Key takeaways
- Treat AI responses as untrusted outputs.
- Check permissions at your application boundary, not in the prompt alone.
- Keep evaluation, monitoring and incident response in the release process.
Editorial note: Educational sample content for review; not a newly reported or independently fact-checked news story.
Start with the threat model
Identify what a malicious prompt or compromised document could do. Common risks include prompt injection, data leakage, excessive agency and unsafe downstream use of model outputs.
Model-generated text must never bypass normal authorization checks or input validation.
Protect the tool boundary
Validate parameters, constrain destinations, isolate credentials and require confirmation for consequential actions. Do not allow the model to fetch arbitrary internal URLs or execute unrestricted commands.
Build an evaluation discipline
Use representative task suites, attack simulations, red teaming, logs that respect privacy and rollback plans. Publish what a system can and cannot do instead of overstating certainty.
Sources & further reading
Primary sources and learning resources. Verify specific product and research claims directly.
