Every AI asset, known and shadow.
Firewalls & Security Groups
what is actually reachable across each boundary
Three boundaries, one route that actually connects — validated, not inferred from configuration.
AI-SPM is the practice of inventorying every AI model, agent, API and data pipeline an organisation runs, then tracking which of them can reach sensitive data. Panop discovers AI assets across the estate, including shadow deployments that never entered a governance process, traces the permissions and paths connecting them to regulated data, and prioritises those findings in the same queue as cloud, identity and application exposure.
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.
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.
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.
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.
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.
Discover the models, agents, APIs and data pipelines in use across the organisation, including those deployed without security review.
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.
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
Daily snapshots accrue over time — the trend fills in as history is recorded.
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
Every function is scored from live evidence, not a questionnaire — so the gap to target moves as the estate does.
A complete inventory of AI assets and the data they can reach
With Panop, know which AI systems exist, what data they can reach, and which of those paths matter first.
Know the 10 things to fix today.
Continuous validation, not annual exercises.
Private Cloud under control.
NIS2. DORA. EU AI Act. Always audit-ready.
Managing Third-Party & Supplier Risk
