AI moves fast. New models are adopted, get updated, configurations drift. Keeping track of it all is hard, and catching security issues before they become incidents can feel impossible.
That is why, as part of our latest release, we’ve added Resource Policies to FireTail.
Resource Policies make it simple to set automated guardrails around your AI resources. They watch for changes, flag anything that matches your policies, and generate alerts as soon as something important happens. Instead of reacting to problems, you can get ahead of them.
What Resource Policies do
Resource Policies are rules you define in FireTail. Each policy monitors your resources continuously. When FireTail detects a new resource, change or a configuration that matches a policy, it creates an event and raises an alert.
This gives security teams:
- Continuous visibility into changes across their AI environments
- Immediate alerts when something falls out of compliance
- Less manual monitoring and fewer blind spots
Resource Policies make posture management proactive instead of reactive.

How it works
Getting started with Resource Policies in FireTail is easy:
- Create a Resource Policy in the FireTail console
- Define what it should look for (for example, any new high risk model in code or cloud)
- FireTail monitors your resources automatically
- When a match or change is detected, FireTail creates an event and sends an alert
A simple policy can be created in under a minute. Once it’s live, FireTail handles the monitoring and alerting for you.
See the results in your event stream
Each time a Resource Policy is triggered, FireTail logs it as a new event. You can see exactly what changed, when it changed, and which policy caught it.
This makes it easy to investigate changes, respond quickly and prove that controls are being enforced.
Why this matters
Resource Policies give security teams confidence and control in fast-moving environments. And they are not just about security alerts. They also give teams a way to enforce governance in fast-changing environments. Many organizations have clear requirements around how AI resources can be used: which model providers are approved, which regions data can be processed in, or which configurations are acceptable.
With Resource Policies, these rules can be codified and continuously enforced. If your policy specifies Anthropic enterprise, FireTail can alert you the moment a resource points to another provider. If your compliance obligations require data to stay in the US or EU, FireTail will flag any drift into unsupported regions. This moves governance from a static checklist to a real-time safety net.
- Reduce risk by catching changes the moment they happen
- Speed up response times with instant alerts
- Cut down on repetitive manual checks
They turn your security posture from a periodic audit into a real-time system.
Get started
Resource Policies are available now. You can start by creating a simple policy to detect any new AI resource that is missing a security tag.
Read the full setup guide here: Resource Policies Documentation
Once your first policy is in place, you’ll get immediate visibility into every change that matters.
FireTail gives security teams the tools to keep up with your AI resources as they change. Resource Policies are the latest step in making that process simple, fast and reliable.
If you would like to see the power of FireTail’s API security platform for yourself, start a free trial today…
*** This is a Security Bloggers Network syndicated blog from FireTail - AI and API Security Blog authored by FireTail - AI and API Security Blog. Read the original post at: https://www.firetail.ai/blog/introducing-resource-policies-for-continuous-ai-security