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← Scott by Lyzr AI

Scott by Lyzr AI — agentic threat model

9.0AIVSS 9.0 · Critical

Skott presents a high-risk profile due to its multi-agent autonomy and direct integration with publishing and social media APIs, where a compromise could lead to automated brand damage or data exfiltration.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 8.5AARS uplift 0.98Factor sum 6.2/10Threat ×1.05Mitigation ×0.95
Autonomy of Action
0.80
Goal-Driven Planning
0.80
Self-Modification
0.20
Dynamic Tool Use
0.70
Persistent Memory
0.60
Contextual Awareness
0.70
Dynamic Identity
0.30
Multi-Agent Interactions
0.90
Non-Determinism
0.60
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 LLMs are not named, but the agent integrates with 'top LLMs'. Threats include prompt injection bypassing content filters and model misalignment leading to inappropriate automated posts.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — Integrates with unnamed vector databases. Threats include knowledge-base poisoning where malicious SEO data is injected, leading the agent to generate spam or malicious links.

L3 · Agent Frameworks✓ mapped

Powered by Lyzr's Automata framework. Threats include framework-level vulnerabilities, insecure tool integration with publishing APIs, and memory poisoning across the multi-agent planning phases.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — Deployment details are omitted. Threats include the exposure of sensitive social media and blogging API credentials stored within the environment, and lack of execution sandboxing.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — Mentions 'human-like content filtering' and 'detailed analytics' but lacks security-specific guardrail details. Threats include evasion of content filters to publish unauthorized or harmful content.

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

Not certain from the listing — Described as 'enterprise-grade' but lacks explicit compliance certifications (e.g., SOC2, ISO). Threats include weak access controls allowing unauthorized users to trigger autonomous publishing workflows.

L7 · Agent Ecosystem✓ mapped

Utilizes a multi-agent architecture for specialized tasks (SEO, creation, distribution). Threats include agent-to-agent trust abuse, where a compromise in the research agent cascades to corrupt the publishing agent.

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.