Robocorp — agentic threat model
Robocorp is an enterprise-grade platform for building and scaling AI agents, presenting high risk due to its deep integration with business systems and automation capabilities, which could lead to significant impact if compromised.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.70 | |
| Self-Modification | 0.20 | |
| Dynamic Tool Use | 0.90 | |
| Persistent Memory | 0.60 | |
| Contextual Awareness | 0.60 | |
| Dynamic Identity | 0.70 | |
| Multi-Agent Interactions | 0.60 | |
| 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 specific foundation models used depend entirely on the developer's choice during implementation on the Robocorp platform.
Not certain from the listing — Data operations, vector stores, and RAG pipelines are configured by the enterprise building on the platform, rather than being pre-defined.
Robocorp provides the core orchestration framework and action-server capabilities. Key threats include insecure tool integration, prompt injection bypassing tool constraints, and framework-level vulnerabilities in action execution.
As a platform for scaling agents, Robocorp manages execution environments (cloud/hybrid). Threats include container escape, privilege escalation within the runner environment, and exposure of API keys or secrets used for integrations.
Not certain from the listing — While Robocorp provides run monitoring via its control room, specific AI-centric evaluation, guardrails, and drift detection capabilities are not detailed in the brief listing.
Not certain from the listing — Enterprise platforms typically implement RBAC and compliance controls, but specific certifications (e.g., SOC2, ISO) are not explicitly detailed in this listing.
The platform is designed to scale multiple AI agents. Threats include cascading failures across automated workflows, unauthorized agent-to-agent interactions, and compromised agents executing malicious actions across the enterprise ecosystem.
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.