AgentReadyHomeAgent Listing

← AI Teammates for Clinical Research

AI Teammates for Clinical Research — agentic threat model

9.2AIVSS 9.2 · Critical

Tilda presents a high-risk profile due to its integration into sensitive healthcare environments (clinical trials, regulatory compliance, and finance) across multiple specialized AI teammates. The lack of explicit security controls or compliance certifications in the listing, combined with multi-agent orchestration, elevates the potential impact of data poisoning or tool misuse.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.2AARS uplift 0.99Factor sum 5.5/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.60
Goal-Driven Planning
0.70
Self-Modification
0.20
Dynamic Tool Use
0.60
Persistent Memory
0.50
Contextual Awareness
0.70
Dynamic Identity
0.30
Multi-Agent Interactions
0.80
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 Tilda are not disclosed. Potential threats include adversarial prompt injection targeting clinical trial protocols or model misalignment leading to incorrect regulatory interpretations.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — While it mentions 'AI-powered source configuration' and 'data management', the exact data storage, vector databases, or RAG pipelines are not detailed. Threats include clinical data poisoning or unauthorized exfiltration of PHI/PII.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — Tilda operates as multiple 'teammates' (regulatory, data management, finance), implying complex orchestration, planning, and tool calling, but the specific framework (e.g., LangChain, AutoGen, proprietary) is undisclosed. Threats include insecure tool integration with clinical trial management systems (CTMS).

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — Hosting, sandboxing, and secrets management details are not provided. Given the healthcare context, secure hosting (e.g., HIPAA-compliant cloud) is critical, but the listing does not specify. Threats include container compromise or unauthorized access to clinical databases.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — No details are provided regarding evaluation frameworks, guardrails, or logging mechanisms. Gaps here could lead to undetected drift in clinical trial data processing or regulatory compliance monitoring.

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

Not certain from the listing — Although it operates in healthcare (implying HIPAA, GCP, or 21 CFR Part 11 requirements), the listing does not explicitly state its compliance certifications or access control mechanisms.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — Tilda features multiple 'teammates' (regulatory, data management, finance), suggesting a multi-agent setup or specialized sub-agents. However, the exact interaction protocols or trust boundaries between these teammates are not detailed.

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