SailPoint Entro changes NHI governance for machine credentials

At a glance

What this is: This is SailPoint's analysis of machine credential governance, arguing that discovery, lineage mapping, and runtime defence are now necessary to govern API keys, tokens, and service account secrets at enterprise scale.

Why it matters: It matters because IAM and PAM teams now have to govern non-human access that powers automation and AI agents, not just human users, while proving ownership and revocation across the full credential lifecycle.

Context

Machine credentials are the access layer that lets applications, scripts, services, and AI agents act without a human present. In this article, SailPoint argues that those credentials are multiplying faster than teams can inventory them, which creates a governance gap between what exists and what security can actually see.

The practical issue is not simply secret sprawl. It is the loss of lineage, ownership, and revocation discipline across non-human identities, especially when a single secret can be embedded in code, tied to a departed employee, or reused by an automation chain. Once AI-driven workflows enter the picture, the governance problem becomes one of scale and accountability, not only discovery.

Key questions

Q: What breaks when machine credentials are discovered but not linked to business owners?

A: Discovery without ownership produces inventory, not governance. Teams can see that a secret exists, but they cannot decide who can revoke it, what depends on it, or whether it should still be active. That creates a common failure mode where exposed credentials remain usable because no one can safely remove them.

Q: Why do service accounts and API keys increase governance risk?

A: They often exist outside interactive controls such as MFA and SSO, and many are created with standing access that is never reviewed. That combination creates persistent exposure, weak accountability, and a large attack surface when secrets are copied into code, CI/CD, or cloud services.

Q: How do teams know if NHI governance is actually working?

A: Look for complete inventory coverage, clear ownership, enforced rotation, and reliable decommissioning. If new credentials appear faster than they are classified, or if stale secrets stay valid after workload changes, the programme is not governing machine identities effectively.

Q: What is the difference between secrets detection and NHI governance?

A: Secrets detection finds exposed credentials, while NHI governance tracks how those credentials are issued, reused, rotated, and retired. Detection answers whether a secret is visible. Governance answers whether the identity behind that secret is controlled throughout its lifecycle. Mature programmes need both because exposure without lifecycle control leaves the same risk open.

Technical breakdown

Why machine credential discovery is not enough

Discovery tools can identify API keys, tokens, and service account secrets, but discovery alone only proves that something exists. Governance requires correlation to the application, script, or agent using the secret, plus the human or business process that owns it. Without that lineage, teams cannot tell whether a credential is active, orphaned, reused, or linked to a stale integration. SailPoint's framing shows why visibility without attribution leaves the core control problem intact: security teams still lack the decision context needed to revoke or retain access confidently.

Practical implication: Treat discovery as an input to governance, not the governance control itself.

How lineage mapping changes non-human identity control

Lineage mapping connects a secret to the workload or operator that uses it, then traces that relationship historically. That matters because machine credentials often outlive the people and projects that created them, especially in developer environments with long-lived integrations. Historical correlation also exposes orphaned secrets, unmanaged access paths, and technical debt that standard sweeps miss. In practice, lineage is what turns a flat inventory into an identity graph, which is the difference between knowing a credential exists and knowing whether it should still exist.

Practical implication: Build lineage into NHI governance so revocation decisions can be tied to ownership and lifecycle state.

What runtime defence adds to secrets governance

Runtime defence extends controls beyond static inventory by watching token behaviour and intercepting malicious AI tool calls in real time. That changes the governance model from one-time discovery to continuous enforcement around actual use. In this article, SailPoint also points to risk ranking and guided remediation, which suggests a control stack where the most dangerous credentials get priority, and routine cases can be remediated faster. For teams, the architectural lesson is clear: secret management, identity governance, and runtime monitoring now need to work as one control plane.

Practical implication: Pair credential inventory with behaviour monitoring so misuse can be contained while governance catches up.

Threat narrative

Attacker objective: The objective is to exploit untracked machine credentials to reach sensitive systems through a quiet, durable access path.

1. Entry occurs when API keys, tokens, or service account secrets are embedded in code, automation, or agent workflows and remain invisible to standard security sweeps.
2. Escalation happens when those long-lived credentials persist after the original owner, application, or process changes, creating an orphaned access path that still works.
3. Impact follows when attackers or rogue automations use the exposed secret to reach sensitive systems, while defenders lack enough lineage to prove ownership or revoke cleanly.

Breaches seen in the wild

• Dropbox Sign breach 2024: A compromised back-end service account gave attackers Dropbox Sign customer data, including API keys, OAuth tokens and MFA information.
• Hugging Face Spaces breach 2024: Unauthorised access to Hugging Face Spaces may have exposed secrets users stored for AI apps; tokens were revoked and org tokens removed.

Read our 52 NHI Breaches Analysis report for a comprehensive view of breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Machine credentials create an identity governance problem, not just a secrets problem: Once API keys, tokens, and service account secrets power applications and AI agents, the control question shifts from whether a secret exists to whether its owner, lineage, and lifecycle are still defensible. Standard inventory and perimeter-style sweeps do not answer that question. The practitioner implication is that NHI governance has to operate as identity governance, not as a narrow secrets hygiene exercise.

Lineage mapping is the missing governance primitive for machine identities: A credential without a current relationship to a workload, script, or business process is not governable in any meaningful way. SailPoint's emphasis on tracing secrets back to people and processes reflects a broader reality across OWASP-NHI and NIST-CSF: attribution is what makes revocation, recertification, and audit evidence possible. Teams that cannot trace usage are managing artifacts, not identities.

Customer Zero validation matters because NHI controls fail quietly when they are only tested in theory: Machine credential governance must survive real developer repositories, real integrations, and real operational friction. That is why proving discovery and remediation internally is more useful than abstract feature claims. Practitioners should judge NHI programmes by whether they hold up inside the environments where secrets actually accumulate.

Runtime defence changes the control boundary for AI-era identity risk: When AI agents can trigger tool calls and consume credentials at runtime, the governance assumption that access can be reviewed after the fact becomes weaker. The implication is not just more monitoring, but a shift toward continuous enforcement around use, scope, and behavioural anomaly. In other words, the identity programme must govern both the secret and the session in which it is consumed.

Unified identity graphs will become the practical centre of gravity for audit and compliance: Fragmented vault reports are no longer enough when auditors and insurers want end-to-end lineage for human and non-human access. This is where identity governance, PAM, and NHI operations converge into one evidentiary model. Practitioners should expect audit readiness to depend increasingly on whether they can present a coherent identity graph rather than disconnected secret lists.

From our research library:

• Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them, according to the Ultimate Guide to NHIs.
• 69% of organisations still authenticate machine identities with long-lived API keys, according to the 2026 State of AI Agent Identity Security Report.
• Read next: Guide to NHI Rotation Challenges

What this signals

Credential lineage will become the decisive control for machine identities: Organisations that can only enumerate secrets will keep finding themselves behind the problem, because the real question is whether each credential can be traced to a current workload and owner. That is the shift from secret inventory to governed identity state, and it is now central to NHI programmes.

Machine credential governance is converging with AI runtime control: As agents consume credentials dynamically, access review cycles alone stop being enough, because the use of the secret may occur faster than a traditional certification loop can act. Teams should expect governance evidence to move closer to issuance and runtime monitoring, not just periodic review.

For practitioners

• Map credential-to-owner lineage Link each API key, token, and service account secret to the workload, script, or agent that uses it, then tie that back to a named owner or process.
• Inventory orphaned machine credentials Prioritise secrets that no longer map cleanly to an active application, repository, or business process because those are the most likely to survive past their useful life.
• Add risk ranking to remediation queues Separate routine secrets from high-risk credentials so the team can revoke, rotate, or escalate the most exposed items first without drowning in manual work.
• Monitor runtime token behaviour Watch for unusual token use, unexpected tool calls, and secrets consumed outside their normal workload context so misuse can be interrupted before broader access follows.

Key takeaways

• Machine credentials now create an identity governance problem because ownership, lineage, and lifecycle state determine whether a secret is still defensible.
• The article points to a practical blind spot: standard sweeps can find secrets, but they cannot by themselves prove which workload, person, or process still deserves them.
• Security teams need lineage-aware governance, risk-based remediation, and runtime monitoring if they want machine identity controls to hold up under AI-scale automation.

Key terms

• Machine Credential Lineage: The traceable relationship between a secret and the workload, script, service, or agent that uses it. In NHI governance, lineage is the evidence that a credential still has a legitimate purpose and owner, which makes revocation, recertification, and audit defensible.
• Identity Graph: An identity graph is a relationship map that connects identities, assets, data, and permissions so teams can see how access actually flows. In NHI programmes, it helps explain which agent is related to which owner, which system, and which policy boundary.
• Runtime Defense: Runtime defense is the set of controls that inspect, constrain, and stop unsafe AI behavior while the system is operating. For hospitality deployments, it covers both incoming prompts and outgoing responses, plus the tool calls that agents may trigger after a model decides to act.
• Orphaned Credential: A secret, token, or service account password that remains active and valid after the NHI it was issued to has been decommissioned, or after the person or system responsible for it has left the organisation.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity security are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building or maturing an IAM programme, it is worth exploring.