AgentReadyHomeAgent Listing

← Emily | ESG Data Collection Agent

Emily | ESG Data Collection Agent — agentic threat model

7.8AIVSS 7.8 · High

Emily presents moderate risk due to its access to sensitive corporate ESG and manufacturing data for automated collection and reporting, where integrity failures could lead to regulatory non-compliance or greenwashing accusations.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 6.5AARS uplift 1.33Factor sum 3.8/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.60
Goal-Driven Planning
0.50
Self-Modification
0.10
Dynamic Tool Use
0.50
Persistent Memory
0.40
Contextual Awareness
0.50
Dynamic Identity
0.20
Multi-Agent Interactions
0.10
Non-Determinism
0.40
Opacity & Reflexivity
0.50

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 — likely utilizes commercial LLMs for parsing unstructured ESG documents. Primary threats include prompt injection leading to manipulated carbon calculations or misaligned reporting outputs.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — ingests manufacturing and utility data. Risks include data poisoning of the ESG knowledge base, leading to incorrect sustainability metrics, and unauthorized exfiltration of proprietary operational data.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — orchestrates multi-step collection and validation. Vulnerabilities could involve insecure tool integration when connecting to corporate ERPs, utility APIs, or external databases.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — deployed as a closed-source SaaS. Key threats include insecure storage of third-party API credentials and lack of sandboxing during data ingestion processes.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — requires robust validation guardrails to prevent hallucinated metrics, but specific logging, drift detection, or human-in-the-loop verification mechanisms are not detailed.

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

Not certain from the listing — must align with strict ESG reporting frameworks (e.g., CSRD, GHG Protocol), but the listing lacks details on access controls, audit trails, or compliance certifications.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — no multi-agent or ecosystem integrations are described, limiting immediate exposure to agent-to-agent trust abuse.

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