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Image Text Editor — agentic threat model

5.9AIVSS 5.9 · Medium

The Image Text Editor exhibits very low agentic risk due to its single-turn, human-in-the-loop nature and lack of autonomous planning or tool-use capabilities. The primary security concerns are traditional web application risks, such as the exposure of sensitive user-uploaded screenshots and potential server-side vulnerabilities during image processing.

OWASP AIVSS score rationale

AIVSS = (CVSS_Base + AARS) × Mitigation_Factor, where AARS = (10 − CVSS_Base) × (Factor_Sum / 10) × ThM
CVSS base 5.3AARS uplift 0.61Factor sum 1.3/10Threat ×1.0Mitigation ×1.0
Autonomy of Action
0.10
Goal-Driven Planning
0.10
Self-Modification
0.00
Dynamic Tool Use
0.20
Persistent Memory
0.10
Contextual Awareness
0.30
Dynamic Identity
0.00
Multi-Agent Interactions
0.00
Non-Determinism
0.30
Opacity & Reflexivity
0.20

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 specialized OCR and diffusion/inpainting models rather than general LLMs. Primary threats include adversarial image inputs designed to bypass detection or exploit parser vulnerabilities, and potential model extraction of proprietary font-matching weights.

L2 · Data Operations⚠ not certain from listing

Not certain from the listing — processes user-uploaded images and screenshots in real-time. Threats include data exfiltration of sensitive PII or credentials contained within uploaded screenshots, and data poisoning if user uploads are retained for model fine-tuning.

L3 · Agent Frameworks⚠ not certain from listing

Not certain from the listing — likely structured as a deterministic image-processing pipeline rather than an agentic framework. Vulnerabilities could arise from insecure integration of third-party image manipulation libraries or font-rendering engines.

L4 · Deployment & Infrastructure⚠ not certain from listing

Not certain from the listing — deployed as a web and mobile browser application. Key threats include Server-Side Request Forgery (SSRF) if the tool allows loading images via URL, and resource exhaustion (DoS) during heavy image processing tasks.

L5 · Evaluation & Observability⚠ not certain from listing

Not certain from the listing — no mention of logging, abuse monitoring, or content guardrails. Gaps exist in detecting the upload of malicious payloads disguised as images or the processing of illicit/copyrighted material.

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

Not certain from the listing — closed-source, freemium model with no stated compliance certifications. Lacks clear privacy guarantees regarding the retention and deletion of user-uploaded images, posing GDPR/CCPA compliance risks.

L7 · Agent Ecosystem✓ mapped

This is a standalone vertical utility with no described multi-agent interactions, marketplace integrations, or external agent dependencies, making ecosystem-level threats negligible.

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.