Agentic AI security and AI agent identity
AI agents that hold only the access they need, for only as long as they need it
Agents with keys to everything
AI agents now read documents, call APIs and move data on their own. Each one is a non-human identity (NHI): an account, key or token used by software rather than a person. Agents are often given long-lived keys with broad rights, and nobody reviews what they do with them.
Attackers have noticed. A crafted document can instruct an agent to leak data (prompt injection), a poisoned tool description can redirect it (tool poisoning), and a stolen key can run up a bill on your models (LLMjacking).
What changes for you
No standing privileges
Agents receive short-lived credentials for each task and hold no access between tasks.
Attacks found before attackers find them
Your agents and models are attacked on purpose, in a controlled way, and the weaknesses are fixed.
Data that stays in
Sensitive data cannot leave through a model's answers, its logs or a stolen key.
What we deliver
AI agent identity
Each agent gets its own identity, owner and purpose, managed in your identity and access management (IAM) like any other account, with every action logged.
Dynamic just-in-time credentials
Credentials issued for one task and expired when it ends, so a leaked token is worth little and no agent holds access it is not using.
AI red-teaming
Controlled attacks on your models and agents, including jailbreaks, prompt injection and tool poisoning, with every finding reproduced, ranked and retested after the fix.
Prompt-injection and tool-poisoning firewalls
Guardrails between agents, their inputs and their tools that detect and block instructions hidden in documents, web pages and tool descriptions.
LLM data-leakage prevention
Controls that stop personal and confidential data from leaving through prompts, answers or logs, for sovereign and hosted models alike.
LLMjacking defence
Model keys kept in a vault, usage limits and alerts on unusual consumption, so a stolen key is caught before it costs you.
Model supply-chain audits
Checks on where your models, weights, datasets and agent tools come from, and whether anything has been altered.
How the work runs
List the agents
We find every agent, model and tool in use, the identities they hold and the data they can reach.
Model the threats
For each agent we work out what an attacker would target and how, from its inputs to its tools.
Red-team
We attack the agents and models within agreed rules and record every finding so it can be reproduced.
Harden
We introduce agent identities, just-in-time credentials, guardrails and leakage controls, starting with the highest risks.
Retest and monitor
We retest every fix and set up monitoring for agent behaviour and model usage.
Proof in production
We build the multi-agent systems we secure. In a regulated financial institution, our agents work under human supervision and permission-aware retrieval, so each one sees only the documents its user may see.
Standards and tools
- AI and machine learning
- Jais
- Mistral
- Security and cryptography
- HashiCorp Vault
- Standards and regulations
- EU AI Act
- GDPR
- MENA PDPL
How to start
What happens next
Pre-consulting session
A free 30-minute online pre-consulting session: we go through your goals, systems and constraints.
Readiness review
In a free 48-hour readiness review, a Principal Architect checks your project against the 6-point Definition of Ready and recommends the track that fits.
Choosing the track
Scope-ready projects receive a binding proposal within 3–5 business days. Concept-stage projects start in the Blueprint Studio. A live system that is failing, undocumented or needs integration starts with a diagnostic of 1–2 weeks. The Blueprint Studio and the diagnostic each have a fixed fee, quoted in the proposal.
Delivery in five stages
Mobilisation, sprints with live demonstrations, integration and hardening, acceptance and go-live, then managed services. After launch comes a warranty period, then optional support and maintenance.
Embedded specialists and strategic augmentation
Nearshore and on-site principal engineers and specialists, and embedded solution, transformation, PQC and integration architects.
AI-native product teams
Managed, cross-functional pods of senior engineers, equipped with agentic coding and QA harnesses.
The quickest way in is the Post-quantum (CBOM) and agent security audit package, one of our rapid engagement packages.
Questions and answers
What is a non-human identity, and why does it matter for AI?
A non-human identity is any account, key or token used by software instead of a person: service accounts, API keys, and now AI agents. They are easy to create and easy to forget, and many never expire. An AI agent that acts on its own with such a key can do a great deal of harm if it is misled or the key is stolen.
What is prompt injection?
An attack that hides instructions in content an AI model reads, such as an email, a document or a web page, so the model follows the attacker instead of its user. It cannot be prevented by the model alone. Defence combines guardrails on inputs and outputs, agents with limited access, and human approval for sensitive actions.
How do just-in-time credentials work for agents?
Instead of a permanent key, the agent asks for access when a task starts. It receives a credential limited to that task and that time, and the credential expires when the task ends. Every request is logged, so you can see which agent did what and on whose behalf.
What does an AI red-team exercise involve?
We agree the scope and rules, then attack your models and agents the way an adversary would: jailbreaks, prompt injection, tool poisoning and attempts to extract data. You receive every finding with the steps to reproduce it, ranked by risk, and we retest after the fixes.
Can you secure agents and models we did not build with you?
Yes. Identity, credentials, guardrails and monitoring sit around the agent, so they work with agents built in-house, by another supplier or on a vendor's platform. We need access to the agent's configuration and its connections, not necessarily its code.
We use a hosted model from a large provider. Is our data safe?
It depends on the provider's terms, the region it runs in and what you send it. We review those three, add leakage controls in front of the model and, where the data may not leave your jurisdiction, recommend a sovereign or private model instead.
Ready to build? Ask for a proposal.
Send your requirements or RFP. Our architects validate them and return a binding, fixed-scope proposal.
What happens next
Readiness review
In a free 48-hour readiness review, a Principal Architect checks your project against the 6-point Definition of Ready and recommends the track that fits.
Binding proposal
After architecture validation at no cost, you receive a binding, fixed-scope proposal within 3–5 business days: milestones, architecture, team structure and SLAs. We sign a non-disclosure agreement (NDA) with you on request, before you share your requirements.
Mobilisation
Once you sign, our engineering pods begin Sprint 0 within 5–10 business days of contract signature.
Delivery in five stages
Mobilisation, sprints with live demonstrations, integration and hardening, acceptance and go-live, then managed services. After launch comes a warranty period, then optional support and maintenance.