need it
- You are putting an LLM, RAG system or agent in front of users or into a workflow.
- Your AI system touches sensitive data, PII or internal systems.
- You are worried about prompt injection, data leakage or unsafe outputs.
- You need AI to sit within your existing security and compliance posture.
- You want an independent view of your AI system's security before launch.
How we work
From threat model to monitored production
1
Scope and threat model
We map the system, its data and its attack surface, and agree the risks to focus on.
2
Assess
We review architecture, access, data flows and guardrails against AI-specific threats.
3
Design controls
We define the secure architecture, guardrails and controls the system needs.
4
Implement and test
We build the controls in and test them, alongside your engineering team.
5
Monitor
We set up logging, detection and a response plan for once it is live.
Why Noseberry
Why choose Noseberry for AI security
AI-specific, not generic
We secure the parts traditional security misses: prompts, retrieval, model and agent behaviour.
Engineering-led
Controls built into the system by the team that ships AI, not a report that sits on a shelf.
Honest scope
Technical security work that supports your obligations. We do not sell certification or guarantees.
Proven at scale
2M+ lives touched, 15+ Fortune 500 clients, 250+ solutions across 20+ countries.
Frequently Asked Questions
They are engineering and testing services that protect AI systems and the data they touch, covering the model, the data, the pipeline and the application, against AI-specific threats such as prompt injection, data leakage and unsafe outputs.
AI adds new attack surfaces that traditional security does not cover: untrusted natural-language input can manipulate a model (prompt injection), training data and models can be attacked or stolen, and outputs can be unsafe or leak data. AI security addresses those on top of standard controls.
Prompt injection is when crafted input makes a model ignore its instructions or take unintended actions. It cannot be eliminated entirely, but it can be substantially mitigated with isolation, input and output controls, least-privilege tool access and monitoring, which is what we build.
No. We provide technical security engineering and testing that supports your security and compliance obligations. Formal certification and the compliance determination sit with your qualified security and audit teams.
Yes. We threat-model and assess an existing LLM, RAG or agent system, then design and implement the controls it is missing, working with your team.
Security services build the defences; red teaming adversarially tests them. They complement each other, and we offer both.
Put AI into production securely
Book a free review and we will threat-model your AI system and map the controls it needs.
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