Your network is no longer the boundary. Identity is. In most real incidents, the attacker does not hack in so much as they log in. That is why security leaders are rethinking human identities and machine identities as the core control plane for modern defense.
This post breaks down what makes human identities different from machine identities, where each has different risks in practice, and how SOC and IT teams can turn identity sprawl into measurable risk reduction.
Why human identities and machine identities are now the primary attack surface
Most security programs were built around endpoints, networks, and apps. But cloud and SaaS moved value to APIs and session tokens, while DevOps and automation multiplied non-human access. The result is a two-headed identity problem:
- Human identities: employees, admins, contractors, partners, and sometimes customers, authenticated through an IdP and often federated through SSO.
- Machine identities: service accounts, workloads, bots, scripts, CI/CD runners, and applications authenticating via API keys, OAuth clients, certificates, or workload identity frameworks.
Adversaries love identities because they scale. A compromised credential can unlock multiple apps, and valid accounts blend into normal activity.
The shift also aligns with zero trust guidance, where identity is a foundational pillar, and access decisions must be continuously evaluated, not assumed.
What human identities include
When leaders say identity, they usually mean the directory and the IdP. In reality, human identities span multiple systems and states across the entire lifecycle, from joiner to leaver.
NIST’s digital identity guidance is useful because it forces clarity around assurance, authentication strength, and lifecycle expectations.
Where human identities fail in practice
Human identities tend to break at the seams between systems. Over time, organizations accumulate privilege drift, MFA exceptions, and inconsistent entitlement models across SaaS apps federated through SSO. The SOC then inherits the complexity during investigations, when it becomes hard to confirm whether access was legitimate or simply allowed.
In many environments, session risk is under-monitored. That matters because session theft and token replay can bypass otherwise strong authentication controls, especially when policies do not enforce step-up checks for sensitive actions.
What machine identities include, and why they are harder to manage
If human identities are messy, machine identities are exponential.
A single application may use a cloud IAM role, a Kubernetes service account, an OAuth client, and one or more secrets for external dependencies. Many of these identities are created by infrastructure code and CI/CD pipelines, which means they can appear and change faster than governance processes can follow.
Workload identity frameworks like SPIFFE emphasize cryptographic identity for services and short-lived credentials, which directly addresses the brittleness of static secrets.
Where machine identities fail in practice
Machine identities often fail due to ownership ambiguity and lifecycle gaps. Service accounts and app registrations may outlive the applications they were meant to serve. Permissions that were granted temporarily become permanent. Secrets are copied into multiple places, then never rotated because no one is sure what will break.
Cloud identity guidance from defense and government sources consistently highlights non-person entity authentication and certificate hygiene because mismanaged non-human access can create systemic risk.
The control differences that matter
Security teams often apply the same playbook to both, and that is where programs stall. Human identities need strong authentication, session risk management, and role governance. Machine identities need cryptographic attestation, short-lived credentials, and rigorous secret hygiene.
Here is a practical comparison:
The takeaway is to treat human identities and machine identities as related, but not interchangeable. Your tooling, telemetry, and governance should reflect the difference.
Identity telemetry the SOC should insist on
SOC teams cannot defend what they cannot see. For both human identities and machine identities, you want enough telemetry to answer four investigation questions quickly: who or what authenticated, what they accessed, what changed, and whether it was expected.
This expectation maps cleanly to zero trust guidance, where identity signals and continuous evaluation are foundational.
Detection engineering ideas tied to real attacker behavior
If you want a single technique to rally around, start with valid accounts. Attackers routinely abuse legitimate credentials for initial access, persistence, and privilege escalation.
Below is a compact set of detection ideas that connect human identities and machine identities to observable signals, without turning your SOC into a rules factory.
Checklist for operationalizing identity detections
- Baseline normal sign-in patterns for human identities by role and geography, then alert on high-confidence anomalies (new device plus new location plus sensitive app access).
- Alert on changes to privileged access paths, such as new admin role assignments, new OAuth app permissions, and group changes that grant broad access.
- Detect impossible workflow sequences for machine identities, such as token use from an unexpected runtime, or API calls that do not match the service’s normal call graph.
- Flag long-lived credentials in use, such as API keys and tokens that have not rotated within policy windows, especially when used against high-value APIs.
- Correlate identity events to impact signals, like privilege changes followed by data access spikes, mailbox rules, unusual exports, or infrastructure modifications.
That checklist is intentionally short. It is easier to run well, tune, and improve than a sprawling set of fragile detections.
Designing controls that reduce risk without slowing the business
Identity programs fail when they are purely restrictive. The goal is to reduce blast radius and shorten time-to-confidence.
For human identities: Raise assurance, reduce standing privilege
Phishing-resistant MFA, conditional access, and session controls are table stakes. The bigger win is minimizing standing privilege so that compromised human identities cannot immediately do damage. Consider just-in-time access and just-enough administration patterns for high-impact roles.
For machine identities: Eliminate static secrets where possible
For machine identities, the north star is reducing or eliminating long-lived secrets. Use short-lived tokens and workload-bound identities, and ensure secrets that must exist are stored in managed systems with rotation and auditability.
Workload identity frameworks, including SPIFFE, are built around strongly attested identities for services, which is a direct antidote to “API key in a config file” syndrome.
Pragmatic guardrails that work in most organizations
- Standardize on a small number of approved patterns for machine authentication (for example, workload identity for runtime, secret manager for exceptions).
- Require explicit ownership metadata for machine identities (service name, team, environment, expiry).
- Enforce rotation SLAs for any static credentials that remain, and alert on violations.
- Gate sensitive actions behind stronger signals for human identities, including step-up authentication and device posture.
- Treat identity changes as high-signal events for SOC correlation, not just admin noise.
That is enough to create momentum without triggering a months-long platform rewrite.
Treat identity as the perimeter, and manage both sides of it
The organizations that materially reduce breach likelihood systematically shrink the attack surface created by human identities and machine identities, then instrument the remaining paths so the SOC can rapidly confirm intent.
Start by separating the control strategy, with stronger authentication and minimized standing privilege for human identities, and short-lived, workload-bound credentials plus rotation discipline for machine identities. Anchor detections to attacker behavior like valid accounts, and insist on identity telemetry that supports fast investigation.
If you are pressure-testing how quickly your team can investigate identity-driven incidents across SaaS, cloud, and workloads, consider a structured evaluation of an agentic SOC approach.
