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← Paramus

Paramus — agentic threat model

8.4AIVSS 8.4 · High

PARAMUS presents a high-risk profile due to its deep integration with critical pharmaceutical and chemical infrastructure (LIMS, MES, ELN). A compromise could lead to intellectual property theft or dangerous physical-world impacts on chemical manufacturing processes.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.4AARS uplift 0.97Factor sum 5.8/10Threat ×1.05Mitigation ×0.9
Autonomy of Action
0.60
Goal-Driven Planning
0.70
Self-Modification
0.20
Dynamic Tool Use
0.80
Persistent Memory
0.60
Contextual Awareness
0.70
Dynamic Identity
0.40
Multi-Agent Interactions
0.70
Non-Determinism
0.50
Opacity & Reflexivity
0.60

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.

L1 · Foundation Models⚠ not certain from listing

Not certain from the listing — The specific foundation models powering PARAMUS are not disclosed. Standard LLM risks like prompt injection or adversarial manipulation could lead to corrupted scientific reasoning or incorrect chemical formulations.

L2 · Data Operations✓ mapped

Integrates directly with ELN, LIMS, MES, and office files. This creates a highly sensitive data surface where data poisoning could corrupt research databases, and data exfiltration could leak proprietary chemical structures or drug formulas.

L3 · Agent Frameworks✓ mapped

Orchestrates specialized chemistry tools (RDKit, PSI4) and legacy in-house software. Insecure tool integration or prompt injection could allow attackers to execute arbitrary code via legacy APIs or abuse simulation tools to design hazardous compounds.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — The deployment architecture (cloud vs. on-premise) and sandboxing controls for executing chemistry code (like PSI4) are not specified, leaving potential gaps in container isolation and privilege management.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — While 'Conclusions (CoT)' combines AI with expert knowledge, there is no explicit mention of automated guardrails, real-time drift monitoring, or security logging for the agentic workflows.

L6 · Security & Compliance (cross-cutting)⚠ not certain from listing

Not certain from the listing — Despite operating in highly regulated sectors (pharma/chemical), the listing does not detail specific compliance certifications (e.g., GxP, SOC2) or identity/access management controls.

L7 · Agent Ecosystem✓ mapped

Features a multi-agent ecosystem ('Free Agents' and 'Legacy Agents' working together). This introduces risks of cascading failures, unauthorized agent-to-agent communication, and trust abuse if a single legacy agent is compromised.

MAESTRO — the 7-layer agentic threat-modeling framework (Cloud Security Alliance / Ken Huang).