Mistral Large 24.11 — agentic threat model
Mistral Large 24.11 is a highly capable foundation model whose primary agentic risk stems from its advanced function-calling capabilities, which could be exploited via prompt injection to execute unauthorized API workflows in connected enterprise environments.
OWASP AIVSS score rationale
| Autonomy of Action | 0.30 | |
| Goal-Driven Planning | 0.40 | |
| Self-Modification | 0.10 | |
| Dynamic Tool Use | 0.60 | |
| Persistent Memory | 0.20 | |
| Contextual Awareness | 0.70 | |
| Dynamic Identity | 0.10 | |
| Multi-Agent Interactions | 0.20 | |
| Non-Determinism | 0.50 | |
| Opacity & Reflexivity | 0.70 |
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.
As a state-of-the-art foundation model, L1 threats are highly relevant. These include adversarial prompt injection, model stealing (especially for self-deployed instances), and potential training data poisoning or membership inference.
Not certain from the listing — while a 128K context window is supported for processing large documents, the listing does not detail specific RAG pipelines, vector database integrations, or data lineage controls.
Supports parallel and sequential function calling for workflow automation. This introduces risks of tool misuse, insecure tool integration, and unauthorized API execution if the model is manipulated via prompt injection.
Available via cloud APIs (Azure, AWS, GCP) or self-deployment. Threats include API key exposure, cloud infrastructure misconfigurations, and host/container compromise if self-deployed.
Not certain from the listing — the model is fine-tuned for factual accuracy and reduced hallucinations, but the listing does not specify built-in guardrails, real-time monitoring, or observability frameworks.
Not certain from the listing — commercial licensing is available, but specific compliance certifications (e.g., SOC2, ISO, EU AI Act alignment) or identity and access management controls are not detailed.
Not certain from the listing — although the model can power multi-agent systems, the listing does not describe a native multi-agent orchestration ecosystem or marketplace interactions.
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.