AI risk, data protection and human oversight

AI Security & Guardrails

Understand where your AI tools could expose information or act beyond their intended limits. Review selected AI tools, assistants and workflows, test agreed safeguards, and get practical changes your team can implement.

  • AI risk register tied to your selected use cases
  • Guardrail recommendations and agreed configuration changes
  • Test results, ownership and an operating handover
The question we help answer

Your team is using AI. Are the right controls in place?

An assistant may have access to customer records, shared documents or tools that can change a system. The important question is what information it can reach, which actions it can take and when a person needs to approve the result. We review these boundaries for the use cases you select.

Inside the service

What the engagement covers

Map AI use and information flows

  • Identify the purpose, business owner, users and connected data sources for each selected use case
  • Review what information enters the service and available provider retention or training settings
  • Record sensitive information, third-party dependencies and evidence we cannot access

Review permissions and decision boundaries

  • Check user and service-account access, tool permissions and separation between customers or workspaces where relevant
  • Define which messages, record changes and consequential actions require human approval
  • Review least privilege, secrets handling, output validation and limits on tool use

Test the agreed safeguards

  • Use approved test data to examine prompt manipulation, sensitive information disclosure and unsafe actions within scope
  • Check rejection, escalation, approval and exception handling against agreed criteria
  • Document observed results and limits; model behaviour and provider settings can change

Design improvements and hand over

  • Prioritise policy, configuration and application-control changes by business impact
  • Include agreed guardrail configuration or implementation only with explicit change approval
  • Define ownership, logs, monitoring, manual recovery and the conditions for retesting
What you receive

An AI risk and guardrail action pack

  • Use-case and data-flow summary with the review boundary
  • Evidence-linked findings and a prioritised guardrail action register
  • Agreed design or configuration changes and test results
  • Operating guidance for approvals, exceptions and review ownership
What we need

Information and permissions agreed first.

  • Selected AI tools, use cases, owners and deployment information
  • Approved test accounts and synthetic or redacted test records
  • Relevant access, data-handling and acceptable-use settings
  • Agreed permission to test connected applications and tools
Fictional example — not client work

An AI assistant can draft a reply, but should it send it?

The situation

A fictional assistant can read a shared folder and prepare customer replies. Its connected account can also send messages without a separate approval.

The practical response

The business agrees a narrower account, an approved data source and a human approval step before sending. Test messages containing misleading instructions are routed to review.

What this example shows

The example demonstrates the boundary and test approach. It does not show a real client result or prove that every prompt-manipulation attempt is prevented.

A clear process

From the question to practical action.

Keeping the scope clear

What is outside the engagement

  • A guarantee that prompt injection, data leakage or incorrect model outputs can never occur
  • Legal opinions, model certification or a blanket assessment of every AI tool used by your business
  • Unlimited model development, full automation builds or ongoing monitoring unless separately agreed
Common questions

Before you start

How are price and timing agreed?

Before work begins, we agree the scope, deliverables, fee and delivery schedule in writing. Tell us about any deadline in your initial enquiry. Submitting the form does not confirm a booking or start paid work.

Is this different from your automation service?

Yes. This service reviews and improves safeguards around selected AI use. The automation service builds a specific workflow. They can be combined only through an agreed scope.

Can you implement guardrails as well as review them?

Agreed configuration or implementation work can be included where the platform supports it, with approved access, change controls and validation. The scope identifies what is advice and what will actually be changed.

Can guardrails make AI completely safe?

No. Controls reduce particular risks within their tested limits. Human oversight, permissions and operating checks remain important as the system changes.

Discuss AI security and guardrails

Tell us which AI tools or workflows you use, what information they handle and which actions concern you. Do not send real customer records or confidential prompts. Please keep passwords, sensitive records and configuration exports out of the initial enquiry.

Discuss AI security and guardrails

Relevant guidance

These links provide background for the review approach. Cyber Evident is not affiliated with or endorsed by the publishers.