The AI security gaps most orgs don't catch until it's too late
The AI security gaps most orgs don't catch until it's too late
A practitioner's guide to inventory, permissions, logging, and incident response for AI tools already running in your environment.
Every organization we've worked with thought they were fine on this.
Inventory
An organization finds out they're running twelve AI tools, six of them quietly sending data to third-party servers. Nobody decided that. It just happened, one convenient tool at a time.
Permissions
An agent with read access to staging finds a production credential in an environment variable, and uses it, because nothing was scoped to stop it. It's the default when nobody sets the boundary.
Logging
A database gets deleted. No logs explain why. The team spends a week hunting a threat actor that was never there, because the actual cause, an AI agent, was never even a suspect.
Incident response
A SOC analyst triages an AI-caused incident like a ransomware precursor. They check for C2 infrastructure and review lateral movement. None of it applies. The playbook never had a branch for this.
People
Someone pastes a credential into a chat tool to save five minutes. Nobody told them not to, because nobody had said it out loud.
The guide walks through what each of these five actually needs: inventory, threat modeling, permissions, logging, and IR readiness. Scoped the same way we'd scope it for a client, free.