---
title: "AI Asset Discovery: Security Posture Management"
description: "AI asset discovery for models, agents, APIs and shadow AI. Panop inventories every AI system and maps which of them can reach sensitive data."
url: https://panop.io/solutions/ai-spm/
---

# AI-SPM

AI asset discovery for every model, agent and shadow tool.

[Book a demo](https://panop.io/demo)

Validated

1 route that actually reaches production

Inventory

Models, agents, APIs

Includes

Shadow AI

Firewalls & Security Groups

what is actually reachable across each boundary

Three boundaries, one route that actually connects. It is validated, not inferred from configuration.

## What is AI asset discovery?

AI asset discovery is the inventory of every model, agent, API and data pipeline in use, including tools staff adopted without a security review. Panop puts those AI assets into the same exposure model as cloud and application systems, then traces which of them can reach regulated or confidential data.

## Why is AI security posture hard to manage?

AI systems are deployed faster than security teams can inventory them, and the tooling that governs cloud and application risk was not built to reason about models, agents or the data they can reach.

- ### Limited AI Visibility

    Organisations often lack a complete inventory of AI models, agents, APIs, and shadow AI, making it difficult to understand and manage their expanding AI attack surface.

- ### Emerging AI Threats

    AI systems introduce new risks such as prompt injection, data leakage, model manipulation, and excessive agent permissions that traditional security tools cannot effectively detect or validate.

- ### Fragmented Risk Management

    AI security is frequently disconnected from existing cybersecurity programs, making it difficult to prioritise AI risks alongside cloud, identity, and application exposures while meeting evolving governance and compliance requirements.

## How does Panop secure AI models, agents and pipelines?

Panop brings AI assets into the same exposure model as the rest of your estate, so AI risk is prioritised alongside cloud, identity and application exposure.

### Inventory every AI asset

Discover the models, agents, APIs and data pipelines in use across the organisation, including those deployed without security review.

**+3**26/06 to 21/08

Critical 27 High 203 Medium 259 Low 99

### Surface shadow AI

Identify AI services reached by your applications and staff that never entered a governance process.

Business Risk Register

likelihood × impact, traced to the exposure driving it

| ID | Business Risk | Band | L | I | Top Driver | Owner | Treatment |
| --- | --- | --- | --- | --- | --- | --- | --- |
| BR-1 | Data Breach & Confidentiality | High | 5 | 3 | Unrestricted file upload on portal | CISO | Mitigate |
| BR-2 | Operational Disruption | High | 5 | 3 | Unrestricted file upload on portal | CTO | Mitigate |
| BR-3 | Fraud & Financial Loss | High | 5 | 3 | Unrestricted file upload on portal | CFO | Accept |
| BR-4 | Regulatory & Legal Exposure | High | 5 | 3 | Deprecated TLS 1.0 on gateway | CLO | Mitigate |
| BR-5 | Reputational & Brand Damage | High | 5 | 3 | Deprecated TLS 1.0 on gateway | CMO | Mitigate |
| BR-6 | Intellectual Property Theft | High | 5 | 3 | Unrestricted file upload on portal | CISO | Mitigate |

Every band traces back to a specific, validated exposure, so the treatment decision is defensible.

### Map paths to sensitive data

Trace which models and agents can reach regulated or confidential data, and through which permissions.

Risk Evolution

exploitable chains, critical chokepoints & assets at risk over 30 days

Exploitable chains Critical chokepoints Assets at risk

Daily snapshots accrue over time, and the trend fills in as history is recorded.

### Govern against emerging requirements

Align AI exposure findings with the controls the EU AI Act and internal governance policies expect you to evidence.

Maturity Model

NIST CSF 2.0 · current profile against target

Current Target profile

Every function is scored from live evidence, not a questionnaire, so the gap to target moves as the estate does.

## What changes once AI assets are in the exposure model?

A complete inventory of AI assets and the data they can reach

- Models, agents and AI APIs brought into scope alongside cloud and application assets
- Shadow AI deployments surfaced before they reach production data
- Excessive agent permissions identified through reachable data paths
- AI risk prioritised in the same queue as the rest of the estate
- Faster coordination between security, data and engineering teams on AI governance

With Panop, know which AI systems exist, what data they can reach, and **which of those paths matter first**.

[Book a demo](https://panop.io/demo)

## Explore other use cases

- [Risk Prioritisation Know the 10 things to fix today.](https://panop.io/solutions/risk-prioritisation)
- [Autonomous Pentest Continuous validation, not annual exercises.](https://panop.io/solutions/autonomous-pentest)
- [Cloud Security Private Cloud under control.](https://panop.io/solutions/cloud-security)
- [Compliance NIS2. DORA. EU AI Act. Always audit-ready.](https://panop.io/solutions/compliance)
- [Supplier Security Managing Third-Party & Supplier Risk](https://panop.io/solutions/third-party-risk)

[View all solutions](https://panop.io/use-cases)