Spot AI — agentic threat model
Spot AI presents a high-impact risk profile primarily due to its integration with physical security infrastructure (IP cameras) and real-time surveillance data, where compromise could lead to severe privacy violations and physical security breaches.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.40 | |
| Opacity & Reflexivity | 0.60 |
Scored with the canonical OWASP AIVSS formula (AIVSS calculator reference); agentic risk factors estimated from the agent’s described capabilities.
MAESTRO 7-layer threat model
Per-layer threats for this agent. Layers tagged “not certain from listing” are general, caveated commentary where the public description didn’t pin that layer.
Not certain from the listing — relies on computer vision and video intelligence models which are highly susceptible to physical adversarial attacks (e.g., adversarial patches or clothing designed to evade detection) and model evasion.
Ingests, processes, and stores real-time video streams from local IP cameras. Key threats include unauthorized access to stored footage, data exfiltration of sensitive surveillance data, and potential tampering with video history.
Not certain from the listing — the orchestration layer managing video analytics pipelines and alerting logic is unspecified, but vulnerabilities here could allow attackers to suppress alerts or manipulate detection thresholds.
Deployed as a hybrid cloud video platform connecting to local IP cameras. This introduces risks of edge gateway compromise, lateral movement from the cloud platform into local OT/IT networks, and unauthorized access to cloud dashboards.
Not certain from the listing — lacks details on how model drift, false positive rates, or camera tampering (e.g., lens covering) are monitored and validated to prevent blind spots.
Not certain from the listing — surveillance platforms require strict role-based access control (RBAC) and compliance with privacy regulations (GDPR/CCPA) regarding facial recognition and public recording, which are not detailed here.
Not certain from the listing — potential integrations with external physical security systems (e.g., access control, alarms) could lead to cascading failures or unauthorized physical access if the AI triggers false positives.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).
These scores are auto-generated from public information (the agent's own listing, docs, and repository) using the canonical OWASP AIVSS formula and the MAESTRO framework — an estimate for guidance, not a penetration test, audit, or certification. See the scoring methodology. Are you the vendor? Factual corrections are free.