Security

AI Agent Security Services: least-privilege agents, tamper-evident logs, zero exceptions.

Autonomy raises the stakes on security, so we build it into the substrate. Agents act under least-privilege identities, inside guardrails that define what they may never do, with every action logged to a tamper-evident record. Security here is not a review at the end. It is the reason the board can approve autonomy at all.

0 agent actions outside the audit trail
100% actions logged, replayable & reversible
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Australia
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Denmark
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Outcomes

What you get, stated as results.

  • Least-privilege identity and runtime guardrails on every agent
  • A tamper-evident record ready for audit and regulators
  • Security modelled for autonomy, not retrofitted

Capabilities

What this practice covers.

Agent identity & access

Every agent runs under a scoped, revocable identity with least-privilege access to systems and data.

Guardrails & policy

Hard limits on what an agent may do, enforced at runtime. Not left to the model to respect.

Tamper-evident audit

An immutable record of every action, decision, and data touch, ready for regulators and internal audit.

Threat modelling for autonomy

We model the new attack surface autonomous systems create. Prompt injection, tool abuse, data exfiltration.

Data protection

Masking, residency, and encryption applied where agents read and write sensitive data.

Continuous assurance

Ongoing monitoring and red-teaming of live agents, not a one-time sign-off.

The stack behind this service.

Real tools our team works in day to day, not a generic capability list.

Cloudflare
Okta
AWS

How it works

A sequenced path, not a big bang.

0
Agent actions outside the audit trail

Model the threats

Map the attack surface autonomy introduces across identity, tools, and data.

Set the guardrails

Runtime policy defining the actions no agent may ever take, enforced in code.

Instrument everything

Tamper-evident logging wired into every agent action and data touch.

Assure continuously

Live monitoring and red-teaming keep assurance current as agents change.

Proof, Not Promises

Real engagements, the results attached to each one.

41 injection attempts blocked during adversarial testing

Regional insurer, Florida

Authorisation defects reduced from 23 findings to zero

Private clinic group, South East England

Where it applies

Ten industries. One audited standard.

Different regulations, different systems of record — the same discipline every time: agents that run inside guardrails and leave a record you can read.

View all industries →

Security case studies

Challenge, solution, results. What this practice has shipped.

Anonymised at the client's request. Each card states the pain point, what we built, and what changed. Plus the service type and country.

02 studies
AI Agents USA

Guardrails and audit trail for a Florida insurer's claims agents

Regional insurer, Florida

Challenge
The insurer's claims agents could read policy records, draft correspondence and trigger payments under a threshold. Internal audit asked how the company would prove an agent had not been manipulated by a malicious claim document, and nobody could answer with evidence rather than assurances.
Solution
AGS added a guardrail layer: prompt-injection screening on every document, allow-listed tools per agent with per-action approval rules, and a tamper-evident log that records inputs, reasoning summaries and actions. We ran adversarial tests with crafted claims and handed audit a report they could reproduce.
Results
  • 41 injection attempts blocked during adversarial testing
  • Every agent action reconstructable within 30 seconds
  • Audit findings closed in 5 weeks
Service type · AI AgentsCountry · USA
Web UK

Authorisation overhaul for a private clinic group patient portal

Private clinic group, South East England

Challenge
A routine review found the patient portal's role checks were inconsistent: some pages relied on hiding links rather than enforcing access, and a receptionist account could reach clinical notes via a direct URL. With 40,000 registered patients, the group needed this fixed before it became an incident.
Solution
We replaced ad-hoc checks with a single authorisation policy enforced on every request, mapped to the group's staff roles, and added access logging by record. A full test suite exercises each role against each resource, and the group's clinical safety officer signed off before release.
Results
  • Authorisation defects reduced from 23 findings to zero
  • Full role-by-resource test suite runs in 4 minutes
  • Fixed and re-tested within 6 weeks
Service type · WebCountry · UK

FAQ

Security: questions, answered.

How do you secure autonomous AI agents?

We build security into the substrate. Agents act under least-privilege, revocable identities, inside runtime guardrails that define what they may never do, with every action logged to a tamper-evident record. Security here is not a review at the end. It is the reason the board can approve autonomy at all.

What new security risks do autonomous agents introduce?

Autonomy creates a new attack surface: prompt injection, tool abuse, and data exfiltration. We model these threats across identity, tools, and data, then enforce hard limits at runtime rather than leaving the model to respect them, and red-team live agents continuously as they change.

Can you prove what an agent did for auditors and regulators?

Yes. Every action, decision, and data touch is written to an immutable, tamper-evident record. Zero agent actions fall outside the audit trail. It is ready for regulators and internal audit, so you can replay exactly what an agent did and why, without reconstructing it after the fact.

Are guardrails enforced by the model or by the system?

By the system. Guardrails are hard limits on what an agent may do, enforced at runtime and in code, not left to the model to honour. That distinction is what lets least-privilege identity and policy hold even when a prompt tries to push an agent past its bounds.

Is security a one-time review or ongoing?

Ongoing. Continuous assurance means live monitoring and red-teaming of agents in production, not a one-time sign-off. Because agents change as workflows shift, assurance is kept current. Threats are re-modelled, guardrails updated, and the audit trail reviewed rather than filed and forgotten.

Put Security to work.

Tell us the workflow. We'll show you the shortest path to a running agent.

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