LLM Penetration Testing Services
Packages & Pricing.

LLM penetration testing for chatbots, agents and RAG apps

LLM penetration testing attacks your AI application the way an adversary would. Omeiro tries direct and indirect prompt injection, jailbreaks, data extraction and abuse of the tools your agent can call, then reports what worked.

Higher tiers test the connected APIs, RAG data access and re-test after fixes.

LLM penetration testing: scope, environment and what is attacked

The model is only one part of the target. LLM penetration testing also covers the system prompt, retrieval sources, tools the agent can call and the permissions behind them, because indirect prompt injection often arrives through a document or web page the model reads. Before ordering, describe what the app can do, what data it can reach and what outcome would worry you most, such as leaking another customer's records or taking an unapproved action.

A test environment keeps risk low. LLM penetration testing sends hostile prompts and may trigger real actions, so use staging data and low-privilege accounts where possible, with limits on spending. Share architecture notes, model providers and any guardrails you already use. Remember that results describe a moment in time, since prompts, models and tools change. Plan retesting after major changes, and treat each finding as a design question about permissions, not only a wording problem.