agentic cybersecurity / ai agents / blue team

AI agent security that doesn’t stop at the audit

We audit the AI agents you run — prompt injection, tool permissions, MCP servers, and data exposure — against the OWASP Top 10 for Agentic Applications, then deploy blue-team agents that monitor, find, and fix vulnerabilities all the time.

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Why audit your AI agents

An AI agent reads text it did not write, then acts on it with your credentials. A conventional security review is built for code that only does what it was programmed to do, so it is not built to catch what goes wrong in between.

Run by people who build agents

The audit is done by the team that designs and builds AI agents, led by a founder with a master’s in cybersecurity — so every finding arrives with a fix that fits how agents actually work, not a generic warning.

Untrusted input is everywhere

An agent that reads emails, documents, web pages, or tool output can be steered by whoever wrote them. We trace every place untrusted text enters, and what the agent can do once it has.

Least privilege for every tool

What an agent can break is bounded by what its tools can reach. We map every tool and MCP server it can call and every credential it holds, then cut each one down to what the task needs.

A human check where it counts

Irreversible actions — payments, deletions, outbound messages, production changes — should wait for a person. We check which ones actually do, and which only look like they do.

A blue team that stays on

An audit is a snapshot, and prompts, tools, and dependencies change with every release. Our blue-team agents keep working after the report: monitoring, finding new vulnerabilities, and fixing them.

Answers for your security reviews

When an enterprise customer’s security review asks how your AI agent is secured, you answer with a threat model, findings, fixes, and re-test results — not a promise.

What we deliver

Agent Threat Model & Scope

We map each agent: what it is for, the data it reads, the tools and MCP servers it calls, the credentials it holds, and the actions it can take — then agree the scope in writing before any review starts.

Agent Security Review

Direct and indirect prompt injection, tool misuse, over-broad permissions, secrets handling, memory and data leakage, unsafe output handling, and missing approval gates — reviewed against OWASP’s agentic and LLM risk lists.

Findings Report & Remediation Plan

A prioritized report with where each issue lives, how to reproduce it, what an attacker gets from it, and the change that closes it — plus a re-test once your team ships the fixes. We can implement them ourselves if you want the work off your plate.

Blue-Team Agents, Always On

Defensive AI agents we deploy to actively monitor your systems, find new vulnerabilities as they appear, and fix them — continuously, not once a year.

Fixed-price packages

Fixed scope, fixed price. Need something larger? Book a call and we will scope it.

Fixed price

AI Agent Security Audit

$1,000USD

Agent threat model: data the agent reads, tools and MCP servers it calls, credentials it holds, actions it can take
Security review of prompt injection (direct and indirect), tool misuse, permissions, secrets, data leakage, output handling, and approval gates
Review against OWASP Top 10 for Agentic Applications and OWASP Top 10 for LLM Applications
Prioritized findings report with reproduction steps and the change that closes each finding
Re-test after your team ships the fixes, confirmed in writing

Book a call

Process

01
Map
We inventory your agents, their tools, and their permissions, and agree what is in scope and what a bad day looks like for your business.
02
Audit
Each agent is reviewed against OWASP’s agentic and LLM risk lists, with every finding reproduced and written up beside its fix.
03
Defend
Your fixes ship and we re-test them. Then blue-team agents take over the ongoing work of monitoring, finding, and fixing vulnerabilities.

What we audit against

Published, checkable frameworks — each card links to its official source.

OWASP Top 10 for Agentic Applications

OWASP’s list of the most critical security risks for autonomous and agentic AI systems, published in December 2025 — the baseline every agent review here starts from.

OWASP Top 10 for LLM Applications

The risks every LLM-powered system inherits — prompt injection, sensitive information disclosure, excessive agency — which an agent carries too.

NIST AI Risk Management Framework

NIST’s framework for managing AI risk, with its Generative AI Profile (NIST AI 600-1) — how findings are organized into a risk program rather than a one-off list.

MITRE ATLAS

MITRE’s public knowledge base of adversary tactics and techniques that target AI systems — used to model who would attack your agent, and how.

Faqs

Common questions about AI agent security

The term is used two ways: securing the AI agents a company runs, and using AI agents to do security work. This service covers both. We audit and harden your agents, then deploy our own blue-team agents to keep monitoring, finding, and fixing vulnerabilities after the audit ends.

The Cybersecurity Audit reviews conventional application code, dependencies, authentication, and cloud configuration. This audit covers what is specific to agents: untrusted text steering behavior, tools and MCP servers with too much reach, and actions taken without a human check. A product with an agent in it often needs both, and we can scope them together.

No. The audit is review-driven: we read the agent’s prompts, tool definitions, permissions, and code rather than attacking it from the outside, which shows us logic an external tester has to guess at. The ongoing work is blue team — defensive monitoring and fixing — not offensive testing. If you need a formal external pen test with an attestation letter, we will say so.

They keep working after the audit: actively monitoring your systems, finding new vulnerabilities as they appear, and fixing them. A one-off audit tells you where you stood on the day it ended; the blue team keeps that answer current.

No. We audit agents whoever built them — your in-house team, another agency, or an agent platform you configured — as long as we can see how they are wired: prompts, tools, permissions, and code.

No, and no audit like this can — SOC 2 reports are issued by licensed CPA firms. What it gives you is the technical evidence: a threat model, findings, fixes, and re-test results you can hand to your auditor or to an enterprise customer’s security review.

Yes, before anything is shared. Prompts, tool definitions, and findings are confidential by default and are never used as a public reference.

Explore other services

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Cybersecurity Audit

The conventional half — application code, dependencies, authentication, and cloud configuration reviewed against OWASP, NIST, and CIS.

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AI Agent Development

AI agents that call tools, query your systems, and complete multi-step tasks — with the guardrails and evaluation to run in production.

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LLM Integration & RAG

LLM provider integration and retrieval-augmented generation grounded in your own data, with evaluation and monitoring built in.

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Security & Compliance Audits

Which audit your product needs — cybersecurity, AI agent security, QA/UX, or HIPAA/GDPR — and how to run more than one together.

Let’s talk

Book a call with our CEO

Denys Havryliak

Founder & CEO

10+ years in Software Engineering
Master’s in Cybersecurity
Deep, current knowledge of AI tooling

You’ll talk to the person who builds. Denys works hands-on across product, architecture, and delivery — and keeps a close watch on what today’s AI tooling can genuinely do in production, not just in a demo.

Book a call with Denys