Free RAG & Agent Security Lab
Hands-on, simulated labs on AI-agent security — RAG data poisoning, excessive agency / tool abuse, and tool-based SSRF & data exfiltration — with the defence for each. Free, from Neurobyte.
About this lab
Retrieval-augmented generation (RAG) and autonomous agents make AI applications far more capable — and far more attackable. This free RAG and agent security lab offers hands-on, simulated scenarios covering RAG data poisoning, excessive agency and tool abuse, and tool-based server-side request forgery (SSRF) and data exfiltration, with the defence demonstrated for each attack.
It's aimed at developers and security teams building agentic systems, where a single over-permissioned tool or a poisoned document can turn a helpful assistant into an attacker's instrument. Practising these attacks in a safe lab is the fastest route to designing agents that fail safely. Combine it with our Prompt Injection Lab and Secure AI Deployment Checklist.
Frequently asked questions
What attacks does the RAG and agent lab cover?
RAG data poisoning (planting malicious content in a knowledge base), excessive agency and tool abuse (an agent doing more than intended), and tool-based SSRF and data exfiltration — each paired with its defence.
Why are AI agents risky?
Agents can take actions through tools and APIs, so an injection or a poisoned document can cause real-world effects. Over-broad permissions and unvalidated inputs/outputs turn a helpful agent into an attack vector.
How do I secure a RAG or agent system?
Apply least privilege to tools, validate and constrain inputs and outputs, isolate and vet retrieved content, and monitor agent actions. Practise the failure modes here, then self-assess with the Secure AI Deployment Checklist.