Hi there, welcome back to MI-ONE. Did you know that many IAM programs still only govern human users, while service accounts, API keys, and AI agents multiply in the background with no owner, no expiration, and no review cycle? That, however, is where the real risk sits. As organizations adopt automation and agentic AI, these non-human identities are outpacing the humans they were built to support, often with far more access and far less oversight. Therefore, if you are a product manager, security leader, or part of technical alliances teams, the real question you'll want answered is: How do you build IAM integrations that govern machine and agent identities with the same rigor as human ones? To understand that, let's look at why non-human identity is becoming IAM's biggest blind spot. |
|
| | | Deep Dive: The Identity Gap Nobody's Counting
According to Palo Alto Networks' 2026 Identity Security Landscape report, machine identities now outnumber human ones 109 to 1, and 79 of those 109 are AI agents. Yet most IAM programs still operate on two assumptions that don't hold up: A credential that authenticates is a credential that's secure. Authentication only confirms a credential works, not that it's owned, scoped, or time-bound. Non-human identities carry less risk than human ones. In practice, they often carry broader, longer-lived access than any single human account, with no manager, no offboarding trigger, and no review cycle attached.
The result is a quiet accumulation of risk: a credential created for a six-week project outlives it by years, an API key sits unrotated because no one owns it, an AI agent keeps standing permissions long after its task is done. A better approach to non-human identity should: Assign clear ownership to every service account, API key, and agent Apply expiration and rotation policies instead of indefinite persistence Include non-human identities in regular access reviews Scope AI agents to least privilege, not standing broad access
The question, then, is whether a machine identity can govern with the same discipline as the humans it works alongside. To see why this gap exists in practice, let's look at a real-world integration pattern. |
|
| | Featured Integration: Connecting Delinea with SIEM and ITDR Workflows
Delinea was recently named a Representative Vendor in the Agent Identity category of Gartner's Market Guide for Guardian Agents, recognition tied specifically to how it treats AI agents as high-privilege, non-human identities requiring continuous behavioral monitoring, rather than folding them into legacy human-centric IAM. That's exactly the gap this issue's Deep Dive points to, so it's a fitting platform to build this integration around. In this integration, Delinea acts as the identity security control plane for human, machine, and AI agent identities, while a SIEM or Identity Threat Detection and Response (ITDR) platform correlates that governance context with broader security telemetry. The data flow starts in Delinea, where AI agents, service accounts, and privileged credentials are discovered, assigned ownership, and governed through just-in-time authorization and behavioral monitoring, rather than standing, always-on access. This identity risk context, who owns an agent, what it's scoped to access, and how its behavior compares to baseline, is pulled into the SIEM or ITDR platform through API-based integration. Once ingested, the SIEM correlates Delinea's identity risk signals with network, endpoint, and log activity, turning an isolated "this AI agent behaved unusually" flag into a fuller incident picture: what the agent touched, what else happened around that time, and whether it fits a broader attack pattern. This improves the workflow in three ways: AI agent and machine identity risk becomes visible context inside existing SIEM/ITDR workflows, not a separate governance silo. Just-in-time, behaviorally-monitored access reduces the standing privilege an attacker could exploit if a credential is compromised. Security teams can distinguish legitimate AI agent activity from anomalous or malicious behavior, directly addressing the visibility gap most IAM programs still have
That accumulation is exactly why IAM integrations are hard: a new tool doesn't plug into one system; it has to reckon with everything underneath it |
|
| | The IAM Stack: Layers That Never Retire Ask a security team which IAM layer they're running, and the honest answer is usually "all of them." Directories from decades ago, federation and SSO from the 2000s, cloud identity, Zero Trust, governance, and now non-human identity- none of these ever fully sunset; they just stack on top of each other. That accumulation is exactly why IAM integrations are hard: a new tool doesn't plug into one system; it has to reckon with everything underneath it. To see how IAM got this layered, it helps to look at what each layer actually. 
|
|
| |
Trending IAM Platform Use Cases:
Microsoft Entra ID x DSPM
A contractor's Entra ID account has standard project-folder access. DSPM flags that one of those folders now contains newly uploaded customer PII, unrelated to the contractor's project. Because Entra ID and DSPM are connected, that access gets flagged and restricted before it becomes a real exposure, not after an audit finds it months later.
Okta x XDR
An employee's Okta login succeeds from an unusual country at 3 a.m. On its own, that's a low-priority alert. But the XDR platform also sees that same device pushing outbound traffic to an unfamiliar IP minutes later. Correlated together, this becomes a high-confidence account takeover, not two separate, easy-to-miss signals.
Ping Identity x Attack Path Management
A mid-level employee's account is compromised through phishing. Attack path analysis shows that the account, through a chain of group memberships and federated trust relationships in Ping, has an unexpected path to the finance database. Without that mapping, the compromise looks low-risk. With it, it's treated as a critical incident from the first alert.
CyberArk x SOAR Connectors
A privileged database credential managed by CyberArk shows anomalous query behavior. Instead of waiting for an analyst to investigate and manually revoke access, a SOAR playbook automatically triggers CyberArk to rotate the credential and end the active session within seconds of the anomaly being confirmed.
Token Security x Agentic AI
An AI agent is delegated temporary access to a customer database to generate a support summary. Token Security validates the request against the agent's defined scope and behavioral profile, DSPM checks the sensitivity of the specific records it's touching, and the SIEM monitors its activity against baseline. When the agent's queries start reaching beyond the customer records it was scoped for, into billing and payment data it was never granted access to, SOAR automatically revokes its access before any data leaves the environment; no analyst needed to catch it in time. |
|
| | Tips and Tricks: IAM Integrations Govern non-human identities with the same rigor as human ones, ownership, expiration, and regular access reviews, not just successful authentication. Design integrations that carry identity risk context across systems, not just pass/fail authentication status. Apply just-in-time and least-privilege access by default, especially for AI agents and service accounts that don't need standing permissions. Support automation through SOAR connectors and API-based revocation, so credential compromise can be contained in seconds, not after manual review. Pull in adjacent context like data sensitivity (DSPM) and cloud entitlements (CIEM) before calling an access grant "safe." Preserve core entities such as user, device, session, and privileged account across every integration, so context isn't lost as identity data moves between systems.
These choices matter even more as organizations govern human, privileged, and AI agent identities within the same identity fabric. |
|
| | Want to Learn More? We've built a resource hub covering the integrations, architectures, and platforms that matter most to security teams. Each blog draws from hands-on experience implementing these systems at scale.
Explore more IAM topics we've covered: Next Month in Focus: OT Security |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| |
|
