API management and identity merge for machine-to-machine security

At a glance

What this is: This is an analysis of why API management and application identity are converging, with machine-to-machine access and secret handling at the centre.

Why it matters: It matters because IAM, PAM, and NHI teams increasingly need one governance model for APIs, service identities, and automated clients rather than separate control planes.

By the numbers:

• 97% of NHIs carry excessive privileges, increasing unauthorised access and broadening the attack surface.
• Only 20% have formal processes for offboarding and revoking API keys, and even fewer have procedures for rotating them.
• 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools.

👉 Read Kong's analysis of merging API management and identity for machine-to-machine security

Context

API management and identity are converging because machine-to-machine access now carries the same governance burden that human identity has carried for years. When API keys, OAuth tokens, and application credentials are handled in separate systems, teams lose a shared view of entitlement, lifecycle, and revocation. That leaves the programme exposed to sprawl rather than control.

The article's core point is that fragmented control planes create operational friction and security blind spots, especially where static keys are embedded, shared, or manually rotated. For IAM leaders, this is not a gateway question alone. It is an identity governance problem for non-human actors, including service accounts, API clients, and automated workloads.

Key questions

Q: How should security teams govern API keys and tokens as machine identities?

A: Treat every API key, client secret, and token as an identity with an owner, scope, expiry, and revocation path. Put issuance, rotation, and offboarding into a formal lifecycle process, and keep credentials out of code, chat, and wikis. That turns machine access from hidden sprawl into something auditable and governable.

Q: Why do separate API and identity systems create security risk?

A: Separate systems create duplicate policy logic, inconsistent token handling, and weak visibility into who can still access what. When access is provisioned in one place and retired in another, keys linger and scope drifts. The result is a larger attack surface and slower incident containment when a credential is exposed.

Q: What do organisations get wrong about machine-to-machine access?

A: They often treat it as a connectivity problem instead of an identity problem. That leads to shared keys, hardcoded secrets, and ad hoc approvals that are hard to audit. Machine access needs the same governance disciplines used for privileged human access, including inventory, scoping, rotation, and retirement.

Q: How do IAM and platform teams share responsibility for API security?

A: IAM teams should own entitlement model, lifecycle policy, and review standards, while platform teams enforce those decisions in gateways and service controls. The goal is not split accountability, but one operating model for machine access that both teams can measure and enforce consistently.

Technical breakdown

Why API keys and tokens become governance debt

API keys, bearer tokens, and client credentials are identity artefacts, not just authentication mechanisms. Once they are issued, they need ownership, scoping, rotation, and revocation. When those controls sit outside the API platform, the result is governance debt: teams keep issuing credentials faster than they can inventory and retire them. Static keys hardcoded into code or shared through chat make attribution and containment harder because the credential outlives the business process that created it.

Practical implication: inventory every machine credential as an identity object with an owner, expiry, and revocation path.

How OAuth 2.0 and OIDC shift control into the gateway

OAuth 2.0 and OpenID Connect separate authentication from API consumption by allowing a gateway or authorisation server to issue and validate scoped tokens. In a mature model, the gateway becomes the policy enforcement point for machine clients, while upstream services only trust a token that already carries claims, scopes, and audience limits. That reduces duplicated logic across services, but only if token design, claim mapping, and expiry are governed centrally.

Practical implication: standardise token issuance and claim policy at the gateway so services do not implement their own access logic.

Why per-region authorization servers matter for machine identity

Per-region authorisation servers create a boundary for trust decisions, token issuance, and policy enforcement. That matters when API consumers span clouds, geographies, or business units, because identity controls need to follow the operational boundary of the workload, not just the organisation chart. Dynamic claim templates add flexibility, but they also increase the need for strict policy design, since claim values can change with context and must still remain auditable.

Practical implication: align authorisation server boundaries with workload domains and review dynamic claims as part of access governance.

NHI Mgmt Group analysis

API identity is now a governance domain, not a gateway feature. The article describes a common enterprise pattern where API management, human identity, and machine identity sit in different silos. That separation creates lifecycle gaps, inconsistent scoping, and weak revocation behaviour. The practical conclusion is that machine-to-machine access must be governed as identity, not treated as a transport concern.

Standing credential sprawl is the real failure mode behind fragmented API access. The article's ad hoc example, where keys are shared through chat or embedded in code, shows how entitlement becomes invisible once issuance leaves a central process. This is the same structural problem behind many NHI incidents: access persists without reliable ownership or rotation. Practitioners should read this as a control failure in issuance and offboarding, not merely a tooling mismatch.

Unified application identity can reduce friction, but it also concentrates trust decisions. Bringing API management and identity together simplifies enforcement, yet it makes token design, claim governance, and regional policy consistency more consequential. That shifts the burden from many inconsistent controls to one authoritative control plane. The implication is that identity teams and platform teams must share responsibility for machine access governance.

Identity sprawl in machine access mirrors human IAM drift, but at higher speed. Human IAM has long struggled when entitlement review, provisioning, and offboarding are disconnected. The article shows the same pattern in API consumption, where credentials are issued quickly and retired late or never. The practitioner takeaway is that lifecycle discipline has to be built into machine identity from the start, not retrofitted after exposure.

From our research:

• 91.6% of secrets remain valid five days after the targeted organisation is notified, showing a critical gap in remediation procedures, according to Ultimate Guide to NHIs.
• Only 5.7% of organisations have full visibility into their service accounts, according to Ultimate Guide to NHIs.
• For a broader lifecycle lens, see Ultimate Guide to NHIs , Lifecycle Processes for Managing NHIs for offboarding, rotation, and access review guidance.

What this signals

Identity sprawl is moving into the API layer, and most programmes are still not built for it. When machine credentials are issued outside a lifecycle process, the same persistence problem that plagues service accounts appears in APIs, tokens, and embedded secrets. With 97% of NHIs carrying excessive privileges, according to the Ultimate Guide to NHIs, the question is no longer whether to govern machine access, but how quickly the operating model can be unified.

This is where application identity governance becomes a useful concept: the API layer is not just enforcing connectivity, it is enforcing who or what may act on behalf of the application. Teams that already manage human IAM and NHI lifecycle together are better positioned to absorb this shift. Teams that still split gateway operations from identity policy will keep discovering exposures after the fact.

For practitioners, the next step is to tie API security metrics to identity outcomes, not just traffic outcomes. That means measuring credential age, revocation latency, and the percentage of API consumers with documented ownership, then using those signals to drive lifecycle remediation.

For practitioners

• Map machine identities to owners and expiry dates Build an inventory of every API key, client secret, and token issuer, then assign a business owner, technical owner, and enforced expiry. Treat keys in code, wikis, and chat as unmanaged identities until they are traced back to a lifecycle process.
• Centralise token issuance and scope policy Move access decisions into a single gateway or authorisation layer so scopes, claims, audiences, and revocation logic are enforced consistently. Keep upstream services from inventing their own authentication rules for machine clients.
• Eliminate static credentials from source and shared channels Scan repositories, CI/CD pipelines, and collaboration tools for embedded secrets, then replace them with managed identity flows and short-lived credentials. Use this as a control objective for both new builds and legacy integrations.
• Align machine identity governance with workload boundaries Define regional or domain-specific authorisation policies where workloads actually run, then review claim templates, scopes, and revocation procedures against those boundaries. This reduces drift between platform architecture and identity governance.

Key takeaways

• API security becomes materially stronger when machine credentials are governed as identities with owners, scopes, and expiry.
• The article's core warning is lifecycle drift: secrets and tokens persist long after the business need for them has ended.
• Practitioners should converge gateway policy, identity lifecycle, and secret hygiene into one operating model for machine access.

Key terms

• Machine Identity: A machine identity is the set of credentials and trust attributes used by a non-human actor to authenticate and access services. In practice, it includes API keys, tokens, client secrets, and certificates that require ownership, scoping, rotation, and revocation like any other identity.
• Application Identity Governance: Application identity governance is the control of how software clients obtain, use, and retire access to APIs and services. It combines lifecycle management, authorization policy, and auditability so machine access is visible, bounded, and accountable across platforms and environments.
• Token Scope: Token scope is the set of permissions encoded into an access token that limits what a client can do. Strong scope design reduces blast radius by ensuring the token is valid only for the intended API, audience, and action set, instead of granting broad or persistent access.
• Credential Lifecycle: Credential lifecycle is the full process of issuing, using, rotating, and retiring a secret or token. For machine identities, lifecycle control is essential because stale credentials often remain valid long after their operational purpose has ended, creating hidden exposure and revocation delays.

Deepen your knowledge

NHI governance, agentic AI identity, and machine identity lifecycle are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are responsible for identity security strategy or NHI governance in your organisation, it is worth exploring.

This post draws on content published by Kong: Merge API Management & Identity to Unlock Your API Platform's Potential. Read the original.