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PyroTrace independently verifies what your production AI agents can reach, what they actually touch, and which of it is sensitive.

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Your agent can reach 47 systems. It used 3. One holds PII it has no business touching.

PyroTrace maps what production AI agents can reach, records what they actually use, and flags sensitive access. It does not rely on configuration alone.

Book a 20-minute demo→Explore a sample agent map
checkout-agentrole/agent-checkoutsupport-agentrole/agent-supportmcp-gatewaypayments-toolss3://orders-prodrds/customerssecrets/paymentsPIIbedrock/claudeapi.vendor.io+41
ObservedFirst-seenRiskyInternetGranted, unused
Agent mapSensor-observed
checkout-agentrole/agent-checkoutsupport-agentrole/agent-supportmcp-gatewaypayments-toolss3://orders-prodrds/customerssecrets/paymentsPIIbedrock/claudeapi.vendor.io+41
ObservedFirst-seenRiskyInternetGranted, unused
Reach47 resources granted
Used3 touched, sensor-observed
Sensitive1 PII-classified
Verify

An evidence-backed inventory of every AI agent and MCP server you actually run

Measure

Resource reach per agent: granted vs. used, joined with data sensitivity

Reduce

Review unused grants and document the resulting reduction in reach

Built for production AI

Independent evidence for security, platform, and compliance teams.

Deploy

Read-only, kernel-level sensor

Connect

AWS, CloudTrail, Bedrock, SageMaker, MCP

Understand

Evidence linked to every finding

Conversation controls inspect prompts. Posture tools inspect config. PyroTrace adds workload evidence.

Production AI agents hold real credentials and real reach into your cloud. Conventional inventory and posture data can leave their observed resource use unresolved.

Shadow agents & MCP

Discover production agents from observed activity.

Evidence: attributed workload traffic

Names aren't evidence

Verify identities instead of trusting role names.

Evidence: identity and role chain

Standing grants pile up

Separate permissions granted from permissions used.

Action: review unused grants

Sensitive data, one hop away

Expose reachable PII, PHI, and payment resources.

Evidence: classified resource path

The invisible middle

Connect agent activity to cloud and network events.

Evidence: prompt-to-resource run story

Audit deadlines are real

Export an evidence-linked record of reach and use.

Action: framework-mapped report

Verify the inventory. Measure the reach. Reduce it.

PyroTrace joins what each agent is granted with what it demonstrably did, then turns the gap into safe, provable least-privilege cuts.

01

Inventory with evidence

Every agent and MCP server, proven

Agents are discovered from sensor, CloudTrail, and gateway telemetry. Every inventory entry is backed by observed activity, never a configuration name alone.

02

Measure real reach

Granted vs. used, per agent

Resource-Reach Utilization, Sensitive Reach, and Shadow Access & Egress: the modeled reach of each agent joined against what the sensor actually observed.

03

Reduce and prove

Cut unused grants, export the proof

Review grants with no observed use, surface first-seen and risky paths on the Agent Map, and export framework-mapped reports with supporting evidence.

Granted vs. used, joined with sensitivity.

For every agent, one answer: how many resources it can reach, how many it demonstrably touched, and which of them hold data that matters. That gap helps prioritize least-privilege reviews.

  • Reach is computed from live IAM role chains, network paths, and model layer permissions. This includes who can invoke Bedrock and SageMaker models.
  • Usage is observed from traffic attributed to agents at the kernel, CloudTrail, and gateway telemetry. This includes bytes sent.
  • Sensitivity joined from data classification: PII, PHI, and payment data flagged where an agent can actually reach it

Log-based tools tell you a token was used. We show when agent-attributed traffic reached a sensitive-classified resource; payload content remains unverified.

PII
47
Reachable · granted
3
Touched · observed
1
Sensitive · classified

Every claim carries its evidence.

Agents are identified through an evidence ladder. It uses registry facts, structural facts, operator declarations, observed behavior. A name is never evidence.

PyroTrace Sensorkernel · eBPFAWS CloudTrailcontrol planeMCP gatewaytool callsLLM telemetryOTel GenAI · sidecarSIEM importSplunk · SentinelEDRhost activityEvidenceledger
PyroTrace Sensor

kernel-level (eBPF), read-only flow observation

AWS CloudTrail

control-plane API activity

MCP gateway

tool calls and server registrations

LLM telemetry

OTel GenAI, gateway, sidecar

SIEM import

Splunk, Sentinel mappings

EDR

host activity imports

We watch from the kernel.

Log-based tools tell you a token was used. PyroTrace shows when agent-attributed traffic reached a sensitive-classified resource or external endpoint. Payload content remains unverified by design.

1

Not a CNAPP

We don't rescan your cloud posture. We verify what your agents actually do with the access your cloud already grants them.

2

Not another alert feed

Findings map to OWASP LLM Top 10, MITRE ATLAS, and NIST AI RMF. Each finding includes evidence instead of a severity guess.

3

Independent by design

The sensor observes the workload itself, so the inventory never depends on teams remembering to self-report their agents.

See your agents' real reach.

See how PyroTrace connects agent identity, reachable resources, observed usage, and data sensitivity in one evidence-backed view.

Book a 20-minute demo →Explore a sample agent map