A security approach that treats people, their communications, and their data as the main attack surface. It focuses on reducing risk where users work across email, cloud apps, browsers, and collaboration tools. In practice, it combines prevention, detection, and governance around human behavior and the information people handle.
Expanded Definition
Human-centric security extends beyond classic endpoint or perimeter thinking and treats people, their messages, and the information they handle as the primary exposure layer. In NHI and IAM environments, that means focusing on email, browsers, collaboration tools, cloud apps, and the workflows where users create, approve, share, or move sensitive data. The approach overlaps with NIST Cybersecurity Framework 2.0, but the term is used more as an operating model than a formal standard.
Definitions vary across vendors, but the consistent idea is to protect the human interaction path rather than only the infrastructure behind it. That includes phishing resistance, data loss controls, identity governance, and behavioural signals that reveal risky actions before they become incidents. Human-centric security also recognises that many NHI compromises begin with a person misusing a secret, approving an OAuth grant, or forwarding sensitive material into a less-controlled environment.
The most common misapplication is treating it as employee awareness training alone, which occurs when organisations ignore the technical controls needed to protect the communication and data flows people actually use.
Examples and Use Cases
Implementing human-centric security rigorously often introduces friction for users, requiring organisations to weigh tighter control over communications and data against the convenience of fast collaboration.
- Email and collaboration filtering that detects credential theft, impersonation, and risky sharing before a user exposes secrets or approves a fraudulent request.
- Data protection policies that restrict copying API keys, certificates, or tokens into chat tools, documents, and code repositories.
- Identity-centric monitoring that flags unusual consent grants, impossible travel, or mass downloads in cloud applications.
- Just-in-time access and step-up verification for sensitive actions, especially where a human approval can trigger downstream machine access.
- Governance reviews that combine user behaviour, application access, and secret handling, as described in Ultimate Guide to NHIs and aligned operationally with NIST Cybersecurity Framework 2.0.
It is especially useful in environments where employees routinely work across SaaS platforms, browsers, and shared workspaces, because those are the places where policy gaps become security incidents.
Why It Matters in NHI Security
Human-centric security matters because many NHI incidents start with a person, even when the blast radius affects machines. A developer pasting a long-lived token into a ticket, an employee approving a suspicious OAuth grant, or an analyst sharing a report that contains embedded credentials can all create durable access paths that are hard to detect and revoke. The operational issue is not only malicious insiders; it is also ordinary workflows that move secrets faster than governance can track them.
NHI Mgmt Group research shows that 96% of organisations store secrets outside secrets managers in vulnerable locations such as code, config files, and CI/CD tools, while 79% have experienced secrets leaks and 77% of those incidents caused tangible damage, according to Ultimate Guide to NHIs. That makes the human layer inseparable from NHI control design. This is why human-centric security also belongs in broader governance discussions reflected in NIST Cybersecurity Framework 2.0.
Organisations typically encounter the consequences only after a phishing event, leaked token, or over-shared document exposes downstream systems, at which point human-centric security becomes operationally unavoidable to address.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP Agentic AI Top 10 and OWASP Non-Human Identity Top 10 address the attack and risk surface, while NIST CSF 2.0, NIST AI RMF and NIST Zero Trust (SP 800-207) set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| NIST CSF 2.0 | PR.AC-1 | Human-centric security depends on identity-aware access decisions for users and their data flows. |
| NIST AI RMF | Frames human oversight and socio-technical risk as core to AI-enabled security operations. | |
| NIST Zero Trust (SP 800-207) | 4.2 | Zero Trust relies on continuous verification of people, devices, and access context. |
| OWASP Agentic AI Top 10 | A10 | Human misuse can trigger unsafe agent actions, permissions, or tool exposure. |
| OWASP Non-Human Identity Top 10 | NHI-02 | Secret handling by people is a primary pathway into NHI compromise and exposure. |
Limit user access paths, review entitlements, and tie sensitive actions to explicit identity verification.
Related resources from NHI Mgmt Group
- What breaks when security teams rely only on human-centric threat models for AI agent activity?
- How do organisations know whether a people-centric security programme is actually reducing human risk?
- What regulatory frameworks address Non-Human Identity security?
- How should security teams govern non-human identities at scale?
