Kyberis helps agents and security teams decide what matters now. Use it to resolve threat entities, retrieve bounded evidence, pivot through relationships, prioritize signals for an environment, and produce deterministic assessments.Documentation Index
Fetch the complete documentation index at: https://developer.kyberis.ai/llms.txt
Use this file to discover all available pages before exploring further.
Get started
Make your first authenticated request, resolve an entity, and run an assessment.
Set up an agent
Install the Kyberis skill and connect MCP for Claude, Cursor, Codex, or Windsurf.
Investigate a CVE
Validate active exploitation, relationships, evidence, and remediation priority.
Interpret responses
Understand resolution states, evidence, rankings, assessments, batches, and errors.
What Kyberis returns
Kyberis APIs return structured JSON for machine consumers. Serving-path assessment generation is deterministic and LLM-free, so agents can branch on fields such asresolution.status, priority_score, confidence_score, evidence IDs, and error_code.
Recommended workflow
- Resolve raw input with
/v2/entity-resolutionunless the request is broad discovery. - Retrieve claim-level evidence with
/v2/evidence. - Pivot with
/v2/relationshipswhen you need related actors, campaigns, malware, sectors, or indicators. - Rank environment-relevant signals with
/v2/prioritize. - Run the specific assessment endpoint for the subject type.
- Preserve
request_id,run_id,step_id, confidence, caveats, and evidence references in your final answer.
Build paths
API keys
Authenticate directly with REST APIs or mint short-lived bearer tokens.
Skills
Give coding agents Kyberis investigation playbooks and response rules.
API reference
Explore every endpoint from the OpenAPI specification.