Protect your own AI applications against prompt injection, data leakage and misuse.
When you build chatbots, copilots or AI agents, new risks appear: prompt injection, jailbreak attempts, data leakage from retrieved documents and misuse of connected tools. The OWASP Top 10 for LLM applications lists these risks and is the baseline for AI application security.
LLM guardrails filter inputs and outputs, enforce model access control, restrict what RAG security pipelines retrieve and log activity. SecureBeans configures Azure AI Content Safety and Microsoft security controls and arranges AI red teaming to test them before launch.
LLM guardrails are controls around a large language model application that filter harmful or malicious inputs and outputs, prevent data leakage and restrict what the model and its tools can do.
Prompt injection is an attack where crafted text - typed by a user or hidden in a document or webpage - manipulates an AI model into ignoring its instructions, leaking data or taking unintended actions.
It is a community list of the most critical security risks for applications built on large language models, including prompt injection, sensitive information disclosure and excessive agency.
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