By Sapumal Herath · Owner & Blogger, AI Buzz · Last updated: February 7, 2026 · Difficulty: Beginner
Tool‑connected AI agents are powerful because they can do more than “chat.” They can read data, call APIs, and take actions across real systems.
That also means agent security becomes an identity problem: What identity is the agent running as? What is it allowed to do? For how long? And can you prove what happened after the fact?
This guide explains Non‑Human Identity (NHI) for AI agents in plain English and gives you practical guardrails you can apply today—without turning your rollout into a months‑long IAM project.
Note: This article is for educational purposes only. It is not legal, security, or compliance advice. If your agents touch sensitive data or can take irreversible actions, involve your security/compliance team and deploy in stages.
🎯 What “Non‑Human Identity” means (plain English)
A non‑human identity (NHI) is any identity used by software instead of a person. Examples include:
- Service accounts
- API keys and tokens
- Workload identities (microservices, containers, jobs)
- Automation bots (RPA, scripts)
- AI agents that call tools and APIs
NHIs are often more dangerous than human accounts because they:
- run 24/7,
- are easier to copy/paste and reuse,
- can be over‑privileged “for convenience,”
- and often have weaker review and lifecycle management.
⚡ Why AI agents make NHI risk worse
With a normal integration, you usually know what actions it performs.
With an agent, the system can decide which tools to call and when. That introduces new failure patterns:
- Delegation chains: the agent acts “on behalf of” a user, then calls a tool that acts “on behalf of” the agent.
- Permission drift: teams keep adding access as new tasks arrive (“just give it one more scope”).
- Prompt injection → tool misuse: untrusted content can push the agent to do unsafe things, and identity becomes the blast radius.
Rule of thumb: If an agent can take actions, treat its identity like privileged infrastructure.
🚩 The 7 most common “agent identity” mistakes
Most agent incidents trace back to a small set of identity mistakes:
- Shared tokens: one token used by multiple agents, teams, or environments.
- Long‑lived credentials: keys that rarely rotate and never expire.
- Over‑privileged scopes: “admin” tokens for convenience.
- No separation between dev/staging/prod: production tokens leaking into non‑prod.
- Weak approval gates: write actions happen without human confirmation.
- No “who approved this?” trail: actions can’t be tied to a user or ticket.
- No revocation plan: you can’t quickly disable the agent’s access during an incident.
If you fix just these, you prevent a large percentage of “rogue agent” events.
✅ The “Safe Agent Identity” blueprint (practical guardrails)
This is a simple baseline that scales from small teams to enterprise deployments.
🪪 1) Separate identities: user ≠ agent ≠ tool
- User identity: who requested the task
- Agent identity: the non‑human identity executing the workflow
- Tool identity: the downstream service enforcing its own authorization rules
Do not rely on “the agent is the user.” That collapses boundaries and makes auditing harder.
⏱️ 2) Use short‑lived, task‑scoped credentials
- Prefer tokens that expire quickly (minutes, not months).
- Scope tokens to the smallest resource set (one repo/folder/project at a time).
- Scope tokens to the smallest action set (read-only first; write requires approval).
🔒 3) Least privilege + least agency
- Read-only by default for early pilots.
- Write actions require explicit approvals and tight scopes.
- Irreversible actions (delete, merge, publish, payments) require stronger controls (two‑person approval, restricted agent roles, or no automation).
🧑⚖️ 4) Approval gates are identity controls
Approvals aren’t only “process.” They reduce blast radius by ensuring the agent cannot use its identity to perform high-impact actions silently.
🧾 5) Audit trails that answer 3 questions
- Who requested it? (user)
- What executed it? (agent identity + tool identity)
- Who approved it? (human approval record)
🧭 Quick triage: what identity model should you use?
Use this table as a starting point:
| Scenario | Recommended identity approach | Why |
|---|---|---|
| Read-only agent (search, summarize, draft) | Agent service identity with read-only scopes | Simple, low blast radius |
| Write actions (create/update tickets, PR drafts) | Agent identity + approval gate + task-scoped write token | Prevents silent writes |
| High-impact actions (send, publish, delete, merge, payments) | Human approval + step-up authorization + strict allowlists | Human is the final safety boundary |
| Multi-agent workflows | Separate identities per agent role + scoped permissions per role | Limits cascading failure impact |
✅ Copy/paste: Agent Identity & Permissions Checklist
Use this before enabling tools/connectors in production.
🪪 A) Identity design
- Agent identity defined: name/ID and owner documented
- Environment separation: dev/staging/prod identities separated
- No shared tokens: credentials are not reused across teams or environments
🔐 B) Token rules
- Short-lived tokens: tokens expire quickly
- Task-scoped tokens: scopes limited to the current task’s resources
- Rotation & revocation: we can rotate and revoke quickly
🧰 C) Tool permissions
- Read-only first: default tool permissions are read-only
- Write requires approval: human confirmation required
- Irreversible actions locked: delete/merge/publish/payment restricted
🧾 D) Auditability
- Tool calls logged: tool, parameters, timestamp, agent identity, user identity
- Approvals logged: who approved, what action, what changed
- Retention set: logs retained long enough for investigations (but not forever)
🧯 E) Incident readiness
- Kill switch: disable tools/connectors fast
- Draft-only mode: switch external outputs to draft-only during incidents
- Evidence capture: prompts, tool calls, approvals, and retrieved sources preserved
🧪 Mini-labs (fast exercises that improve agent identity safety)
Mini-lab 1: Tool permission mapping (Read / Write / Irreversible)
- List every tool the agent can call.
- Label each tool as Read, Write, or Irreversible.
- Make a rule: Read tools can run; Write tools require approval; Irreversible tools require extra controls or are disabled.
Mini-lab 2: Token scope matrix
- Create a table: tool → resource scope → action scope → token lifetime.
- Reduce scope until it matches only the minimal required task.
- Add a “step-up approval required?” column for write/irreversible actions.
Mini-lab 3: “Who did what?” drill
- Pick one recent agent action (even in a test environment).
- Answer in 2 minutes: who requested it, what executed it, who approved it.
- If you can’t, your audit trail is not ready for production.
📝 Copy/paste: Agent Identity Decision Record (simple internal form)
Agent name / ID: __________________________
Owner: __________________________
Environment: dev / staging / prod (circle one)
Tools enabled: __________________________
Default permission level: none / read-only / write with approval / write without approval (circle one)
Token lifetime: __________________________
Resource scope: __________________________
Approval gates: __________________________
Audit logs: tool calls + parameters + approvals (yes/no)
Kill switch ready: disable tools + draft-only mode (yes/no)
Next review date: __________________________
🏁 Conclusion
Agent security isn’t only prompt engineering. It’s identity engineering.
If you want to prevent privilege abuse and rogue actions, start with the basics: separate identities, short-lived task-scoped tokens, least privilege, approval gates, and strong audit trails. Then expand capability only after you prove safe behavior in monitoring and incident drills.
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