Invicta AI — agentic threat model
Invicta AI is a closed-source platform for orchestrating multi-agent teams, presenting elevated systemic risks due to complex agent-to-agent interactions, potential cascading failures, and a lack of visible security guardrails or sandboxing controls.
OWASP AIVSS score rationale
| Autonomy of Action | 0.80 | |
| Goal-Driven Planning | 0.80 | |
| Self-Modification | 0.30 | |
| Dynamic Tool Use | 0.70 | |
| Persistent Memory | 0.60 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.50 | |
| Multi-Agent Interactions | 1.00 | |
| Non-Determinism | 0.80 | |
| Opacity & Reflexivity | 0.80 |
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 allows building teams of agents, but the specific underlying foundation models (e.g., GPT-4, Claude) are not detailed. Threats include model reprogramming or misaligned outputs if users can plug in arbitrary models.
Not certain from the listing — No specific details on RAG, vector databases, or training data pipelines are provided. Threats include knowledge-base poisoning or data exfiltration if agents access shared data stores.
As an orchestration platform for building teams of agents, the framework layer is highly critical. Threats include insecure tool integration, tool misuse, and memory poisoning across the orchestrated agents.
Not certain from the listing — As a closed-source platform, the hosting, sandboxing, and secrets management details are unspecified. Threats include container compromise or lateral movement if agent execution environments are not properly sandboxed.
Not certain from the listing — No mention of built-in evaluation, logging, or guardrail mechanisms. Threats include blind spots in multi-agent interactions and lack of auditability for cascading agent failures.
Not certain from the listing — No explicit compliance certifications (like SOC2, ISO) or identity/access management controls are mentioned in the brief description.
Highly relevant as the platform explicitly supports building 'Teams of AI Agents' (multi-agent orchestration). Threats include agent-to-agent trust abuse, cascading failures, and rogue/compromised agents within a team.
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.