Agentic Security
Secure agent behavior at runtime.
Connect purpose, identity, tools, sensitive data, and destinations in one view.
Agentic Security
Connect purpose, identity, access, and outcome
Runtime evidence chain
The observed path behind this activity
Initiator
support-user
Verified
Agent
case-resolution
Managed
MCP tool
customer-lookup
Approved
Data
customer.pii
Sensitive
Destination
external-api
First seen
Purpose changed during execution
Sensitive customer data moved to a destination outside the established support workflow.
See the path behind every agent action
Connect each request to the identities, tools, data systems, and destinations involved.
Intent drift
Detect when an agent's destinations, tools, data access, credentials, commands, or activity pattern no longer fit its established purpose.
Agent identity
Trace an action from its initiating actor through delegated agents, services, credentials, and downstream principals.
Runtime governance
Use observed behavior to review permissions, investigate risky handoffs, and define clearer operating boundaries.
THE RUNTIME GAP
Permission does not prove purpose.
Evaluate the entire workflow, not each permitted step in isolation.
Runtime context
Observed evidence chain
Prompts, responses, model and tool activity
RAG and vector-database access
Sensitive data access and downstream movement
01 / RUNTIME CONTEXT
Reconstruct the workflow
Connect prompts and responses with retrieval, tool calls, MCP activity, database access, service-to-service traffic, and egress. The result shows how the request was carried out across systems.
Runtime comparison
Expected and observed behavior
Expected
Observed
02 / APPROPRIATE USE
Assess data, authority, and outcome
A new endpoint is not automatically a threat. Aurva considers the agent's established purpose, the sensitivity and scale of access, the authority used, and where the result went before raising a finding.
Reviewable finding
Runtime evidence · high confidence
Reviewable intent and identity context
Permission and credential risk surfaced together
Containment and right-sizing recommendations
03 / GOVERNANCE
Tighten operating boundaries
Use findings to review intent, investigate risky handoffs, and right-size permissions. Aurva provides the supporting records and a recommended response; enforcement remains under customer control.
RUNTIME SIGNALS
Explain every agent action
Correlate model, identity, application, and data-system records.
01
Agent and model
Which agent or service acted, which model it used, and what operation ran.
02
Identity and delegation
The initiating actor, delegated agents and services, credentials, and service principals.
03
Data and tools
The MCP tools, APIs, databases, vector stores, and sensitive data involved.
04
Destination and outcome
Where information moved and whether the result remained within expected boundaries.
Connect inventory to runtime activity.
See what exists, who acted, and what data moved.
Trace every agent action.
See where purpose or authority changed.
Inventory the AI estate.
Find models, tools, MCP servers, and vector stores.
