Agency AI — agentic threat model
Agency AI acts as a centralized hub for agent development and observability (AgentOps), making it a high-value target; a compromise could expose execution logs, API keys, and control flows across hundreds of production enterprise agents.
OWASP AIVSS score rationale
| Autonomy of Action | 0.20 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.30 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.20 | |
| Multi-Agent Interactions | 0.70 | |
| 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, supporting various LLMs. Threats include adversarial prompt injection bypassing the observability layer or model-level vulnerabilities in the underlying 400+ production agents.
Not certain from the listing — As an observability platform (AgentOps), it ingests massive amounts of execution traces, prompts, and outputs. This creates a high risk of data exfiltration or exposure of sensitive PII/secrets logged during agent runs.
Agency AI provides developer tools and AgentOps for agent orchestration. Vulnerabilities in the framework or SDKs could allow malicious agents to bypass guardrails, poison agent memory, or execute unauthorized tool calls.
Not certain from the listing — Hosting details for the 400+ production agents are unspecified. Risks include container escape, insecure API endpoints for AgentOps telemetry, and lack of sandboxing for executed agent code.
This is Agency AI's core strength via AgentOps. However, threats include blind spots in telemetry, evasion of logging by sophisticated malicious agents, or log tampering to hide unauthorized actions.
Not certain from the listing — While aiming for 'dependable' enterprise AI, specific compliance standards (e.g., SOC2, GDPR) or fine-grained RBAC for the observability dashboard are not detailed.
With over 400 agents in production, the platform is highly exposed to multi-agent cascading failures, rogue agent interactions, and trust abuse across different agent deployments.
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.