Runtime security for agentic data access

Authorized ≠ appropriate.

AIOStack connects agents, identities, DB principals, data, and destinations into a single runtime evidence chain.Permissions alone do not make agents safe. Context does.

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Runtime evidence chain showing actor, agent, identity, database principal, data, destination, allowed access, and context break
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Trusted evidence chain

Every hop is authorized. The break is where data leaves context.

A single runtime path showing who acted, which identity and DB principal were used, what sensitive data was touched, and where it moved.

Authorized
User
claims_ops
Authorized
Agent
claims assistant
Authorized
Tool
MCP lookup
Authorized
DB principal
customer_ro
Observed
Sensitive data
KYC + balance
Context break
New destination
external API
Expected path
Every individual hop is authorized by policy.
Context break
The final movement is wrong.
Runtime proof

See what Aurva captures in one runtime pass.

Aurva reconstructs the full chain from prompt to identity to DB principal to access behavior to sensitive data to destination, without relying on app proxies or code changes.

Layer
Evidence
Why it matters
Start
User prompt to resolve customer ticket
Sets the intent and model context for the chain.
Identity
jon.doe@co.com -> svc-gpt-pipeline -> db-principal-prod
Shows the trust path behind the action.
Access behavior
230K rows returned from customer records
High-volume access outside normal scope.
Data touched
PII: customer email, NPS score
Sensitive data was accessed in this flow.
Destination
External endpoint: api.openai.com
Flag: data left the trusted boundary.
Behavior
Volume spike above baseline
Behavior drifted.
Why posture is not enough

Access graphs show what can happen. Aurva shows what did happen.

IAM and NHI tools are essential. But agentic risk appears when trusted access moves beyond permission into DB use, query behavior, sensitive data, and downstream movement.

IAM / NHI posture
What access exists?

You see who could access, not what actually happened.

Cloud activity
What control-plane events were logged?

You see activity, not the full runtime story.

Aurva runtime layer
What actually happened to sensitive data?

You see actor, identity, DB principal, query behavior, data touched, destination, and drift.

Category boundary

Built for the runtime layer others do not see.

IAM stops at permission. NHI stops at identity. Cloud logs stop at control-plane activity. Gateways see only traffic that passes through them.

IAM / NHI
Who has access
What they did with sensitive data
Cloud logs
Control-plane events
DB principal, query behavior, data touched
Agent gateways
Traffic that passes through them
Runtime access outside the gateway path
AIOStack
Runtime data access chain
Actor, identity, DB principal, query, data, destination, drift
What AIOStack does

Full agentic security in one runtime layer.

AIOStack turns fragmented agent activity into an evidence-backed map of identities, tools, data, behavior, and risk.

01

Runtime evidence layer

Connect agents, identities, DB principals, data touched, destinations, and behavior into one explainable chain.

02

Agent discovery

See agents, MCP servers, tools, vector DBs, and unmanaged deployments.

03

Identity chain mapping

Trace user to agent to service account to DB principal.

04

Multi-agent lineage

Reconstruct tool calls, data touched, and downstream actions.

05

Sensitive data movement

Understand what data was touched, where it moved, and whether the destination was expected.

06

Governance from behavior

Right-size permissions and reduce drift using observed runtime evidence.

Install AIOStack

Get started in minutes, not weeks

Start with runtime visibility for local and cloud deployments. Install when you are ready, or talk to an engineer for a guided rollout.

curl -fsSL https://aurva.ai/install.sh | bash