Latest DeepSeek R2 — agentic threat model
DeepSeek R2 is primarily a highly efficient, large-scale foundation model (MoE) rather than an autonomous agent, meaning its primary risks lie in model alignment, input/output manipulation, and downstream integration vulnerabilities rather than autonomous execution.
OWASP AIVSS score rationale
| Autonomy of Action | 0.10 | |
| Goal-Driven Planning | 0.20 | |
| Self-Modification | 0.00 | |
| Dynamic Tool Use | 0.10 | |
| Persistent Memory | 0.10 | |
| Contextual Awareness | 0.50 | |
| Dynamic Identity | 0.00 | |
| Multi-Agent Interactions | 0.00 | |
| Non-Determinism | 0.70 | |
| 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.
As a 1.2T parameter Hybrid Mixture-of-Experts model, the primary threats are model stealing, adversarial prompt injection, and output misalignment. Its open-source nature makes it susceptible to local fine-tuning poisoning, while its high efficiency could be abused for low-cost, large-scale generation of malicious content.
Not certain from the listing — The listing mentions long-context processing and real-time data analytics, but does not detail the underlying training data lineage, RAG pipelines, or vector database integrations, leaving it potentially vulnerable to data poisoning or embedding inversion depending on how it is deployed.
Not certain from the listing — While capable of code generation and complex reasoning, no specific agentic orchestration framework, memory architecture, or tool-calling protocols are defined in the listing, making tool misuse risks highly dependent on downstream implementation.
Not certain from the listing — The model boasts high cluster utilization and FP16 peak performance, but the hosting infrastructure, sandboxing for code execution, and secrets management are not specified.
Not certain from the listing — No built-in guardrails, evaluation suites, or drift monitoring tools are mentioned in the directory listing.
Not certain from the listing — There is no mention of identity management, access control, or regulatory compliance (such as NIST or EU AI Act alignment) in the provided description.
Not certain from the listing — The listing does not describe any multi-agent orchestration or marketplace integrations, meaning cascading ecosystem failures are currently out of scope.
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.