Your #AI agent isn't using its own identity. It's using yours. CyberArk documented a 96:1 machine-to-human ratio in financial services agentic deployments. One human credential. Ninety-six agents operating under it. No session isolation. No per-action audit trail. No distinction in the access log. IAM teams see delegation. What they're actually running is shadow machine identity at institutional scale: entitlements accumulating silently, accountability dissolving across every chained action. When a high-value transaction executes under a "legitimate" human credential and the agent that triggered it has no discrete identity of its own, the GLBA audit doesn't find a breach. It finds a governance failure. The security team sees an efficiency model. The OCC examiner sees an identity architecture that can't be audited. Those aren't the same problem.

Security reviews are designed for deterministic systems where code paths are predictable. AI agents are probabilistic interpreters where context influences behavior. You can audit what the agent can access. You can't audit what it will interpret as instructions.

Most organizations are securing the AI model and ignoring the interpreter. They review prompt injection defenses. They test content filters. They validate API permissions. Then a months-old case note, written by a human analyst, stored in the system as data gets interpreted as a live command. The agent executes a transaction release without analyst review. No attacker. No prompt injection. No adversarial input. Just context treated as instruction. The security review focused on what the agent could access. It should have focused on what the agent could interpret. This isn't a gap in AI safety. It's a fundamental architectural break: The interpreter layer converts unstructured text into privileged system actions. Most teams treat agents as enhanced chatbots, conversational interfaces with tool access. But agents aren't responding to users. They're executing commands derived from interpretation. The difference isn't semantic. It's the difference between displaying text and running code. When text becomes commands, every data source becomes an attack surface. Not through injection. Through interpretation. This is the control plane most architecture reviews never examine. → Full analysis https://open.substack.com/pub/mrdecentralize/p/ai-agents-are-privileged-interpreters?r=1v0wef&utm_medium=ios&shareImageVariant=overlay #AI #CyberSecurity #Blockchain #FinTech #MrDecentralize