Runtime API security is about misuse, not just authentication

At a glance

What this is: LEVO argues that modern API risk is driven less by unauthenticated access than by authenticated misuse, where valid requests trigger unintended data exposure or actions at runtime.

Why it matters: IAM, PAM, NHI, and application security teams need runtime visibility and fine-grained authorization because endpoint-level access checks do not stop valid identities, service accounts, or AI-driven workflows from overreaching.

Context

API security is the discipline of controlling what authenticated callers can do after a request is accepted. The problem in modern systems is that boundary controls can confirm identity and still miss unsafe behaviour inside the workflow, especially when APIs connect services, workloads, and AI-driven integrations.

That gap matters because APIs increasingly act as the execution layer for business logic and machine-to-machine access. For identity programmes, the issue is not only whether a caller is real, but whether its permissions, token scope, and runtime behaviour are constrained tightly enough to prevent overreach in production.

Key questions

Q: What breaks when API authentication is correct but authorisation is weak?

A: Attackers can still read or modify data they should not reach, because identity was proven without proving entitlement. That failure usually appears as BOLA, broken function-level access, or mass assignment. Security teams should test whether an authenticated caller can move from one object, record, or action to another without additional approval.

Q: Why do valid API requests still create breach risk?

A: Valid API requests still create breach risk because authentication proves the caller is known, not that the caller is entitled to the specific object. If the application accepts an identifier or booking code as proof of access, attackers can modify that value and harvest data without tripping traditional perimeter controls.

Q: How can security teams tell whether API risk controls are actually working?

A: Look for reduced abuse volume, fewer successful automated attacks, and clearer visibility into which non-human clients are making requests and why. If the control is effective, suspicious traffic should be slowed, challenged, or blocked before it reaches core systems, while legitimate integrations continue to function normally.

Q: When should organisations prioritise API discovery over more perimeter filtering?

A: When the API landscape is changing faster than the inventory, discovery should come first because you cannot govern what you cannot see. Perimeter filtering helps only after the active and shadow surfaces are known. For organisations with many service integrations or AI-connected workflows, inventory completeness is the prerequisite for any durable control model.

Technical breakdown

Why authentication is not enough for API security

Authentication answers who or what made the request. It does not answer whether the requested action was appropriate, whether the response exposed too much data, or whether the input triggered hidden behaviour in downstream logic. In modern API stacks, that distinction matters because the same authenticated identity can be used in ways the original designers did not anticipate. Runtime API security therefore needs to pair authentication with contextual authorization, response filtering, schema enforcement, and behavioural monitoring. Without those layers, a valid request can become a misuse path even when no traditional exploit is present.

Practical implication: treat authentication as the start of control, not the control boundary.

How shadow and undocumented APIs create governance gaps

Shadow APIs are endpoints that remain reachable even though they are not consistently inventoried, maintained, or tested. They often include legacy services, internal tools, and temporary interfaces that outlive their original purpose. Because these APIs are outside the active lifecycle, they frequently lack the same policy checks, logging, and ownership as primary services. That creates a governance problem as much as a technical one: if teams cannot see an API, they cannot reliably scope access, classify data exposure, or retire dangerous paths. Inventory quality is therefore a security control, not just an operations task.

Practical implication: tie API inventory to ownership, decommissioning, and access review workflows.

Why runtime visibility is the missing control layer

Runtime visibility means observing how an API behaves in live conditions, including which identities call it, what data moves through it, and which patterns differ from normal use. Static analysis and perimeter tooling can tell you what a request looks like, but not always what it does once the system accepts it. That is why many misuse cases escape WAFs and gateways: the traffic is valid, but the behaviour is not. Effective runtime control closes the gap between intended design and actual production behaviour, which is where most modern API risk now lives, especially in service-to-service and AI-connected environments.

Practical implication: monitor production behaviour continuously so policy can follow actual usage, not assumed usage.

Threat narrative

Attacker objective: The objective is to use legitimate API access to extract data, trigger unauthorized actions, or expand access beyond the intended workflow boundary.

1. Entry occurs through a valid authenticated API request that passes boundary checks because the traffic itself appears legitimate.
2. Credential or token abuse is not required; the attacker or misused caller relies on over-broad authorization, excessive data exposure, or unsafe backend logic.
3. Impact follows when the accepted request exposes data or triggers an unintended workflow that was never meant to be reachable through that interface.

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.
• OneLogin API flaw (CVE-2025-59363): A OneLogin API flaw exposed OIDC client secrets to anyone with an API key, including vendors (CVE-2025-59363); fixed with no customer impact.

Read and download The State of NHI & AI Agent Breach Report 2026, covering 200+ breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Runtime API security is now a governance problem, not just a traffic-filtering problem. The article is right to move attention away from authentication alone because modern APIs are judged by what they allow after access is granted. That makes authorization scope, response design, and behavioural policy the real control surface. For IAM and NHI teams, the practical conclusion is that identity assurance must be matched by runtime constraint.

Shadow API inventory is a control dependency, not an optional hygiene task. Undocumented and unmanaged APIs create the same kind of trust gap that unmanaged machine identities create elsewhere in the stack: a reachable surface with unclear ownership and inconsistent policy. Shadow API visibility: the inability to see every live interface means teams cannot confidently govern exposure, access scope, or lifecycle retirement. Practitioners should treat inventory completeness as a prerequisite for any meaningful runtime policy.

Fine-grained authorization must extend below the endpoint layer. The article shows why endpoint-level allow decisions are too coarse when valid identities can still perform the wrong action. That problem is especially relevant where service accounts, workload identities, or AI-driven workflows call APIs at scale. The lesson for identity governance is clear: approval of a caller is not enough unless the downstream action and data access are separately constrained.

API misuse is becoming more important as AI-driven workflows expand the execution layer. Once APIs are used to drive automation, the risk shifts from single requests to chains of legitimate actions with compounding effects. That increases the value of runtime monitoring, schema enforcement, and data minimization because a trusted integration can still create business impact without ever looking hostile at the perimeter. Practitioners should re-evaluate where their trusted pathways now do the most damage.

Traditional security tooling still matters, but only as part of a layered model. WAFs, gateways, and authentication remain useful, yet they are structurally limited because they mostly decide whether a request may enter, not what that request may do. The governance implication is that API security must be measured by enforcement after acceptance, especially for systems that expose regulated data or machine-to-machine workflows. Teams should align controls to runtime behaviour, not boundary assumptions.

From our research library:

• Secrets management is a top five cybersecurity priority for only 33% of organisations, behind cloud security (45%), API security (42%), and endpoint security (36%), according to the 2024 State of Secrets Management Survey.
• Read next: NHI Authentication Guide

What this signals

Shadow API visibility: the next governance failure will be incomplete inventory, not simply weak perimeter filtering. As service-to-service calls and AI-connected workflows expand, practitioners will need ownership, lifecycle, and data classification to keep runtime policy attached to the real attack surface.

API security programmes should increasingly be judged by what they can observe in production, not by what they block at the edge. That means identity teams, application owners, and cloud security teams need shared visibility into request context, response content, and deprecated interfaces.

Runtime controls also change how machine identities are managed. Service accounts, workload identities, and delegated tokens can all behave safely in one workflow and unsafely in another, so the security model has to follow the action rather than assume the caller's identity is the whole risk.

For practitioners

• Map every API to an owner and data class Inventory documented, undocumented, internal, and deprecated APIs, then assign ownership and sensitivity labels so no interface sits outside governance.
• Enforce action-level authorization Apply authorization checks to the specific record, object, or workflow step being requested, not just to the endpoint or authenticated session.
• Minimise response payloads by default Remove unused fields, mask sensitive values, and prevent internal object structures from being returned simply because the caller is authenticated.
• Monitor runtime API behaviour for misuse patterns Track who calls each API, what data flows through it, and where production behaviour diverges from expected usage so policy can be tuned in context.

Key takeaways

• Most API breaches are governance failures at runtime, where valid access is allowed to do more than the business intended.
• The main evidence in this article is the gap between authentication and enforcement, especially where APIs expose more data or actions than planned.
• Teams need inventory, action-level authorization, and runtime monitoring if they want API security to survive real production workflows.

Key terms

• Runtime API security: Runtime API security is the protection of application programming interfaces while they are actively handling live traffic. It focuses on authenticating callers, authorizing each request, validating inputs, limiting abuse, and detecting anomalous behavior in real time. It also includes securing tokens, enforcing transport encryption, and monitoring API interactions for misuse or data exposure.
• Shadow API: An API endpoint that exists in production but is not fully known, reviewed, or governed by the security programme. Shadow APIs often emerge through fast delivery, copy-paste development, or overlooked internal routes, and they create untracked exposure because they sit outside inventory, policy, and ownership processes.
• Excessive Data Exposure: Excessive data exposure occurs when an API returns more information than the caller actually needs. The issue is usually a design and authorization problem rather than a coding typo, and it increases breach impact because a stolen credential can reveal far more data than intended.
• Object Level Authorization: Object level authorization controls access to individual records or resources, not just to an endpoint. It prevents users from reaching data that is technically available through a route but should remain hidden according to policy, role, or ownership. This is a key safeguard against broken access control.

Deepen your knowledge

NHI Mgmt Group covers identity security, NHI governance, and agentic AI through independent research, practitioner guides, and the NHI Foundation Level course. It is suitable for teams that need to connect API-driven access to broader identity and lifecycle control.