The model can request an action. The authorization system decides.
Prompt injection is not a bug you patch in the prompt. It is the reason agent actions must be authorized outside the model.
Read moreResources
The knowledge center for machine authority
Research, practical guides, perspectives and dated product updates on non-human identity security, AI agent security and explainable risk — evidence before claims.
Latest
Read the reasoning, not just the claims
10 pieces so far: 2 research, 3 guides, 2 blog posts, 2 product updates and 1 architecture deep-dive. Each one names what is available today and what is still direction.
Browse researchClassification, ownership and lifecycle, as built
How Trustivan types each identity, records who owns it and on whose word, and tracks where it is in its life — with evidence behind every value and unknown shown as unknown.
Read moreThe connector contract and identity graph search
How identities enter Trustivan — one read-only connector contract with a sync lifecycle and evidence on every record — and a graph you can walk for reach, paths and blast radius.
Read moreShadow AI is an identity problem
Blocking AI tools does not stop shadow AI. Agents show up in the identity layer as new principals, OAuth grants and tool bindings — which is exactly where you can govern them.
Read moreThe 30-day plan to inventory and own every NHI
Four weeks, four outcomes: a complete inventory, a classification, an accountable owner for every production identity and an evidence trail — without boiling the ocean.
Read moreWhy non-human identity risk has to be explainable
A conceptual framework for scoring machine-identity risk that a human can audit — and why a score without evidence is worse than no score.
Read moreInside the identity graph: every edge is evidence
How Trustivan models owners, identities, credentials, services, resources and actions as a graph, why every edge carries evidence, and what that design makes possible.
Read moreOwnership is the control
Most non-human identity programs stall on one question. Ownership is not a field to fill in after the real work — it is the control every other control depends on.
Read moreIdentity ≠ Credential: the model behind NHI security
Why treating a secret as if it were an identity leads to the wrong inventory, the wrong owner and the wrong fix — and the relationship model that works.
Read moreMapping the OWASP Non-Human Identities Top 10 to controls you can evidence
A practical walk through the ten NHI risk categories, the question each one asks, and the evidence a control plane should be able to show for it.
Read moreTopics
Primers, frameworks and reference
Start with the fundamentals of non-human identity and AI agent security, map the OWASP lists to controls you can evidence, and look up any term in the glossary.
NHI Security 101
Definitions, a working taxonomy, the relationship model and the ten risks that matter most for machine identities
AI Agent Security 101
Why agents differ from service accounts, the threat vocabulary and the authorization principle
OWASP NHI Top 10
Each OWASP category mapped to a question, the evidence to collect and a control you can show
OWASP Agentic Threats
Agentic AI threat categories from OWASP, mapped to identity-centric controls
Glossary
Forty-plus terms from access path to workload identity, defined plainly and cross-linked
Security Architecture
How the Trustivan platform is built, isolated, audited and kept honest
Product Updates
What is built, what is a future capability and what is not built by design
Full visibility. Explainable risk. Controlled action.
See how Trustivan maps your non-human and agentic identities to the credentials, access paths and actions that matter.