AI Agent Security
Detect accidental and malicious AI agent activity — in the same converged picture as your people, systems, and facilities.
AI agents almost never arrive with an identity of their own. They act through a user’s credentials, an API token, or a service account, which means their activity lands in your logs as that identity’s activity. Tooling that watches models and prompts never sees the consequence. Orphean approaches it from the other end: it knows what each identity normally does, and it tests every action against the physical world around it. Automation that overreaches stops looking like the human it is borrowing — whether the cause is a misconfiguration or an attacker.
The Approach
You Don’t Need to Inventory Agents to Catch Them
Most approaches to AI agent security start by trying to enumerate every agent in the estate — a race that governance keeps losing, because agents are stood up faster than they are registered, and because an agent borrowing a human’s session leaves no separate identity to enumerate.
Orphean inverts the problem. Every entity it monitors already has a behavioral baseline built from 30 days of its own history, and every action is scored for convergence across physical, cyber, and operational domains. Agent-driven activity is caught not because Orphean recognizes the agent, but because the behavior no longer fits the identity performing it.
Baseline
Five behavioral dimensions — event rate, severity mix, source mix, hourly rhythm, and event type — learned over a rolling 30-day window for every entity.
Detect
Z-score thresholds and multivariate outlier detection surface deviation in tempo, scope, and reach — the three things automated activity almost always gets wrong.
Corroborate
Cross-domain patterns test the digital activity against badge, door, and camera evidence for the same entity, and score the contradiction.
Act
High-confidence convergences open an investigation case with multi-step guided recommendations, and every step is recorded for audit.
Threat Model
Accidental Harm and Malicious Intent
An agent does not need an attacker behind it to cause damage. Both halves of the problem break the same baselines — and telling them apart is exactly what explainable risk drivers are for.
Accidental: Runaway Automation
A retry loop, a bad prompt, or an unbounded task turns one agent into thousands of calls against production. The event-rate baseline for that identity breaks first, well before anyone reads a failed-job queue.
Accidental: Unintended Reach
An over-permissioned agent reads records it was never meant to touch. Source-mix and event-type baselines flag the identity operating outside anything in its history — no policy violation required.
Malicious: Hijacked Credentials
An attacker driving an agent inherits everything that identity can do, and inherits its reputation as legitimate automation. The behavior still has to match 30 days of history, and it doesn’t.
Malicious: Agents as Insiders
A trusted agent steered toward data collection produces exactly the pattern Data Exfiltration with Physical Presence and After-Hours Data Access were built to catch — scored Critical even when the underlying events arrive as informational.
In Practice
What Convergence Catches
Each of these is invisible to a tool that watches only one domain.
The Assistant That Read Too Much
An AI assistant running under an analyst’s credentials begins enumerating a database that analyst has never queried, at ten times their normal rate. The deviation is scored against their own baseline within the detection window.
The Identity in Two Places
An automation authenticates from a data center while the credential owner’s badge places them in a building three time zones away. Impossible Travel matches and floors the convergence at Critical.
The Job That Never Stopped
An integration account’s overnight sync loops without terminating, driving event volume far outside its hourly pattern. Orphean raises the anomaly against the account’s learned rhythm, not a static threshold.
Governance, Risk & Compliance
Prove Your Controls Are Operating
Automated and AI-driven access falls under account-management and access controls you are already accountable for. Orphean evidences them from live operational data rather than periodic attestation.
CIS Controls v8
Support 5.5 — Establish and Maintain an Inventory of Service Accounts — with live activity, ownership, and risk context for the accounts automation actually runs as.
ISO/IEC 27001:2022
Evidence Annex A access-management and monitoring controls from real detections and case outcomes, mapped into the same unified control library as every other framework.
NIST CSF 2.0
Demonstrate Detect and Respond outcomes for automated activity with continuously refreshed control evidence and an immutable log of every status change.
Do You Know What Your
Agents Did Today?
Schedule a personalized demo and see how Orphean surfaces AI-driven activity through the identities it runs as.