Charisma.ai — agentic threat model
Charisma.ai presents a low-to-moderate risk profile, primarily focused on conversational brand safety and data privacy of analytics, mitigated by its hybrid scripted/generative architecture designed for high controllability.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.20 | |
| Persistent Memory | 0.40 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.10 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.40 |
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.
Uses generative AI models alongside scripted options; vulnerable to prompt injection that could bypass the 'on-message' safety guarantees and cause reputational damage.
Not certain from the listing — details on training data ingestion, RAG, or vector stores for the custom courses are not provided, leaving potential risks of data poisoning or exfiltration unverified.
Not certain from the listing — the orchestration framework managing the transition between scripted and generative states is proprietary, presenting unknown risks regarding state manipulation or insecure tool integration.
Not certain from the listing — hosting, sandboxing, and API credential management details are omitted, leaving infrastructure-level vulnerabilities unassessed.
Features KPI-driven, real-time analytics on engagement, which could be vulnerable to manipulation or telemetry tampering if the reporting pipeline is not secured.
Not certain from the listing — while marketed as a 'responsible AI system' with 'maximum controllability,' specific compliance standards (e.g., SOC2, GDPR) or identity/access management controls are not detailed.
Not certain from the listing — there is no mention of multi-agent orchestration or marketplace integrations, suggesting a closed ecosystem with minimal external agent-to-agent risks.
MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).