AgentReadyHomeAgent ListingPricing

← Mailmodo AI

Mailmodo AI — agentic threat model

8.7AIVSS 8.7 · High

Mailmodo AI presents a moderate-to-high risk profile primarily due to its integration with email delivery systems and customer databases, where compromise could lead to large-scale phishing, spam campaigns, or customer data exfiltration.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.0AARS uplift 0.72Factor sum 3.6/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.40
Goal-Driven Planning
0.50
Self-Modification
0.10
Dynamic Tool Use
0.40
Persistent Memory
0.40
Contextual Awareness
0.50
Dynamic Identity
0.20
Multi-Agent Interactions
0.10
Non-Determinism
0.60
Opacity & Reflexivity
0.40

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 underlying foundation models used for generating subject lines, templates, and campaign plans are unspecified, leaving potential exposure to prompt injection or model-reprogramming attacks that could generate malicious email content.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — The agent processes customer lists and campaign performance data for 'AI Segmentation' and reporting, presenting risks of data exfiltration or unauthorized access to personally identifiable information (PII) if the data pipeline is compromised.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — Orchestration of the 'AI Journey Builder' and 'Mailmodo Co-Pilot' suggests an agentic framework that translates user goals into campaign workflows, which could be vulnerable to indirect prompt injection via incoming customer data or email replies.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — The hosting environment and API integrations for email dispatch are not detailed, raising concerns about secure credential storage (e.g., API keys for ESPs) and isolation of execution environments.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — It is unclear what guardrails or observability tools are in place to monitor generated email content for spam, phishing indicators, or brand-damaging material before automated dispatch.

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

Not certain from the listing — No specific compliance standards (such as SOC2, GDPR, or CAN-SPAM alignment controls) are detailed in the directory listing to guarantee secure data handling and user consent verification.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — The agent operates primarily as a horizontal SaaS tool; there is no indication of multi-agent collaboration or external agent 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.