AI agent security

Your agents have access to your data. Do you know what a prompt injection can make them do with it?

LLM agents connect to your email, your files, your APIs, and your workflows. That's exactly why they're useful — and exactly what attackers now target. Prompt injection, jailbreaks, and indirect attacks turn a helpful assistant into an unwitting insider. We harden agents and AI applications before they're in production — and test the ones that already are.

Delivered by security practitioners who assess model risk and build guardrail architectures for regulated enterprises — not a vendor selling its own platform.

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Free scoping call

The threat model

Agents have a unique attack surface

Traditional security assumes a human sits between the attacker and the data. With autonomous agents, that assumption is gone. Our assessments rate each attack class and map it to the control that closes it.

Attack 01 / 06

Critical

Direct Prompt Injection

A user or attacker issues instructions that override the system prompt, coercing the model into actions outside its intended role — such as ignoring safety rules or revealing hidden context.

Control: Input classification, system-prompt hardening, and separation of untrusted instructions from trusted instructions.

Attack 02 / 06

Critical

Indirect Prompt Injection

Malicious instructions hidden inside content the agent fetches — a webpage, an email, a document, or an API response — hijack the agent without any direct interaction with the attacker.

Control: Tool-call allowlisting, content provenance checks, and least-privilege tool scoping.

Attack 03 / 06

High

Jailbreak

Adversarial phrasing or encoding bypasses the model's safety alignment, unlocking disallowed capabilities — data access, code execution, or harmful outputs.

Control: Layered guardrail policy, output filtering, and continuous red-team testing after each model update.

Attack 04 / 06

High

Data Exfiltration

A manipulated agent is induced to return an internal dataset or secret — via direct output, encoded output, or a crafted tool call such as emailing a file to an attacker-controlled address.

Control: Outbound egress controls, data-loss-prevention rules on tool calls, and anomaly detection on agent response behavior.

Attack 05 / 06

Medium

Tool / Privilege Abuse

An agent holding broad tool access (email, files, APIs) is steered into destructive or business-impacting actions — deleting records, approving transactions, or modifying configs.

Control: Per-tool allowlist, human-in-the-loop approval gates for high-impact actions, and session isolation.

Attack 06 / 06

Medium

Model & Supply Chain Risk

Third-party models, plugins, and agent frameworks carry their own vulnerabilities, poisoning, or data-handling exposure. A dependency change can silently open a new attack path.

Control: Model/plugin inventory, version pinning, and vendor security review across the agent supply chain.

What we deliver

Six workstreams, one hardened agent estate

Each workstream is scoped to your stack and regulatory environment. We produce findings you can act on, controls you can operate, and tests you can re-run after every model or prompt change.

Workstream 01 / 06

Agent Architecture Review

We map your agent topology — models, tools, data flows, and human approval gates — and identify where an attacker can reach sensitive data or trigger high-impact actions.

Workstream 02 / 06

Prompt & Guardrail Design

System-prompt hardening, instruction hierarchy, and input/output guardrails engineered for your specific business logic — not a generic policy dump.

Workstream 03 / 06

Tool & Data Access Governance

Least-privilege tool scoping, allow/deny lists, and human-in-the-loop approval gates placed on the actions that matter most.

Workstream 04 / 06

Adversarial Red-Teaming

We attack your agents with realistic prompt injection, jailbreak, and exfiltration techniques — and document every path and the control that closes it.

Workstream 05 / 06

Monitoring & Detection

Anomaly detection on agent behavior, outbound egress controls, and logging that gives you a forensic trail when a compromise happens.

Workstream 06 / 06

Ongoing Testing Cadence

Automated regression tests that re-run after every prompt, model, or tool change — so a Monday release can't silently reintroduce a Thursday vulnerability.

Methodology

Test what you ship — then keep testing

AI security isn't a one-time review. A prompt change, a new tool, or a model upgrade can reintroduce a vulnerability tomorrow. We set up the testing cadence that keeps pace with your releases.

OWASP LLM Top 10 as our map

Every finding is mapped to the OWASP Top 10 for Large Language Model Applications — the de-facto standard your security and compliance teams already reference.

NIST AI RMF alignment

Controls align to the NIST AI Risk Management Framework and NIST CSF 2.0 where relevant, so agent security lands in your broader governance program instead of sitting apart.

Test, fix, re-test

We don't hand you a list and leave. The deliverable is a hardened state plus a test harness you can run continuously.

Vendor-agnostic

We don't sell a platform. Recommendations are tool-agnostic and sized to what you actually run — no forced migrations, no lock-in.

The process

From first call to hardened agents in five steps

01

Scoping call
Step 01

30-minute call to map your agent deployment, the tools and data in scope, and the business functions agents touch. We scope the review to your actual architecture.
02

Architecture & threat modeling
Step 02

We document the agent topology and build a threat model focused on prompt injection, jailbreak, and data-exfiltration paths — the attacks agents are uniquely exposed to.
03

Adversarial testing
Step 03

We run realistic attacks against your agents and their tool chains, capturing each successful path and rating its severity. No synthetic demo payloads — tests tailored to your setup.
04

Hardening & controls
Step 04

We implement or specify the fixes: guardrails, tool permissions, approval gates, and monitoring — designed to be operated by your team, not lock you into a vendor.
05

Test harness & handoff
Step 05

You receive the findings, the hardened configuration, and a continuous testing harness so your team can re-verify after every release. Ownership stays with you.

The moment an agent can act on its own, prompt injection stops being a curiosity and becomes a remote code execution on your business logic.

— Principle Security Advisory Team

Questions

What you asked before the call

Is this just a penetration test?

Partially, but broader. A standard pentest tests your network and applications. Agent security tests the model, the tools, and the trust boundary between a manipulated agent and your data — an attack surface traditional tests miss.

We don't have 'agents' — do we need this?

If you use an AI assistant with access to email, files, or APIs — including Copilot, ChatGPT with tools, or internally built assistants — you have an agent surface. The more access it has, the more it's worth hardening.

How long does a review take?

A focused scoping call leads to a review spanning 1–3 weeks depending on the number of agents and tools in scope. The test-harness handoff is included.

What do we get at the end?

A findings report mapped to OWASP LLM Top 10, a hardened configuration or implementation plan, and a re-runnable test harness. Everything is in your name — no vendor lock-in.

Do you need access to our production environment?

We work in a staging or test copy wherever possible. Where production access is needed, it's scoped, read-only where feasible, and protected by an NDA.

How does this relate to an AI risk assessment?

An AI risk assessment (our /ai-assessment) governs your overall AI posture — model risk, regulation, data governance. Agent security is the hands-on hardening of the systems themselves. Many clients start with the assessment, then run a technical agent review.

Ready to start

Don't learn about prompt injection from an incident

Request an AI agent security review. We'll map your agent architecture, show you where the data-exfiltration and manipulation paths are, and harden what you're shipping.

Attack classes assessed

Hardening workstreams

1–3

Weeks to hardened state

Vendor lock-in

Request an agent security review →

Explore

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