Your AI Agent May Be Secure. Your Old Server Probably Isn’t.

This article argues that attackers do not need to attack AI systems directly when legacy infrastructure already provides a path to compromise them. AI agents inherit access from identity providers, cloud roles, service accounts and developer environments. A chain involving an unpatched Tomcat server, Active Directory misconfiguration and overprivileged AWS access keys could expose an AI agent’s data source. The article recommends exposure management that treats AI dependencies, such as storage buckets and functions, as critical assets and maps attack paths across infrastructure, identity, cloud and AI.

Everyone is busy worrying about prompt injection, model poisoning and AI hallucinations. Meanwhile, a forgotten Tomcat server in the corner is quietly asking, “What about me?”
This article makes a simple but important point: attackers may not need to attack your AI agents directly. They can compromise the old infrastructure those agents depend on.
AI agents do not live in magic boxes. They use existing identity systems, cloud storage, service accounts, Lambda functions, SaaS integrations and developer machines. If those supporting systems are overprivileged, misconfigured or unpatched, the AI agent inherits the problem.

The example attack path is painfully familiar. An exposed server has an old vulnerability. The attacker compromises it, steals cached credentials, abuses an Active Directory misconfiguration, reaches a developer workstation, grabs cloud access keys and then accesses the S3 bucket feeding the AI agent’s knowledge base.

No futuristic AI exploit required. Just old-fashioned security debt wearing a shiny new hat.

The lesson for UK organisations is clear: securing AI means securing what AI connects to. That includes Active Directory, IAM roles, cloud storage, developer endpoints and service accounts.
Security teams should map AI dependencies as critical assets, then work backwards to identify the paths attackers could use to reach them. If a single fix blocks several routes to sensitive AI-connected data, prioritise that fix first.

AI may be new, but attackers are still quite happy using last year’s CVE to cause this year’s incident.