Trust graph

Expanded Definition

A trust graph is a relationship model that shows which NHIs, agents, workloads, and systems can reach one another, and what privileges are inherited along those paths. In NHI security, the value is not just inventorying identities, but exposing transitive trust, where one credential or token can move laterally into additional systems that were never intended to be directly reachable.

Definitions vary across vendors, but the core idea is consistent with identity and access governance: graph relationships make hidden access paths visible in a way flat asset lists cannot. That matters for service accounts, API keys, workload identities, and agentic tools that may inherit permissions through roles, trust policies, delegation chains, or token exchange. The NIST Cybersecurity Framework 2.0 reinforces the need to understand access pathways, while NHI Management Group’s Ultimate Guide to NHIs frames visibility and lifecycle control as foundational to reducing blast radius.

The most common misapplication is treating a trust graph as a static CMDB view, which occurs when teams record ownership and host relationships but fail to map actual credential reachability and inherited privileges.

Examples and Use Cases

Implementing a trust graph rigorously often introduces modeling and maintenance overhead, requiring organisations to weigh better attack-path visibility against the effort of continuously collecting accurate identity relationship data.

• A service account with read access to one storage bucket is shown to inherit write access to a deployment pipeline through a shared role assumption path.
• An AI agent is connected to tool APIs, which in turn can call internal systems through delegated tokens, revealing a pivot path that was not visible in the original access review.
• A CI/CD secret stored outside a vault is mapped to multiple runtime workloads, helping teams trace where one leaked credential could be reused. The Ultimate Guide to NHIs highlights why secrets visibility is central to this work.
• A cloud workload identity trusts a federation provider, and the graph reveals that a compromised upstream principal could reach several downstream environments.
• Security teams use graph analysis to test whether a planned privilege reduction actually removes a lateral movement route or merely shifts it elsewhere, aligning with the intent of the NIST Cybersecurity Framework 2.0.

Why It Matters in NHI Security

Trust graphs matter because NHI compromise rarely stays local. When service accounts, API keys, certificates, or agent credentials are overprivileged, the attacker’s first foothold often becomes a staging point for deeper access. NHI Mgmt Group notes that 97% of NHIs carry excessive privileges and 80% of identity breaches involved compromised non-human identities, which makes hidden trust paths a direct operational risk rather than a theoretical modeling concern.

A trust graph helps teams identify where revocation, rotation, token scoping, or role redesign will actually reduce exposure. It also supports zero trust and least-privilege programs by showing which access edges are justified and which are legacy artifacts of convenience. The Ultimate Guide to NHIs emphasizes that visibility gaps persist across most organisations, and graph-based analysis is one of the few practical ways to surface those gaps before they become incidents.

Organisations typically encounter the need for a trust graph only after a stolen token, abused API key, or compromised agent account reveals unexpected lateral movement, at which point the trust graph becomes operationally unavoidable to address.

Related resources from NHI Mgmt Group

• How does NHI security relate to Zero Trust Architecture?
• Why do non-human identities complicate zero trust architecture?
• Why do non-human identities increase zero trust risk?
• Why do NHIs complicate zero trust and least privilege efforts?