LLM Application Security Assessment

It evaluates an application that embeds a large language model — testing prompt injection (direct and indirect), improper output handling, sensitive information disclosure, excessive agency, RAG and embedding weaknesses, tenant isolation, and unbounded consumption — following the OWASP Top 10 for LLM Applications and the OWASP AI Testing Guide, with each finding proven and rated.

A model assessment looks at the model itself — its behavior, its robustness, its training and alignment. An application assessment looks at how a model is wired into a product: the prompts, the tools, the retrieval, the output handling, and the access controls around it. Most real-world risk lives in the application layer, which is what this service tests.

It is an attack where the malicious instruction is not typed by the attacker into the chat, but hidden in content the model later reads — a document, a web page, an email, or a RAG source. When the model retrieves that content, it follows the injected instruction as if it were a legitimate one. It is dangerous because the victim is the model's own trusted data path.

Yes. We test whether retrieval respects the user's permissions (so one user cannot retrieve another's documents), whether the RAG source can be poisoned to steer the model, and whether embedded content can carry an indirect injection. Retrieval is one of the most common places an LLM application leaks data.

Excessive agency is when the model can call tools or take actions broader than the task needs — delete records, send messages, make purchases, reach internal systems. If an injection can steer the model, that agency becomes the attacker's. We check that tools are scoped to least privilege and that high-impact actions require a human check.

We map where prompts and outputs travel — what is logged, what is sent to a third-party provider, and what leaves your boundary — and flag it as part of the assessment. During testing we use scoped, non-sensitive data where possible and agree in advance what may be used, so the test itself does not create exposure.

Many tests are read-only conversations and are safe. Tests that could trigger a tool or an action — a purchase, a message, a deletion — are agreed in advance and run carefully; we prefer a staging environment that mirrors production, and when we must test production we set limits and keep a contact on your side to pause at once.

Each finding gets a CVSS score for a common baseline, adjusted by the real impact — what data or action it reaches, how easily, and whether it crosses a user or tenant boundary — and is mapped to the OWASP Top 10 for LLM Applications. That is why two issues with the same score can be prioritized differently.

Duration depends on the application's complexity — the number of tools, the RAG sources, and the user roles. A typical assessment runs about two to four weeks, and we give a firm estimate after scoping. Re-testing after you remediate is included, to confirm each fix holds.