Govern the Identities That Are Not People
Service accounts, tokens, and agents do most of the acting and carry elevated scope, yet rarely have a face behind them. Govern them by resolving each into one canonical identity with a confidence, a band, and an owner.
Why this is hard
Human identity has decades of tooling; non-human identity has almost none, even though machine actors now outnumber people and carry real privilege. The risk is an agent or token acting with no accountable owner and no resolved identity, which is both a shadow-AI problem and an access-control gap. Governing them starts with resolving who - or what - is acting.
- Machine actors outnumber people and carry elevated scope
- An agent without a linked human owner has no accountability anchor
- Unresolved actors are invisible to normal access controls
- Low identity confidence should change how much an actor is trusted
The approach, step by step
From anonymous machine actors to governed identities
- 1
Resolve the actor
Fold the available evidence about each non-human actor into a canonical identity with a confidence in [0,1] and a band.
- 2
Require an owner
Link each agent and service account to a human owner; flag agent_without_owner and lower its confidence when none exists.
- 3
Surface anomalies
Raise anomalies like unknown_agent and unresolved_actor so ungoverned machine identities are visible.
- 4
Gate on confidence
Let a low confidence band hold consequential actions from that identity for step-up or review.
- 5
Record the decisions
Write each identity-anomaly decision to the ledger so a low-confidence action becomes access-control evidence.
How SentriAI does the work
SentriAI resolves non-human actors deterministically: an agent in the roster or linked to a human owner earns confidence, while one acting without an owner or outside the roster is flagged and trusted less. That confidence flows into the Action Trust Score, so ungoverned machine identities are both surfaced and gated.
What you get out of the box
- A canonical identity and confidence for every machine actor
- Ownership required as the accountability anchor
- Anomalies that surface shadow and ungoverned identities
- Low-confidence actions held and recorded as evidence
Avoid the common pitfall
Frequently asked questions
How do I govern non-human identities?
Resolve each machine actor into a canonical identity with a confidence and a band, require a human owner as the accountability anchor, surface anomalies that expose ungoverned identities, and gate consequential actions from low-confidence identities for step-up or review.
Why does an agent need a human owner?
Ownership is accountability. An agent linked to a human owner earns higher confidence; one acting without an owner is flagged agent_without_owner and trusted less, because there is no one answerable for what it does.
How does this relate to shadow AI?
The anomalies identity resolution raises - agent_without_owner, unknown_agent, unresolved_actor - are the fingerprints of shadow AI, so governing non-human identity is how ungoverned agents surface.
What happens to a low-confidence machine identity?
Its low confidence lowers the trust on its actions, so consequential ones hold for step-up or human review, and the identity-anomaly decision is recorded as access-control evidence.
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