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Automina — agentic threat model

8.8AIVSS 8.8 · High

Automina presents a high-risk profile due to its autonomous cloud-based browser automation capabilities, which are susceptible to indirect prompt injection and session hijacking if untrusted web content is processed without strict sandboxing and guardrails.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 7.5AARS uplift 1.25Factor sum 5.0/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.80
Goal-Driven Planning
0.70
Self-Modification
0.10
Dynamic Tool Use
0.80
Persistent Memory
0.30
Contextual Awareness
0.60
Dynamic Identity
0.50
Multi-Agent Interactions
0.10
Non-Determinism
0.60
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 — The underlying foundation model is not specified, leaving it vulnerable to standard LLM risks like prompt injection and adversarial manipulation without clear model-level guardrails.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — No details are provided regarding data storage, vector databases, or RAG operations, though the agent processes dynamic web data which could lead to indirect prompt injection.

L3 · Agent Frameworks✓ mapped

Automina uses a browser automation framework to execute multi-step 'missions'. This introduces significant risks of indirect prompt injection from untrusted web pages, leading to unauthorized tool execution or data exfiltration.

L4 · Deployment & Infrastructure✓ mapped

As a 'cloud base browser automation' tool, the infrastructure must securely sandbox browser instances to prevent container escape, IP reputation abuse, or lateral movement within the hosting environment.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — There is no mention of logging, observability, or real-time guardrails to monitor and intercept malicious browser actions or anomalous behavior.

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

Not certain from the listing — No compliance certifications (e.g., SOC2, ISO) or identity/access management controls are detailed for securing user sessions and credentials.

L7 · Agent Ecosystem⚠ not certain from listing

Not certain from the listing — The agent operates independently without any indicated multi-agent orchestration or marketplace ecosystem integrations.

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