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Pillar Guide

AI security consulting, explained — and done properly.

Your team shipped AI features. Your security stack was never built to see them. This is what AI security consulting actually covers, what a serious engagement looks like, and how to judge any firm you talk to — including us.

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Why AI security is not application security

Traditional security tooling inspects code, networks and endpoints. AI systems fail differently: the attack goes through language and behaviour, not just code. A model can be manipulated by the content it reads. An assistant can be talked into leaking the data it was trusted with. An agent with tool access can be steered into taking actions nobody authorised.

The industry has catalogued these failure modes — the OWASP Top 10 for LLM Applications, the OWASP Top 10 for Agentic Applications, and MITRE ATLAS — but most security programmes still test none of them. The result is a gap: organisations with mature security postures and completely untested AI surfaces.

Prompt injection

Hostile instructions hidden in documents, emails or web pages hijack the model’s behaviour — the #1 LLM risk, and invisible to a web-app scanner.

Data leakage

Models over-share what they can reach. If the AI can read it, the wrong prompt can extract it — permissions become the whole ballgame.

Agentic abuse

AI agents hold credentials and take actions. A compromised agent is not a bad answer — it is an insider with tools. Read the agentic security guide →

What a serious AI security engagement covers

1. AI-augmented penetration testing

Web, API and LLM surfaces tested together — because attackers do not respect the boundaries between them. Autonomous agents run the relentless enumeration; senior human engineers validate what is actually exploitable. You get gaps ranked by business impact, not a 200-page scanner export.

2. Agentic detection & response

Continuous monitoring that plugs into the stack you already own — CrowdStrike, Microsoft Defender — with agents triaging millions of signals in milliseconds and a human pilot containing validated threats inside a guaranteed 15-minute window.

3. Governance evidence

Security work that regulators can verify: every control mapped to the frameworks your auditors use — EU AI Act, ISO 42001, NIST AI RMF, SOC 2 — with contemporaneous evidence, not after-the-fact write-ups. See the EU AI Act compliance guide for what enforcement now expects.

4. Sovereign AI deployment

When the finding is “your data leaves your boundary,” the fix is architecture: Vantage Workspace runs AI inside your own infrastructure, single-tenant and self-hosted, with every AI action signed to a named person.

$180k

The cost of one security generalist per year — 40 hours a week, generalist skills, high burnout. An AI-security consultancy with an agentic fleet delivers a 24/7 specialist capability for a fraction of that number. Run the math →

How to judge an AI security consultant

Whoever you talk to — including us — ask these five questions. The answers separate firms that test AI from firms that renamed their pentest.

  • Do you test LLM and agentic surfaces explicitly? Ask for OWASP LLM Top 10 and OWASP Agentic Top 10 coverage, by item.
  • Where does my data go when your tooling uses AI? The right answer involves dedicated infrastructure and locally hosted models — not third-party API calls with your incident data.
  • What evidence do I keep? Findings should map to the frameworks your auditors use, with a trail you can hand to a regulator.
  • Who responds when something is found — and how fast? A written SLA in minutes, not a best-effort promise.
  • Can I verify any of this before paying? A serious firm will let you start with a scored, self-serve assessment — no email gate, no sales call.

That last one is how most clients meet us: the free AI security assessment takes about 15 minutes and returns a scored map of your AI attack surface with your top gaps ranked by business impact.

EU AI Act compliance guide Agentic AI security guide The Automated Security Workforce Field Notes blog

Frequently asked questions

What does an AI security consultant actually do?
They identify and close the risks created by AI systems — penetration testing of LLM and agentic surfaces, detection and response tuned to AI-specific attacks, governance evidence for regulators, and secure architecture for AI deployments. The distinguishing skill is testing systems that can be attacked through language and behaviour, not just code.
How much does AI security consulting cost?
Engagements are typically priced as a fraction of one full-time security hire (about $180,000/year in North America). HANDVANTAGE uses annual security token budgets so capacity flexes to your needs instead of billing by the hour. The assessments that scope an engagement are free.
We already have a pentest vendor. Why is that not enough?
Most penetration tests cover web and network surfaces but never send a single adversarial prompt. If your products or internal tools use LLMs or agents, the highest-likelihood attacks — prompt injection, data exfiltration through the model, tool abuse — are outside your current test scope entirely.
How fast can an engagement start?
Same week. Start with the free scored assessment (15 minutes, self-serve), then a strategy session with a senior engineer — you leave that call with a roadmap whether or not you engage us.
Do you work with regulated industries?
That is most of our practice: financial services, healthcare, public sector, legal, fintech, and manufacturing/energy — organisations where the security work must also produce audit evidence mapped to frameworks like the EU AI Act, ISO 42001, HIPAA, FINRA and IEC 62443.

Find out where you stand.

Fifteen minutes, free, scored — and yours to keep whether we ever speak or not.

Take the AI security assessment → Book a strategy session