Inspeq AI — agentic threat model
Inspeq AI is a low-risk observability and compliance platform rather than an active autonomous agent. Its primary security risks involve the integrity of its evaluation metrics and the confidentiality of the application telemetry and logs it monitors.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.10 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.40 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.30 | |
| Opacity & Reflexivity | 0.30 |
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 — the platform is model-agnostic and acts as an evaluation layer rather than hosting a specific foundation model, though it may use internal LLMs-as-a-judge which are vulnerable to adversarial prompt injection.
Not certain from the listing — while it processes evaluation datasets and application logs for monitoring, the exact storage, vector database usage, or RAG architecture is not specified.
Not certain from the listing — it functions as an external monitoring and testing suite rather than an active agent framework executing multi-step autonomous plans.
Supports cloud-agnostic, on-premise, and offline deployments, which significantly reduces external exposure but shifts the burden of secure hosting, sandboxing, and network isolation to the customer's infrastructure.
This is the core of Inspeq AI, focusing on testing, monitoring, and compliance. Threats include evaluation gaming, blind spots in custom metrics, or manipulation of the monitoring telemetry to hide non-compliant behavior.
Explicitly designed for compliance and responsible AI governance. However, the listing does not detail its own internal RBAC, audit logging, or specific certifications like SOC2.
Not certain from the listing — it is a horizontal observability platform and does not explicitly mention multi-agent orchestration or marketplace integrations.
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.