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LLM security testing examines AI-powered features, such as chatbots, copilots, RAG search and autonomous agents, for vulnerabilities that traditional testing misses. Large language models can be manipulated through their inputs, leak sensitive data or take unsafe actions through connected tools. We test these risks before attackers or curious users find them.
Our testing is aligned with the OWASP Top 10 for LLM Applications. We review how your model, prompts, retrieval pipeline and tools are connected, then run targeted manual attacks and repeatable test cases against the live feature. The surrounding web application and APIs are tested too, because most AI incidents happen at these boundaries.
Read our articles on LLMs in cybersecurity and large language model security risks.
Chatbots, customer support assistants, internal copilots, RAG-based search, and AI agents built on commercial, open-source or custom models.
No. Most testing is performed through the same interfaces your users have. Access to prompts, architecture and tool configuration helps us test more thoroughly.
Model updates, new prompts and new tools can introduce new risks, so we recommend retesting after significant changes.
Tell us about your environment and timelines and we will send a clear, fixed-scope proposal. Contact Offensium Vault or book a free call with our team.
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