Data security with AI: keep data safe when the intelligence moves in
AI is only as secure as the way it is built. Every time data is sent to a model, an agent gets access to your systems, or an employee uses AI on their own, new routes for leaks and misuse appear. I build AI solutions where security is designed in from the first line of code — not bolted on afterwards.
- Confidential data and trade secrets are sent unencrypted to external models.
- Agents and integrations are given far broader access than the task requires.
- Nobody knows who has used AI for what — or what has slipped out of the building.
- Manipulated input (prompt injection) can trick the model into leaking data or acting incorrectly.
- Data is encrypted in transit and at rest, and only what is necessary leaves the building.
- Least privilege: every agent and integration gets exactly the permissions the task requires — no more.
- Full logging of what the AI has seen and done, with alerts on abnormal behaviour.
- Input and output are filtered so prompt injection and data leaks are caught before they do damage.
How I secure your AI
Threat assessment
I map which data is in play, where it flows, and what can realistically go wrong — leaks, misuse, attacks or human error. Security starts with knowing what you are protecting.
Encryption all the way
Data is encrypted both in transit (TLS) and at rest. Sensitive fields can be encrypted or masked separately, so even a breach does not expose what matters most.
Access control & least privilege
Every user, agent and integration only gets access to exactly what the task requires. SSO, roles and MFA ensure the AI can never see more than the employee using it.
Secure integrations & secrets
API keys and passwords are kept in a secrets manager — never in prompts, code or logs. Connections to your systems are isolated and monitored.
Defence against prompt injection
Input is validated and output filtered, so manipulated content cannot trick the model into revealing data or performing unwanted actions. Agents run with clear limits and approval at sensitive steps.
Logging & monitoring
Everything the AI sees and does is logged, so you can trace and verify. Abnormal behaviour triggers alerts — and there is a clear plan for what happens if something goes wrong anyway.
Where I focus
Encryption & data flows
Data is encrypted, minimised and masked. I control what is sent to a model in the first place — and what never leaves the building.
Identity & access
SSO, roles, MFA and least privilege. People and AI agents alike only get the permissions the task requires — no more, no less.
Agent guardrails
Clear limits on what an agent may touch, and approval for sensitive actions. Defence against prompt injection and data leaks built in.
Monitoring & response
Logging, audit trails and alerts on abnormal behaviour — plus an agreed plan for what happens if an incident occurs.
The toolbox
If data must not leave the building at all, the solution can run on your own server with a local model — see AI & GDPR. Data security and GDPR go hand in hand: one is the technical protection, the other the legal foundation.
What it means for you
You know exactly which data the AI may see, where it is processed, and what is never sent out of the building
Least privilege, guardrails and filtering close the gaps that new AI usage would otherwise open
Every action is logged, so you can verify, document and react quickly if something happens
Security is not a single product but a way of building — I design it in from the start and keep watch over it in production.