Generative AI Security Testing

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Independent, CREST-accredited security testing for generative AI systems and features. Generative AI and GenAI are the same thing, and this is the page for both.

What is generative AI security testing?

Generative AI security testing is the hands-on assessment of anything in your product that generates content: text, code, images, audio, summaries, replies. It asks the questions a scanner cannot. Can the feature be talked out of its instructions? Can it be made to disclose another customer's data, your system prompt, or the contents of a document it was never meant to quote? Can it be driven to produce output that is unsafe when something downstream acts on it?

The thing being tested is not the model. It is your integration: the prompt you wrap around it, the data you give it access to, the tools you let it call, and what your application does with whatever comes back.

Why it matters

Generative features sit in public, accept free text, and are usually wired into something that matters. That combination is unusual. An attacker needs no exploit kit and no credentials, only a text box and patience, so the barrier to a first attempt is close to zero and the attempts are already happening to anything that has shipped.

Three things tend to go wrong in practice. Data leaks sideways, because retrieval was scoped to the corpus rather than to the user. Guardrails hold against the obvious prompt and fold against an indirect one, delivered in a document or a web page the model reads rather than typed by the user. And generated output is trusted: code that gets executed, markdown that gets rendered, a summary that drives a decision, a tool call that spends money or sends an email.

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How Solusec tests it

We work from the OWASP Top 10 for LLM Applications as a coverage baseline, then test adversarially against your specific feature, because the interesting findings are always in the integration rather than in the generic list. Direct and indirect prompt injection, system prompt and training data disclosure, retrieval scoping and tenant isolation, guardrail and content-filter bypass, insecure handling of generated code and markup, excessive agency where the model can call a tool with real-world effect, and denial of wallet where a cheap prompt buys expensive inference.

Every finding is reproduced and validated by hand before it reaches the report, with the exact prompt or sequence that produced it, so your developers can confirm the fix rather than take our word for it.

What we test it against

Chatbots and customer-facing assistants, copilots embedded in a product, document and email summarisation, code generation, image and asset generation, and RAG pipelines that put your own content in front of a model. If a feature takes input from a person or a document and produces content, it is in scope.

AI testing, led by a human

Solusec is one of the first organisations 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.

Talk to us about testing

Tell us what you need looked at and we will tell you what the work actually involves, what it costs and when we can do it. CREST accredited, and the testing is done by the person you speak to.

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