Digital Workforce — agentic threat model
Digital Workforce presents a high-risk profile due to its focus on enterprise-wide business automation using a mix of human and digital agents, which likely grants it broad access to sensitive internal systems and workflows.
OWASP AIVSS score rationale
| Autonomy of Action | 0.70 | |
| Goal-Driven Planning | 0.60 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.50 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.40 | |
| Multi-Agent Interactions | 0.80 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.50 |
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 description does not specify which foundation models are used to power the digital agents, leaving potential vulnerabilities to model-specific exploits, prompt injection, or alignment issues uncharacterized.
Not certain from the listing — No details are provided regarding data storage, vector databases, RAG pipelines, or how business data is ingested and secured against poisoning or exfiltration.
Not certain from the listing — The specific orchestration framework, memory mechanisms, and tool-calling implementations are not disclosed, making it difficult to assess risks like insecure tool integration or memory poisoning.
Not certain from the listing — The hosting environment, sandboxing capabilities, and network security controls for these digital workers are not specified.
Not certain from the listing — There is no mention of evaluation frameworks, real-time monitoring, logging, or guardrails to detect and mitigate anomalous agent behavior.
Not certain from the listing — No specific compliance certifications (e.g., SOC2, ISO) or identity and access management (IAM) controls are detailed for the platform.
The platform explicitly operates in a hybrid multi-agent and human-in-the-loop ecosystem ('using people and digital agents') to automate business processes. This introduces significant risks of cascading failures across automated workflows, unauthorized agent-to-agent communication, and trust abuse between human and digital workers.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).