Vectranetworks API

openapi: 3.1.0
info:
  title: Vectranetworks API
  version: '2026-10-22'
  description: 'GENERATED FROM DOCUMENTATION by API Evangelist on 2026-10-22: 26 operation(s) read from 26 public documentation page(s) (each
    operation names its page in x-source). This is not the provider''s published contract; Vectranetworks has published no machine-readable contract
    that the pipeline could find. Engine: local.'
  x-evidence-tiers:
    code-example: 0
    documentation: 26
    pages-with-code: 0
    pages-read: 26
  x-generated-from: documentation
  x-provenance: generated
  x-authored-by: API Evangelist
  x-generated: '2026-10-22'
  x-generator: generate-contract-from-docs.py
  x-engine: local
  x-sources:
  - https://docs.vectra.ai/reference/in-app-support.md
  - https://docs.vectra.ai/reference/product-security.md
  - https://docs.vectra.ai/reference/metadata-attributes.md
  - https://docs.vectra.ai/reference/ai-and-ml-terminology.md
  - https://docs.vectra.ai/reference/appliance-eos-eol-policy.md
  - https://docs.vectra.ai/reference/rspan-and-erspan-support.md
  - https://docs.vectra.ai/reference/ai-driven-priortization-faq.md
  - https://docs.vectra.ai/reference/vectra-ui-supported-browsers.md
  - https://docs.vectra.ai/reference/understanding-vectra-host-naming.md
  - https://docs.vectra.ai/reference/how-detection-pcaps-are-generated.md
  - https://docs.vectra.ai/reference/why-is-metadata-sharing-important.md
  - https://docs.vectra.ai/reference/bandwidth-used-between-sensor-and-brain.md
  - https://docs.vectra.ai/reference/product-security/vectra-hardening-appliances.md
  - https://docs.vectra.ai/reference/vectra-coverage-of-mitre-attandck-and-d3fend.md
  - https://docs.vectra.ai/reference/product-security/detect-for-aws-compliance-brief.md
  - https://docs.vectra.ai/operations/analyst-guidance/advanced-search-reference-guide-qux.md
  - https://docs.vectra.ai/operations/event-search/investigate-api-metadata-schema-reference.md
  - https://docs.vectra.ai/reference/metadata-attributes/vectra-ai-platform-azure-metadata-attributes.md
  - https://docs.vectra.ai/reference/metadata-attributes/vectra-ai-platform-network-metadata-attributes.md
  - https://docs.vectra.ai/reference/metadata-attributes/vectra-ai-platform-aws-cloudtrail-metadata-attributes.md
  - https://docs.vectra.ai/reference/metadata-attributes/vectra-ai-platform-azure-ad-and-m365-metadata-attributes.md
  - https://docs.vectra.ai/operations/backup-restore-dr.md
  - https://docs.vectra.ai/operations/event-search/investigate-api-user-guide.md
  - https://docs.vectra.ai/operations/backup-restore-dr/backup-and-restore-v85.md
  - https://docs.vectra.ai/operations/backup-restore-dr/backup-and-restore-v85/restoring-backups.md
  - https://docs.vectra.ai/operations/backup-restore-dr/backup-and-restore-v85/backup-and-restore-faq.md
paths:
  /api/v3.4/investigations:
    post:
      operationId: post_api_v3_4_investigations
      tags:
      - Api
      summary: Submit a query
      x-source: https://docs.vectra.ai/operations/event-search/investigate-api-user-guide.md
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/PostApiV34InvestigationsRequest'
      responses:
        '200':
          description: Success (status as documented)
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PostApiV34InvestigationsResponse'
      x-evidence:
        kind: documentation
  /api/v3.4/investigations/{requestId}:
    get:
      operationId: get_api_v3_4_investigations_requestId
      tags:
      - Api
      summary: Get results (poll or retrieve pages) for a query
      x-source: https://docs.vectra.ai/operations/event-search/investigate-api-user-guide.md
      parameters:
      - name: requestId
        in: path
        required: true
        schema:
          type: string
      - name: page
        in: query
        required: false
        schema:
          type: integer
        description: Page number (default 1)
      - name: page_size
        in: query
        required: false
        schema:
          type: integer
        description: Rows per page (default 100, max 10,000)
      responses:
        '200':
          description: Success (status as documented)
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/GetApiV34InvestigationsRequestidResponse'
      x-evidence:
        kind: documentation
  /oauth2/token:
    post:
      operationId: post_oauth2_token
      tags:
      - Oauth2
      summary: Obtain an OAuth 2.0 access token
      x-source: https://docs.vectra.ai/operations/event-search/investigate-api-user-guide.md
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/PostOauth2TokenRequest'
      responses:
        '201':
          description: Success (status as documented)
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/PostOauth2TokenResponse'
      x-evidence:
        kind: documentation
  /operations/analyst-guidance/advanced-search-reference-guide-qux.md:
    get:
      operationId: get_operations_analyst_guidance_advanced_search_reference_guide_qux_md
      tags:
      - Operations
      summary: Advanced search reference guide (QUX)
      x-source: https://docs.vectra.ai/operations/analyst-guidance/advanced-search-reference-guide-qux.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s overall goal, describing the desired outcome.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /operations/backup-restore-dr.md:
    get:
      operationId: get_operations_backup_restore_dr_md
      tags:
      - Operations
      summary: Backup / Restore / DR
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer and relevant
        excerpts from the documentation.
      x-source: https://docs.vectra.ai/operations/backup-restore-dr.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s overall goal, describing the desired outcome.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /operations/backup-restore-dr/backup-and-restore-v85.md:
    get:
      operationId: get_operations_backup_restore_dr_backup_and_restore_v85_md
      tags:
      - Operations
      summary: Backup and restore (v8.5+)
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer and relevant
        excerpts from the documentation.
      x-source: https://docs.vectra.ai/operations/backup-restore-dr/backup-and-restore-v85.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s overall goal, describing the desired outcome.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /operations/backup-restore-dr/backup-and-restore-v85/backup-and-restore-faq.md:
    get:
      operationId: get_operations_backup_restore_dr_backup_and_restore_v85_backup_and_restore_faq_m
      tags:
      - Operations
      summary: Backup and restore FAQ
      x-source: https://docs.vectra.ai/operations/backup-restore-dr/backup-and-restore-v85/backup-and-restore-faq.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question to ask the documentation.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The broader goal behind the question.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /operations/backup-restore-dr/backup-and-restore-v85/restoring-backups.md:
    get:
      operationId: get_operations_backup_restore_dr_backup_and_restore_v85_restoring_backups_md
      tags:
      - Operations
      summary: Restoring backups
      description: Perform an HTTP GET request on the documentation page with the `ask` and `goal` query parameters to retrieve a direct answer
        and relevant excerpts from the documentation.
      x-source: https://docs.vectra.ai/operations/backup-restore-dr/backup-and-restore-v85/restoring-backups.md
      parameters:
      - name: ask
        in: query
        required: true
        schema:
          type: string
        description: The immediate question to ask the documentation engine, specific and self‑contained, written in natural language.
      - name: goal
        in: query
        required: true
        schema:
          type: string
        description: The broader goal the user wants to achieve, describing the desired outcome rather than restating the question.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/ai-and-ml-terminology.md:
    get:
      operationId: get_reference_ai_and_ml_terminology_md
      tags:
      - Reference
      summary: AI and ML terminology
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer and relevant
        excerpts from the documentation.
      x-source: https://docs.vectra.ai/reference/ai-and-ml-terminology.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question; specific, self‑contained, natural language.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s overall goal; describes the outcome they want to achieve.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/ai-driven-priortization-faq.md:
    get:
      operationId: get_reference_ai_driven_priortization_faq_md
      tags:
      - Reference
      summary: FAQ for AI-driven Prioritization (Urgency scoring) in Respond UX.
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer from the documentation.
      x-source: https://docs.vectra.ai/reference/ai-driven-priortization-faq.md
      parameters:
      - name: ask
        in: query
        required: true
        schema:
          type: string
        description: The immediate question to ask the documentation.
      - name: goal
        in: query
        required: true
        schema:
          type: string
        description: The overall goal the user is trying to achieve.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/appliance-eos-eol-policy.md:
    get:
      operationId: get_reference_appliance_eos_eol_policy_md
      tags:
      - Reference
      summary: Appliance support and EOS / EOL policy
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve answers from the documentation.
      x-source: https://docs.vectra.ai/reference/appliance-eos-eol-policy.md
      parameters:
      - name: ask
        in: query
        required: true
        schema:
          type: string
        description: The immediate question to ask the documentation.
      - name: goal
        in: query
        required: true
        schema:
          type: string
        description: The broader goal the user is trying to achieve.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/bandwidth-used-between-sensor-and-brain.md:
    get:
      operationId: get_reference_bandwidth_used_between_sensor_and_brain_md
      tags:
      - Reference
      summary: Bandwidth used between Sensor and Brain
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer and relevant
        excerpts from the documentation.
      x-source: https://docs.vectra.ai/reference/bandwidth-used-between-sensor-and-brain.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained, written in natural language.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s ultimate goal, describing the outcome they want to achieve.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/how-detection-pcaps-are-generated.md:
    get:
      operationId: get_reference_how_detection_pcaps_are_generated_md
      tags:
      - Reference
      summary: How detection PCAPs are generated
      description: Performs an HTTP GET request on the documentation page, optionally providing `ask` and `goal` query parameters to retrieve
        a direct answer and relevant excerpts.
      x-source: https://docs.vectra.ai/reference/how-detection-pcaps-are-generated.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question to ask the documentation.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The broader goal behind the question.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/in-app-support.md:
    get:
      operationId: get_reference_in_app_support_md
      tags:
      - Reference
      summary: In-App support
      x-source: https://docs.vectra.ai/reference/in-app-support.md
      parameters:
      - name: ask
        in: query
        required: true
        schema:
          type: string
        description: The immediate question, specific and self‑contained.
      - name: goal
        in: query
        required: true
        schema:
          type: string
        description: The user’s overall goal, describing the desired outcome.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/metadata-attributes.md:
    get:
      operationId: get_reference_metadata_attributes_md
      tags:
      - Reference
      summary: Metadata attributes
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer and relevant
        excerpts from the documentation.
      x-source: https://docs.vectra.ai/reference/metadata-attributes.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained, written in natural language.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s ultimate goal, describing the outcome they want to achieve.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/metadata-attributes/vectra-ai-platform-aws-cloudtrail-metadata-attributes.md:
    get:
      operationId: get_reference_metadata_attributes_vectra_ai_platform_aws_cloudtrail_metadata_att
      tags:
      - Reference
      summary: Vectra AI Platform AWS CloudTrail metadata attributes
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer and relevant
        excerpts from the documentation.
      x-source: https://docs.vectra.ai/reference/metadata-attributes/vectra-ai-platform-aws-cloudtrail-metadata-attributes.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s ultimate goal, describing the desired outcome.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/metadata-attributes/vectra-ai-platform-azure-ad-and-m365-metadata-attributes.md:
    get:
      operationId: get_reference_metadata_attributes_vectra_ai_platform_azure_ad_and_m365_metadata_
      tags:
      - Reference
      summary: Vectra AI Platform Azure AD and M365 metadata attributes
      description: Perform an HTTP GET request on the documentation page with the `ask` and `goal` query parameters to retrieve a direct answer
        and relevant excerpts.
      x-source: https://docs.vectra.ai/reference/metadata-attributes/vectra-ai-platform-azure-ad-and-m365-metadata-attributes.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained, written in natural language.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s ultimate goal, describing the outcome they want to achieve.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/metadata-attributes/vectra-ai-platform-azure-metadata-attributes.md:
    get:
      operationId: get_reference_metadata_attributes_vectra_ai_platform_azure_metadata_attributes_m
      tags:
      - Reference
      summary: Vectra AI Platform Azure metadata attributes
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer and relevant
        excerpts from the documentation.
      x-source: https://docs.vectra.ai/reference/metadata-attributes/vectra-ai-platform-azure-metadata-attributes.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: 'The immediate question: it should be specific, self-contained, and written in natural language.'
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s ultimate goal, describing the outcome they want.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/product-security.md:
    get:
      operationId: get_reference_product_security_md
      tags:
      - Reference
      summary: Product security statements and hardening guidance.
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer and relevant
        excerpts from the documentation.
      x-source: https://docs.vectra.ai/reference/product-security.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained, written in natural language.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s ultimate goal, describing the outcome they want to achieve.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/product-security/detect-for-aws-compliance-brief.md:
    get:
      operationId: get_reference_product_security_detect_for_aws_compliance_brief_md
      tags:
      - Reference
      summary: Detect for AWS compliance brief
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer and relevant
        excerpts from the documentation.
      x-source: https://docs.vectra.ai/reference/product-security/detect-for-aws-compliance-brief.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained, written in natural language.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s ultimate goal, describing the outcome they want to achieve.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/product-security/vectra-hardening-appliances.md:
    get:
      operationId: get_reference_product_security_vectra_hardening_appliances_md
      tags:
      - Reference
      summary: Vectra hardening (appliances)
      x-source: https://docs.vectra.ai/reference/product-security/vectra-hardening-appliances.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained, written in natural language.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s ultimate goal, describing the outcome they want to achieve.
      responses:
        '200':
          description: Success (status as documented)
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/GetReferenceProductSecurityVectraHardeningAppliancesMdRespon'
      x-evidence:
        kind: documentation
  /reference/rspan-and-erspan-support.md:
    get:
      operationId: get_reference_rspan_and_erspan_support_md
      tags:
      - Reference
      summary: RSPAN and ERSPAN support
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve answers from the documentation.
      x-source: https://docs.vectra.ai/reference/rspan-and-erspan-support.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
      - name: goal
        in: query
        required: false
        schema:
          type: string
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/understanding-vectra-host-naming.md:
    get:
      operationId: get_reference_understanding_vectra_host_naming_md
      tags:
      - Reference
      summary: Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters
      x-source: https://docs.vectra.ai/reference/understanding-vectra-host-naming.md
      parameters:
      - name: ask
        in: query
        required: true
        schema:
          type: string
        description: 'The immediate question: it should be specific, self-contained, and written in natural language.'
      - name: goal
        in: query
        required: true
        schema:
          type: string
        description: The user’s ultimate goal, describing the outcome they want to achieve.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/vectra-coverage-of-mitre-attandck-and-d3fend.md:
    get:
      operationId: get_reference_vectra_coverage_of_mitre_attandck_and_d3fend_md
      tags:
      - Reference
      summary: Vectra's coverage of MITRE ATT&CK and D3FEND
      x-source: https://docs.vectra.ai/reference/vectra-coverage-of-mitre-attandck-and-d3fend.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question, specific and self‑contained.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The user’s overall goal, describing the desired outcome.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/vectra-ui-supported-browsers.md:
    get:
      operationId: get_reference_vectra_ui_supported_browsers_md
      tags:
      - Reference
      summary: Vectra UI supported browsers
      description: Performs an HTTP GET request on the documentation page with optional `ask` and `goal` query parameters to retrieve a direct
        answer and relevant excerpts.
      x-source: https://docs.vectra.ai/reference/vectra-ui-supported-browsers.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question to ask the documentation engine, specific and self‑contained, written in natural language.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The broader goal the user is trying to achieve, used to tailor the answer.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
  /reference/why-is-metadata-sharing-important.md:
    get:
      operationId: get_reference_why_is_metadata_sharing_important_md
      tags:
      - Reference
      summary: Why is metadata sharing important
      description: Perform an HTTP GET request on the URL with the `ask` and `goal` query parameters to retrieve a direct answer from the documentation.
      x-source: https://docs.vectra.ai/reference/why-is-metadata-sharing-important.md
      parameters:
      - name: ask
        in: query
        required: false
        schema:
          type: string
        description: The immediate question to ask the documentation.
      - name: goal
        in: query
        required: false
        schema:
          type: string
        description: The overall goal the user is trying to achieve.
      responses:
        '200':
          description: Success (status as documented)
      x-evidence:
        kind: documentation
components:
  schemas:
    PostApiV34InvestigationsRequest:
      type: object
      properties:
        query:
          type: string
          description: SQL‑like query string
        version:
          type: string
          description: Query language version, default "1.0"
      required:
      - query
    PostApiV34InvestigationsResponse:
      type: object
      properties:
        request_id:
          type: string
          description: Identifier for the submitted query
        searchable_range:
          type: object
          description: Object containing searchable_days_allowed
    GetApiV34InvestigationsRequestidResponse:
      type: object
      properties:
        request_id:
          type: string
          description: Echo of the query identifier
        data:
          type: array
          description: Array of result rows
        meta.page:
          type: integer
          description: Current page number
        meta.page_size:
          type: integer
          description: Rows returned on this page
        meta.num_rows_available:
          type: integer
          description: Total rows available for the query
        meta.query_status:
          type: string
          description: '"RUNNING", "SUCCESS", or "FAILED"'
        meta.columns:
          type: array
          description: Result schema description
    PostOauth2TokenRequest:
      type: object
      properties:
        grant_type:
          type: string
          description: client_credentials
        client_id:
          type: string
          description: Your API client ID
        client_secret:
          type: string
          description: Your API client secret
      required:
      - grant_type
      - client_id
      - client_secret
    PostOauth2TokenResponse:
      type: object
      properties:
        access_token:
          type: string
          description: Bearer token for API calls
        token_type:
          type: string
          description: Token type, typically "Bearer"
        expires_in:
          type: integer
          description: Lifetime of the token in seconds
    GetReferenceProductSecurityVectraHardeningAppliancesMdRespon:
      type: object
      properties:
        content:
          type: string
          description: The markdown content of the documentation page or the answer to the query.
  securitySchemes:
    Token:
      type: apiKey
      in: header
      name: Authorization
      x-source: https://docs.vectra.ai/configuration/access/external-authentication-qux.md
tags:
- name: Api
- name: Oauth2
- name: Operations
- name: Reference
security:
- Token: []