LLM Security Assessment

A structured review of your large language model system's security posture, risks and controls.

What is LLM Security Assessment?

An LLM security assessment is a systematic review of how secure your LLM system is: its architecture, data flows, guardrails, access controls and exposure to the OWASP LLM Top 10.

Why it matters

Before you can fix AI risk, you need to understand it. Teams shipping LLM features often lack a clear picture of where the exposure is and which risks matter most for their use case.

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How Solusec tests it

We assess your LLM system against a recognised framework, identify and prioritise the gaps, and give you a practical roadmap, with the option to follow up with hands-on penetration testing.

AI testing, led by a human

Solusec is one of the first firms worldwide accredited under CREST's AI-Enabled Penetration Testing standard, so our use of AI is independently assured: responsible, transparent and always human-led. You get faster, broader testing, your data stays out of public AI tools, and every finding is validated by a qualified tester. Read about the accreditation.

What you get

You get a clear, prioritised report mapped to business risk, a walkthrough of every finding with practical fixes your developers can action, and a free retest once you have remediated. No scanner dump, no jargon, no sales team: you deal directly with the tester.

Common questions

Is an assessment the same as a pen test?

No. An assessment reviews posture and controls; a pen test actively attacks the system. Many clients start with an assessment and add testing where risk is highest.

Do you give a roadmap?

Yes, prioritised by risk and effort, so you know what to fix first.

How quickly can testing start?

After a short, free scoping call we give a fixed price and a start date, often within days.

Is your AI use safe and independently assured?

Yes. Solusec holds CREST's AI-Enabled Penetration Testing accreditation, which independently assures that our AI use is responsible, secure and human-led.

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