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Livephoto.Online — agentic threat model

1.8AIVSS 1.8 · Low

Livephoto.Online is a local, browser-based media conversion utility with virtually zero agentic risk, as it lacks autonomous planning, LLM integration, or server-side data processing.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 3.5AARS uplift 0.0Factor sum 0.0/10Threat ×0.9Mitigation ×0.5
Autonomy of Action
0.00
Goal-Driven Planning
0.00
Self-Modification
0.00
Dynamic Tool Use
0.00
Persistent Memory
0.00
Contextual Awareness
0.00
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.00
Opacity & Reflexivity
0.00

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 tool does not appear to use any foundation LLMs or neural models; it relies on FFmpeg compiled to WebAssembly for local media processing.

L2 · Data Operations✓ mapped

All data operations occur locally in the user's browser sandbox. There are no remote vector stores, training pipelines, or data ingestion risks, eliminating data exfiltration and poisoning vectors.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — Despite the 'AI Agents Frameworks' tag, there is no evidence of an orchestration framework, planning loops, or LLM tool-calling mechanisms.

L4 · Deployment & Infrastructure✓ mapped

Deployed as a static web application running in the client's browser. The primary infrastructure threat is front-end compromise (e.g., malicious JS injection/XSS) rather than server-side container escape.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — There are no active LLM guardrails, evaluation frameworks, or monitoring tools mentioned, which is expected for a local, deterministic utility.

L6 · Security & Compliance (cross-cutting)✓ mapped

Compliance risk is extremely low because no user data is uploaded, stored, or processed on external servers, aligning well with strict privacy regulations (GDPR/CCPA).

L7 · Agent Ecosystem✓ mapped

No multi-agent interactions, marketplace integrations, or external agent dependencies exist for this standalone browser tool.

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