elasticsearch-authz▌
elastic/agent-skills · updated Apr 8, 2026
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Manage Elasticsearch role-based access control: native users, roles, role assignment, and role mappings for external
- ›realms.
Elasticsearch Authorization
Manage Elasticsearch role-based access control: native users, roles, role assignment, and role mappings for external realms.
For authentication methods and API key management, see the elasticsearch-authn skill.
For detailed API endpoints, see references/api-reference.md.
Deployment note: Feature availability differs between self-managed, ECH, and Serverless. See Deployment Compatibility for details.
Jobs to Be Done
- Create a native user with a specific set of privileges
- Define a custom role with least-privilege index and cluster access
- Assign one or more roles to an existing user
- Create a role with Kibana feature or space privileges
- Configure a role mapping for external realm users (SAML, LDAP, PKI)
- Derive role assignments dynamically from user attributes (Mustache templates)
- Restrict document visibility per user or department (document-level security)
- Hide sensitive fields like PII from certain roles (field-level security)
- Implement attribute-based access control (ABAC) using templated role queries
- Translate a natural-language access request into user, role, and role mapping tasks
Prerequisites
| Item | Description |
|---|---|
| Elasticsearch URL | Cluster endpoint (e.g. https://localhost:9200 or a Cloud deployment URL) |
| Kibana URL | Required only when setting Kibana feature/space privileges |
| Authentication | Valid credentials (see the elasticsearch-authn skill) |
| Cluster privileges | manage_security is required for user and role management operations |
Prompt the user for any missing values.
Decomposing Access Requests
When the user describes access in natural language (e.g. "create a user that has read-only access to logs-*"), break
the request into discrete tasks before executing. Follow this workflow:
Step 1 — Identify the components
Extract from the prompt:
| Component | Question to answer |
|---|---|
| Who | New native user, existing user, or external realm user (LDAP, SAML, etc.) |
| What | Which indices, data streams, or Kibana features |
| Access level | Read, write, manage, or a specific set of privileges |
| Scope | All documents/fields, or restricted by region, department, sensitivity? |
| Kibana? | Does the request mention any Kibana feature (dashboards, Discover, etc.) |
| Deployment? | Self-managed, ECH, or Serverless? Serverless has a different user model. |
Step 2 — Check for existing roles
Before creating a new role, check if an existing role already grants the required access:
curl "${ELASTICSEARCH_URL}/_security/role" <auth_flags>
If a matching role exists, skip role creation and reuse it.
Step 3 — Create the role (if needed)
Derive a role name and display name from the request. Use the Elasticsearch API for pure index/cluster roles. Use the Kibana API if Kibana features are involved (see Choosing the right API).
Step 4 — Create or update the user
| Scenario | Action |
|---|---|
| New native user | Create the user with the role and a strong generated password. (Self-managed / ECH only.) |
| Existing native user | Fetch current roles, append the new role, update the user with the full array. (Self-managed / ECH only.) |
| External realm user | Create a role mapping that matches the user's realm attributes to the role. (Self-managed / ECH only.) |
| Serverless user | Use the cloud-access-management skill. Assign a predefined role or create a custom role first, then assign it via the Cloud API. |
Example decomposition
Prompt: "Create a user analyst with read-only access to logs-* and metrics-* and view dashboards in Kibana."
- Identify: new user
analyst, indiceslogs-*/metrics-*, dashboards, read access. - Check roles:
GET /_security/role— no match. - Create role via Kibana API (dashboards involved):
logs-metrics-dashboard-viewer. - Create user:
POST /_security/user/analystwithroles: ["logs-metrics-dashboard-viewer"].
Confirm each step with the user if the request is ambiguous.
Manage Native Users
Native user management applies to self-managed and ECH deployments. On Serverless, users are managed at the organization level — skip this section.
Create a user
curl -X POST "${ELASTICSEARCH_URL}/_security/user/${USERNAME}" \
<auth_flags> \
-H "Content-Type: application/json" \
-d '{
"password": "'"${PASSWORD}"'",
"roles": ["'"${ROLE_NAME}"'"],
"full_name": "'"${FULL_NAME}"'",
"email": "'"${EMAIL}"'",
"enabled": true
}'
Update a user
Use PUT /_security/user/${USERNAME} with the fields to change. Omit password to keep the existing one.
Other user operations
curl -X POST "${ELASTICSEARCH_URL}/_security/user/${USERNAME}/_password" \
<auth_flags> -H "Content-Type: application/json" \
-d '{"password": "'"${NEW_PASSWORD}"'"}'
curl -X PUT "${ELASTICSEARCH_URL}/_security/user/${USERNAME}/_disable" <auth_flags>
curl -X PUT "${ELASTICSEARCH_URL}/_security/user/${USERNAME}/_enable" <auth_flags>
curl "${ELASTICSEARCH_URL}/_security/user/${USERNAME}" <auth_flags>
curl -X DELETE "${ELASTICSEARCH_URL}/_security/user/${USERNAME}" <auth_flags>
Manage Roles
Choosing the right API
Use the Elasticsearch API (PUT /_security/role/{name}) when the role only needs cluster and indices
privileges. This is the default — no Kibana endpoint is required.
Use the Kibana role API (PUT /api/security/role/{name}) when the role includes any Kibana feature or space
privileges. The Elasticsearch API cannot set Kibana feature grants, space scoping, or base privileges, so if the user
mentions Kibana features like Discover, Dashboards, Maps, Visualize, Canvas, or any other Kibana application, the Kibana
API is required.
If the Kibana endpoint is not available or API key authentication to Kibana fails, fall back to the Elasticsearch API
for the cluster and indices portion and warn the user that Kibana privileges could not be set. Prompt for a Kibana
URL or alternative credentials before giving up.
Create or update a role (Elasticsearch API)
Default choice when the role has only index and cluster privileges:
curl -X PUT "${ELASTICSEARCH_URL}/_security/role/${ROLE_NAME}" \
<auth_flags> \
-H "Content-Type: application/json" \
-d '{
"description": "'"${ROLE_DISPLAY_NAME}"'",
"cluster": [],
"indices": [
{
"names": ["'"${INDEX_PATTERN}"'"],
"privileges": ["read", "view_index_metadata"]
}
]
}'
Create or update a role (Kibana API)
Required when the role includes Kibana feature or space privileges:
curl -X PUT "${KIBANA_URL}/api/security/role/${ROLE_NAME}" \
<auth_flags> \
-H "kbn-xsrf: true" \
-H "Content-Type: application/json" \
-d '{
"description": "'"${ROLE_DISPLAY_NAME}"'",
"elasticsearch": {
"cluster": [],
"indices": [
{
"names": ["'"${INDEX_PATTERN}"'"],
"privileges": ["read", "view_index_metadata"]
}
]
},
"kibana": [
{
"base": [],
"feature": {
"discover": ["read"],
"dashboard": ["read"]
},
"spaces": ["*"]
}
]
}'
Get, list, and delete roles
curl "${ELASTICSEARCH_URL}/_security/role/${ROLE_NAME}" <auth_flags>
curl "${ELASTICSEARCH_URL}/_security/role" <auth_flags>
curl -X DELETE "${ELASTICSEARCH_URL}/_security/role/${ROLE_NAME}" <auth_flags>
Document-Level and Field-Level Security
Roles can restrict access at the document and field level within an index, going beyond index-level privileges.
Field-level security (FLS)
Restrict which fields a role can see. Use grant to whitelist or except to blacklist fields:
curl -X PUT "${ELASTICSEARCH_URL}/_security/role/pii-redacted-reader" \
<auth_flags> \
-H "Content-Type: application/json" \
-d '{
"description": "PII Redacted Reader",
"indices": [
{
"names": ["customers-*"],
"privileges": ["read"],
"field_security": {
"grant": ["*"],
"except": ["ssn", "credit_card", "date_of_birth"]
}
}
]
}'
Users with this role see all fields except the PII fields. FLS is enforced on search, get, and aggregation results.
Document-level security (DLS)
Restrict which documents a role can see by attaching a query filter:
curl -X PUT "${ELASTICSEARCH_URL}/_security/role/emea-logs-reader" \
<auth_flags> \
-H "Content-Type: application/json" \
-d '{
"description": "EMEA Logs Reader",
"indices": [
{
"names": ["logs-*"],
"privileges": ["read"],
"query": "{\"term\": {\"region\": \"emea\"}}"
}
]
How to use elasticsearch-authz on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add elasticsearch-authz
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches elasticsearch-authz from GitHub repository elastic/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate elasticsearch-authz. Access the skill through slash commands (e.g., /elasticsearch-authz) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★51 reviews- ★★★★★Hana Iyer· Dec 24, 2024
elasticsearch-authz reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Diya Flores· Dec 16, 2024
Useful defaults in elasticsearch-authz — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Kiara Li· Dec 12, 2024
I recommend elasticsearch-authz for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Dhruvi Jain· Dec 8, 2024
Registry listing for elasticsearch-authz matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Luis Haddad· Dec 8, 2024
We added elasticsearch-authz from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Oshnikdeep· Nov 27, 2024
Keeps context tight: elasticsearch-authz is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Sofia Kim· Nov 7, 2024
I recommend elasticsearch-authz for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Charlotte Tandon· Nov 7, 2024
elasticsearch-authz reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Dev Johnson· Nov 3, 2024
Useful defaults in elasticsearch-authz — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Dev Brown· Nov 3, 2024
We added elasticsearch-authz from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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